def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(ComparisonStatistics,
cls).getInputSpecification()
KindInputEnumType = InputData.makeEnumType(
"kind", "kindType", ["uniformBins", "equalProbability"])
KindInput = InputData.parameterInputFactory(
"kind", contentType=KindInputEnumType)
KindInput.addParam("numBins", InputData.IntegerType, False)
KindInput.addParam("binMethod", InputData.StringType, False)
inputSpecification.addSub(KindInput)
## FIXME: Is this class necessary?
class CSCompareInput(InputData.ParameterInput):
"""
class for reading in the compare block in comparison statistics
"""
CSCompareInput.createClass("compare", False)
CSDataInput = InputData.parameterInputFactory(
"data", contentType=InputData.StringType)
CSCompareInput.addSub(CSDataInput)
CSReferenceInput = InputData.parameterInputFactory("reference")
CSReferenceInput.addParam("name", InputData.StringType, True)
CSCompareInput.addSub(CSReferenceInput)
inputSpecification.addSub(CSCompareInput)
FZInput = InputData.parameterInputFactory(
"fz", contentType=InputData.StringType) #bool
inputSpecification.addSub(FZInput)
CSInterpolationEnumType = InputData.makeEnumType(
"csinterpolation", "csinterpolationType", ["linear", "quadratic"])
CSInterpolationInput = InputData.parameterInputFactory(
"interpolation", contentType=CSInterpolationEnumType)
inputSpecification.addSub(CSInterpolationInput)
DistributionInput = InputData.parameterInputFactory(
"Distribution", contentType=InputData.StringType)
DistributionInput.addParam("class", InputData.StringType)
DistributionInput.addParam("type", InputData.StringType)
inputSpecification.addSub(DistributionInput)
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(Code, cls).getInputSpecification()
inputSpecification.setStrictMode(
False) #Code interfaces can allow new elements.
inputSpecification.addSub(
InputData.parameterInputFactory("executable",
contentType=InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("preexec",
contentType=InputData.StringType))
## Begin command line arguments tag
ClargsInput = InputData.parameterInputFactory("clargs")
ClargsTypeInput = InputData.makeEnumType(
"clargsType", "clargsTypeType",
["text", "input", "output", "prepend", "postpend"])
ClargsInput.addParam("type", ClargsTypeInput, True)
ClargsInput.addParam("arg", InputData.StringType, False)
ClargsInput.addParam("extension", InputData.StringType, False)
inputSpecification.addSub(ClargsInput)
## End command line arguments tag
## Begin file arguments tag
FileargsInput = InputData.parameterInputFactory("fileargs")
FileargsTypeInput = InputData.makeEnumType(
"fileargsType", "fileargsTypeType",
["input", "output", "moosevpp"])
FileargsInput.addParam("type", FileargsTypeInput, True)
FileargsInput.addParam("arg", InputData.StringType, False)
FileargsInput.addParam("extension", InputData.StringType, False)
inputSpecification.addSub(FileargsInput)
## End file arguments tag
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(DateBase, cls).getInputSpecification()
inputSpecification.addParam("directory", InputData.StringType)
inputSpecification.addParam("filename", InputData.StringType)
inputSpecification.addParam("readMode", InputData.makeEnumType("readMode","readModeType",["overwrite","read"]), True)
inputSpecification.addSub(InputData.parameterInputFactory("variables", contentType=InputData.StringListType))
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(DTW, cls).getInputSpecification()
orderInputType = InputData.makeEnumType("order","orderType",["0","1"])
inputSpecification.addSub(InputData.parameterInputFactory("order",contentType=orderInputType),quantity=InputData.Quantity.one)
inputSpecification.addSub(InputData.parameterInputFactory("localDistance",contentType=InputData.StringType),quantity=InputData.Quantity.one)
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(FTImporter, cls).getInputSpecification()
fileAllowedFormats = InputData.makeEnumType("FTFileFormat",
"FTFileFormatType",
["OpenPSA"])
inputSpecification.addSub(
InputData.parameterInputFactory("fileFormat",
contentType=fileAllowedFormats))
inputSpecification.addSub(
InputData.parameterInputFactory("topEventID",
contentType=InputData.StringType))
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(Model, cls).getInputSpecification()
inputSpecification.addParam("subType", InputData.StringType, True)
## Begin alias tag
AliasInput = InputData.parameterInputFactory("alias", contentType=InputData.StringType)
AliasInput.addParam("variable", InputData.StringType, True)
AliasTypeInput = InputData.makeEnumType("aliasType","aliasTypeType",["input","output"])
AliasInput.addParam("type", AliasTypeInput, True)
inputSpecification.addSub(AliasInput)
## End alias tag
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(Metric, cls).getInputSpecification()
featuresInput = InputData.parameterInputFactory(
"Features", contentType=InputData.StringListType)
featuresInput.addParam("type", InputData.StringType)
inputSpecification.addSub(featuresInput)
targetsInput = InputData.parameterInputFactory(
"Targets", contentType=InputData.StringListType)
targetsInput.addParam("type", InputData.StringType)
inputSpecification.addSub(targetsInput)
multiOutputInput = InputData.parameterInputFactory(
"multiOutput", contentType=InputData.StringType)
inputSpecification.addSub(multiOutputInput)
multiOutput = InputData.makeEnumType(
'MultiOutput', 'MultiOutputType',
['mean', 'max', 'min', 'raw_values'])
multiOutputInput = InputData.parameterInputFactory(
"multiOutput", contentType=multiOutput)
inputSpecification.addSub(multiOutputInput)
weightInput = InputData.parameterInputFactory(
"weight", contentType=InputData.FloatListType)
inputSpecification.addSub(weightInput)
pivotParameterInput = InputData.parameterInputFactory(
"pivotParameter", contentType=InputData.StringType)
inputSpecification.addSub(pivotParameterInput)
metricInput = InputData.parameterInputFactory(
"Metric", contentType=InputData.StringType)
metricInput.addParam("class", InputData.StringType, True)
metricInput.addParam("type", InputData.StringType, True)
inputSpecification.addSub(metricInput)
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls. This one seems a bit excessive, are all of these for this class?
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(ROM, cls).getInputSpecification()
IndexSetInputType = InputData.makeEnumType(
"indexSet", "indexSetType",
["TensorProduct", "TotalDegree", "HyperbolicCross", "Custom"])
CriterionInputType = InputData.makeEnumType(
"criterion", "criterionType",
["bic", "aic", "gini", "entropy", "mse"])
InterpolationInput = InputData.parameterInputFactory(
'Interpolation', contentType=InputData.StringType)
InterpolationInput.addParam("quad", InputData.StringType, False)
InterpolationInput.addParam("poly", InputData.StringType, False)
InterpolationInput.addParam("weight", InputData.FloatType, False)
inputSpecification.addSub(
InputData.parameterInputFactory('Features',
contentType=InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory('Target',
contentType=InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("IndexPoints",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("IndexSet", IndexSetInputType))
inputSpecification.addSub(
InputData.parameterInputFactory('pivotParameter',
contentType=InputData.StringType))
inputSpecification.addSub(InterpolationInput)
inputSpecification.addSub(
InputData.parameterInputFactory("PolynomialOrder",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("SobolOrder",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("SparseGrid",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("persistence",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("gradient", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("simplification",
InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("graph", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("beta", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("knn", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("partitionPredictor",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("smooth", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("kernel", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("bandwidth", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("p", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("SKLtype", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("n_iter", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("tol", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("alpha_1", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("alpha_2", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("lambda_1", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("lambda_2", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("compute_score",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("threshold_lambda",
InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("fit_intercept",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("normalize",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("verbose",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("alpha", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("l1_ratio", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("max_iter", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("warm_start",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("positive",
InputData.StringType)) #bool?
inputSpecification.addSub(
InputData.parameterInputFactory("eps", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("n_alphas", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("precompute",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("n_nonzero_coefs",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("fit_path",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("max_n_alphas",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("criterion", CriterionInputType))
inputSpecification.addSub(
InputData.parameterInputFactory("penalty",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("dual",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("C", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("intercept_scaling",
InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("class_weight",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("random_state",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("cv", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("shuffle",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("loss",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("epsilon", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("eta0", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("solver",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("alphas", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("scoring", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("gcv_mode",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("store_cv_values",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("learning_rate",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("power_t", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("multi_class",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("kernel",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("degree", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("gamma", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("coef0", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("probability",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("shrinking",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("cache_size", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("nu", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("code_size", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("fit_prior",
InputData.StringType)) #bool
inputSpecification.addSub(
InputData.parameterInputFactory("class_prior",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("binarize", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("n_neighbors",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("weights",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("algorithm",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("leaf_size",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("metric",
InputData.StringType)) #enum?
inputSpecification.addSub(
InputData.parameterInputFactory("radius", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("outlier_label",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("shrink_threshold",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("priors", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("reg_param", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("splitter",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("max_features",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("max_depth", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("min_samples_split",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("min_samples_leaf",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("max_leaf_nodes",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("regr",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("corr",
InputData.StringType)) #enum?
inputSpecification.addSub(
InputData.parameterInputFactory("beta0", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("storage_mode",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("theta0", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("thetaL", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("thetaU", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("nugget", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("optimizer",
InputData.StringType)) #enum
inputSpecification.addSub(
InputData.parameterInputFactory("random_start",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("Pmax", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("Pmin", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("Qmax", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("Qmin", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("outTruncation",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("Fourier", InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("FourierOrder",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("reseedCopies",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("reseedValue",
InputData.IntegerType))
# inputs for neural_network
inputSpecification.addSub(
InputData.parameterInputFactory("hidden_layer_sizes",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("activation",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("batch_size",
InputData.StringType))
inputSpecification.addSub(
InputData.parameterInputFactory("learning_rate_init",
InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("momentum", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("nesterovs_momentum",
InputData.StringType)) # bool
inputSpecification.addSub(
InputData.parameterInputFactory("early_stopping",
InputData.StringType)) # bool
inputSpecification.addSub(
InputData.parameterInputFactory("validation_fraction",
InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("beta_1", InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("beta_2", InputData.FloatType))
# PolyExp
inputSpecification.addSub(
InputData.parameterInputFactory("maxNumberExpTerms",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("numberExpTerms",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("maxPolyOrder",
InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("polyOrder",
InputData.IntegerType))
coeffRegressorEnumType = InputData.makeEnumType(
"coeffRegressor", "coeffRegressorType",
["poly", "spline", "nearest"])
inputSpecification.addSub(
InputData.parameterInputFactory(
"coeffRegressor", contentType=coeffRegressorEnumType))
# DMD
inputSpecification.addSub(
InputData.parameterInputFactory("rankSVD", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("energyRankSVD",
InputData.FloatType))
inputSpecification.addSub(
InputData.parameterInputFactory("rankTLSQ", InputData.IntegerType))
inputSpecification.addSub(
InputData.parameterInputFactory("exactModes", InputData.BoolType))
inputSpecification.addSub(
InputData.parameterInputFactory("optimized", InputData.BoolType))
inputSpecification.addSub(
InputData.parameterInputFactory("dmdType", InputData.StringType))
#Estimators can include ROMs, and so because baseNode does a copy, this
#needs to be after the rest of ROMInput is defined.
EstimatorInput = InputData.parameterInputFactory(
'estimator',
contentType=InputData.StringType,
baseNode=inputSpecification)
EstimatorInput.addParam("estimatorType", InputData.StringType, False)
#The next lines are to make subType and name not required.
EstimatorInput.addParam("subType", InputData.StringType, False)
EstimatorInput.addParam("name", InputData.StringType, False)
inputSpecification.addSub(EstimatorInput)
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for
class cls. This one seems a bit excessive, are all of these for this class?
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for
specifying input of cls.
"""
inputSpecification = super(ROM, cls).getInputSpecification()
IndexSetInputType = InputData.makeEnumType("indexSet","indexSetType",["TensorProduct","TotalDegree","HyperbolicCross","Custom"])
CriterionInputType = InputData.makeEnumType("criterion", "criterionType", ["bic","aic","gini","entropy","mse"])
# general
inputSpecification.addSub(InputData.parameterInputFactory('Features',contentType=InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory('Target',contentType=InputData.StringType))
# segmenting and clustering
segment = InputData.parameterInputFactory("Segment", strictMode=True)
segmentGroups = InputData.makeEnumType('segmentGroup', 'sesgmentGroupType', ['segment', 'cluster'])
segment.addParam('grouping', segmentGroups)
subspace = InputData.parameterInputFactory('subspace', InputData.StringType)
subspace.addParam('divisions', InputData.IntegerType, False)
subspace.addParam('pivotLength', InputData.FloatType, False)
subspace.addParam('shift', InputData.StringType, False)
segment.addSub(subspace)
clsfr = InputData.parameterInputFactory('Classifier', strictMode=True, contentType=InputData.StringType)
clsfr.addParam('class', InputData.StringType, True)
clsfr.addParam('type', InputData.StringType, True)
segment.addSub(clsfr)
metric = InputData.parameterInputFactory('Metric', strictMode=True, contentType=InputData.StringType)
metric.addParam('class', InputData.StringType, True)
metric.addParam('type', InputData.StringType, True)
segment.addSub(metric)
feature = InputData.parameterInputFactory('feature', strictMode=True, contentType=InputData.StringType)
feature.addParam('weight', InputData.FloatType)
segment.addSub(feature)
inputSpecification.addSub(segment)
# unsorted
inputSpecification.addSub(InputData.parameterInputFactory("persistence", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("gradient", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("simplification", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("graph", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("beta", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("knn", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("partitionPredictor", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("smooth", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("kernel", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("bandwidth", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("p", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("SKLtype", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("n_iter", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("tol", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("alpha_1", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("alpha_2", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("lambda_1", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("lambda_2", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("compute_score", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("threshold_lambda", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("fit_intercept", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("normalize", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("verbose", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("alpha", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("l1_ratio", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("max_iter", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("warm_start", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("positive", InputData.StringType)) #bool?
inputSpecification.addSub(InputData.parameterInputFactory("eps", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("n_alphas", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("precompute", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("n_nonzero_coefs", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("fit_path", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("max_n_alphas", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("criterion", CriterionInputType))
inputSpecification.addSub(InputData.parameterInputFactory("penalty", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("dual", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("C", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("intercept_scaling", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("class_weight", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("random_state", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("cv", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("shuffle", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("loss", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("epsilon", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("eta0", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("solver", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("alphas", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("scoring", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("gcv_mode", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("store_cv_values", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("learning_rate", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("power_t", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("multi_class", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("kernel", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("degree", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("gamma", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("coef0", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("probability", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("shrinking", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("cache_size", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("nu", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("code_size", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("fit_prior", InputData.StringType)) #bool
inputSpecification.addSub(InputData.parameterInputFactory("class_prior", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("binarize", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("n_neighbors", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("weights", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("algorithm", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("leaf_size", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("metric", InputData.StringType)) #enum?
inputSpecification.addSub(InputData.parameterInputFactory("radius", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("outlier_label", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("shrink_threshold", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("priors", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("reg_param", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("splitter", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("max_features", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("max_depth", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("min_samples_split", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("min_samples_leaf", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("max_leaf_nodes", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("regr", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("corr", InputData.StringType)) #enum?
inputSpecification.addSub(InputData.parameterInputFactory("beta0", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("storage_mode", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("theta0", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("thetaL", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("thetaU", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("nugget", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("optimizer", InputData.StringType)) #enum
inputSpecification.addSub(InputData.parameterInputFactory("random_start", InputData.IntegerType))
# GaussPolynomialROM and HDMRRom
inputSpecification.addSub(InputData.parameterInputFactory("IndexPoints", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("IndexSet", contentType=IndexSetInputType))
inputSpecification.addSub(InputData.parameterInputFactory('pivotParameter', contentType=InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("PolynomialOrder", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("SobolOrder", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("SparseGrid", InputData.StringType))
InterpolationInput = InputData.parameterInputFactory('Interpolation', contentType=InputData.StringType)
InterpolationInput.addParam("quad", InputData.StringType, False)
InterpolationInput.addParam("poly", InputData.StringType, False)
InterpolationInput.addParam("weight", InputData.FloatType, False)
inputSpecification.addSub(InterpolationInput)
# ARMA
inputSpecification.addSub(InputData.parameterInputFactory('correlate', InputData.StringListType))
inputSpecification.addSub(InputData.parameterInputFactory("P", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("Q", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("seed", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("reseedCopies", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("Fourier", contentType=InputData.FloatListType))
inputSpecification.addSub(InputData.parameterInputFactory("preserveInputCDF", contentType=InputData.BoolType))
### ARMA zero filter
zeroFilt = InputData.parameterInputFactory('ZeroFilter', contentType=InputData.StringType)
zeroFilt.addParam('tol', InputData.FloatType)
inputSpecification.addSub(zeroFilt)
### ARMA out truncation
outTrunc = InputData.parameterInputFactory('outTruncation', contentType=InputData.StringListType)
domainEnumType = InputData.makeEnumType('domain', 'truncateDomainType', ['positive', 'negative'])
outTrunc.addParam('domain', domainEnumType, True)
inputSpecification.addSub(outTrunc)
### ARMA specific fourier
specFourier = InputData.parameterInputFactory('SpecificFourier', strictMode=True)
specFourier.addParam("variables", InputData.StringListType, True)
specFourier.addSub(InputData.parameterInputFactory('periods', contentType=InputData.FloatListType))
inputSpecification.addSub(specFourier)
# inputs for neural_network
inputSpecification.addSub(InputData.parameterInputFactory("hidden_layer_sizes", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("activation", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("batch_size", InputData.StringType))
inputSpecification.addSub(InputData.parameterInputFactory("learning_rate_init", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("momentum", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("nesterovs_momentum", InputData.StringType)) # bool
inputSpecification.addSub(InputData.parameterInputFactory("early_stopping", InputData.StringType)) # bool
inputSpecification.addSub(InputData.parameterInputFactory("validation_fraction", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("beta_1", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("beta_2", InputData.FloatType))
# PolyExp
inputSpecification.addSub(InputData.parameterInputFactory("maxNumberExpTerms", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("numberExpTerms", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("maxPolyOrder", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("polyOrder", InputData.IntegerType))
coeffRegressorEnumType = InputData.makeEnumType("coeffRegressor","coeffRegressorType",["poly","spline","nearest"])
inputSpecification.addSub(InputData.parameterInputFactory("coeffRegressor", contentType=coeffRegressorEnumType))
# DMD
inputSpecification.addSub(InputData.parameterInputFactory("rankSVD", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("energyRankSVD", InputData.FloatType))
inputSpecification.addSub(InputData.parameterInputFactory("rankTLSQ", InputData.IntegerType))
inputSpecification.addSub(InputData.parameterInputFactory("exactModes", InputData.BoolType))
inputSpecification.addSub(InputData.parameterInputFactory("optimized", InputData.BoolType))
inputSpecification.addSub(InputData.parameterInputFactory("dmdType", InputData.StringType))
#Estimators can include ROMs, and so because baseNode does a copy, this
#needs to be after the rest of ROMInput is defined.
EstimatorInput = InputData.parameterInputFactory('estimator', contentType=InputData.StringType, baseNode=inputSpecification)
EstimatorInput.addParam("estimatorType", InputData.StringType, False)
#The next lines are to make subType and name not required.
EstimatorInput.addParam("subType", InputData.StringType, False)
EstimatorInput.addParam("name", InputData.StringType, False)
inputSpecification.addSub(EstimatorInput)
return inputSpecification
def getInputSpecification(cls):
"""
Method to get a reference to a class that specifies the input data for class cls.
@ In, cls, the class for which we are retrieving the specification
@ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls.
"""
#### FULL INPUT LIST SPSA #### -> * means part of FiniteDiff as well
# so far, there's no distinction between optimizers, so all the input from SPSA is here. Fix this when we sort out optimizers.
inputSpecification = super(Optimizer, cls).getInputSpecification()
# assembled objects
targEval = InputData.parameterInputFactory(
'TargetEvaluation',
contentType=InputData.StringType,
strictMode=True)
targEval.addParam('type', InputData.StringType, True)
targEval.addParam('class', InputData.StringType, True)
inputSpecification.addSub(targEval)
sampler = InputData.parameterInputFactory(
'Sampler', contentType=InputData.StringType, strictMode=True)
sampler.addParam('type', InputData.StringType, True)
sampler.addParam('class', InputData.StringType, True)
inputSpecification.addSub(sampler)
function = InputData.parameterInputFactory(
'Function', contentType=InputData.StringType, strictMode=True)
function.addParam('type', InputData.StringType, True)
function.addParam('class', InputData.StringType, True)
inputSpecification.addSub(function)
precond = InputData.parameterInputFactory(
'Preconditioner',
contentType=InputData.StringType,
strictMode=True)
precond.addParam('type', InputData.StringType, True)
precond.addParam('class', InputData.StringType, True)
inputSpecification.addSub(precond)
# variable
## was also part of Sampler, but we need to rewrite variable, so remove it first
inputSpecification.removeSub('variable')
variable = InputData.parameterInputFactory('variable', strictMode=True)
variable.addParam("name", InputData.StringType, True)
variable.addParam("shape", InputData.IntegerListType, required=False)
upperBound = InputData.parameterInputFactory(
'upperBound', contentType=InputData.FloatType, strictMode=True)
lowerBound = InputData.parameterInputFactory(
'lowerBound', contentType=InputData.FloatType, strictMode=True)
initial = InputData.parameterInputFactory(
'initial', contentType=InputData.StringListType)
variable.addSub(upperBound)
variable.addSub(lowerBound)
variable.addSub(initial)
inputSpecification.addSub(variable)
# constant -> use the Sampler's specs.
# objectVar
objectVar = InputData.parameterInputFactory(
'objectVar', contentType=InputData.StringType, strictMode=True)
inputSpecification.addSub(objectVar)
# initialization
init = InputData.parameterInputFactory('initialization',
strictMode=True)
whenWriteEnum = InputData.makeEnumType('whenWriteEnum',
'whenWriteType',
['final', 'every'])
limit = InputData.parameterInputFactory(
'limit', contentType=InputData.IntegerType)
seed = InputData.parameterInputFactory(
'initialSeed', contentType=InputData.IntegerType)
minmaxEnum = InputData.makeEnumType('MinMax', 'OptimizerTypeType',
['min', 'max'])
minmax = InputData.parameterInputFactory('type',
contentType=minmaxEnum)
thresh = InputData.parameterInputFactory(
'thresholdTrajRemoval', contentType=InputData.FloatType)
write = InputData.parameterInputFactory('writeSteps',
contentType=whenWriteEnum)
init.addSub(limit)
init.addSub(seed)
init.addSub(minmax)
init.addSub(thresh)
init.addSub(write)
inputSpecification.addSub(init)
# convergence
conv = InputData.parameterInputFactory('convergence', strictMode=True)
itLim = InputData.parameterInputFactory(
'iterationLimit', contentType=InputData.IntegerType)
pers = InputData.parameterInputFactory(
'persistence', contentType=InputData.IntegerType)
rel = InputData.parameterInputFactory('relativeThreshold',
contentType=InputData.FloatType)
abst = InputData.parameterInputFactory('absoluteThreshold',
contentType=InputData.FloatType)
grad = InputData.parameterInputFactory('gradientThreshold',
contentType=InputData.FloatType)
minstep = InputData.parameterInputFactory(
'minStepSize', contentType=InputData.FloatType)
grow = InputData.parameterInputFactory('gainGrowthFactor',
contentType=InputData.FloatType)
shrink = InputData.parameterInputFactory(
'gainShrinkFactor', contentType=InputData.FloatType)
conv.addSub(itLim)
conv.addSub(pers)
conv.addSub(rel)
conv.addSub(abst)
conv.addSub(grad)
conv.addSub(minstep)
conv.addSub(grow)
conv.addSub(shrink)
inputSpecification.addSub(conv)
# parameter
param = InputData.parameterInputFactory('parameter', strictMode=True)
stochEnum = InputData.makeEnumType('StochDistEnum', 'StochDistType',
['Hypersphere', 'Bernoulli'])
num = InputData.parameterInputFactory(
'numGradAvgIterations', contentType=InputData.IntegerType)
stoch = InputData.parameterInputFactory('stochasticDistribution',
contentType=stochEnum)
bisect = InputData.parameterInputFactory(
'innerBisectionThreshold', contentType=InputData.FloatType)
loop = InputData.parameterInputFactory(
'innerLoopLimit', contentType=InputData.IntegerType)
param.addSub(num)
param.addSub(stoch)
param.addSub(bisect)
param.addSub(loop)
inputSpecification.addSub(param)
return inputSpecification