python.tools Namespace Reference

Classes
class	Matrix

Functions
def	appendToDict (dict, key, val)
def	checkData (data)
def	gzOpen (filename, mode="r")
def	isARFFFile (filename)
def	makedir (path, verbose=False)
def	normalize (data, border=0.0, filename=None, minvals=None, maxvals=None, verbose=False)
def	normalizeClasses (data, border=0.0, minborder=-sys.maxsize-1, verbose=False)
def	readAlpha (filename)
def	readAlphaARFF (filename)
def	readAlphaTrivial (filename, delim=None)
def	readCheckpoint (filename)
def	readData (filename)
def	readDataARFF (filename)
def	readDataTrivial (filename, delim=None, hasclass=True)
def	readGrid (filename)
def	readGridAlpha (fnamegrid, fnamealpha)
def	readNormfile (filename)
def	split_DataVector_by_proportion (data, proportion)
def	split_DataVectors_by_proportion_stratified (data, classes, proportion)
def	split_n_folds (data, num_partitions, seed=None)
def	split_n_folds_sequential (data, num_partitions)
def	split_n_folds_stratified (data, num_partitions, seed=None)
def	writeAlphaARFF (filename, alpha)
def	writeCheckpoint (filename, grid, alpha, adaption=None, fold=None)
def	writeDataARFF (data, merge=False)
def	writeDataMaple (data, merge)
def	writeDataVectorMaple (data, filename, format="%s", maple_name="X", check=True)
def	writeGnuplot (filename, grid, alpha, resolution, mode="w", data=None, fvals=None)
def	writeGnuplotFctn (filename, dim, fctn, resolution, mode="w")
def	writeGnuplotGrid (filename, grid)
def	writeGrid (filename, grid)
def	writeLockFile (filename, txt, mode="a")
def	writeNormfile (filename, border, minvals, maxvals)
def	writeStats (filename, txt, mode="a")
def	writeStringToFile (s, filename, check=True)

Variables
int	ARFF = 1
dictionary	base_types
dictionary	CModes
int	NOTAFILE = -1
int	SIMPLE = 0

Function Documentation

appendToDict()

def python.tools.appendToDict	(		dict,
			key,
			val
	)

checkData()

def python.tools.checkData

(

data

)

gzOpen()

def python.tools.gzOpen	(		filename,
			mode = "r"
	)

Referenced by python.tools.isARFFFile(), python.tools.readDataARFF(), python.tools.readDataTrivial(), python.tools.readGrid(), python.tools.readNormfile(), python.toolsExtended.readReferenceMatrix(), python.tools.writeAlphaARFF(), python.tools.writeDataARFF(), python.tools.writeGnuplot(), python.tools.writeGnuplotFctn(), python.tools.writeGrid(), python.tools.writeLockFile(), and python.tools.writeStringToFile().

isARFFFile()

def python.tools.isARFFFile

(

filename

)

References python.tools.gzOpen().

Referenced by python.tools.readAlpha(), and python.tools.readData().

makedir()

def python.tools.makedir	(		path,
			verbose = False
	)

normalize()

def python.tools.normalize	(		data,
			border = 0.0,
			filename = None,
			minvals = None,
			maxvals = None,
			verbose = False
	)

References python.tools.writeNormfile().

normalizeClasses()

def python.tools.normalizeClasses	(		data,
			border = 0.0,
			minborder = -sys.maxsize-1,
			verbose = False
	)

readAlpha()

def python.tools.readAlpha

(

filename

)

References python.tools.isARFFFile(), python.tools.readAlphaARFF(), and python.tools.readAlphaTrivial().

Referenced by python.classifier.openAlphaFile(), and python.tools.readGridAlpha().

readAlphaARFF()

def python.tools.readAlphaARFF

(

filename

)

References python.tools.readDataARFF().

Referenced by python.uq.dists.SGDEdist.SGDEdist.byFiles(), python.tools.readAlpha(), and python.tools.readCheckpoint().

readAlphaTrivial()

def python.tools.readAlphaTrivial	(		filename,
			delim = None
	)

References python.tools.readDataTrivial().

Referenced by python.tools.readAlpha().

readCheckpoint()

def python.tools.readCheckpoint

(

filename

)

References python.tools.readAlphaARFF(), and python.tools.readGrid().

readData()

def python.tools.readData

(

filename

)

References python.tools.isARFFFile(), python.tools.readDataARFF(), and python.tools.readDataTrivial().

Referenced by python.classifier.openFile().

readDataARFF()

def python.tools.readDataARFF

(

filename

)

References python.tools.gzOpen().

Referenced by python.toolsExtended.buildCoefficientVectorFromFile(), python.toolsExtended.openFile(), python.tools.readAlphaARFF(), and python.tools.readData().

readDataTrivial()

def python.tools.readDataTrivial	(		filename,
			delim = None,
			hasclass = True
	)

References python.tools.gzOpen().

Referenced by python.uq.dists.SGDEdist.SGDEdist.byFiles(), python.tools.readAlphaTrivial(), and python.tools.readData().

readGrid()

def python.tools.readGrid

(

filename

)

References python.tools.gzOpen().

Referenced by python.uq.dists.SGDEdist.SGDEdist.byFiles(), python.classifier.constructGrid(), python.tools.readCheckpoint(), and python.tools.readGridAlpha().

readGridAlpha()

def python.tools.readGridAlpha	(		fnamegrid,
			fnamealpha
	)

References python.tools.readAlpha(), and python.tools.readGrid().

readNormfile()

def python.tools.readNormfile

(

filename

)

References python.tools.gzOpen(), and sgpp::combigrid.split().

Referenced by python.classifier.doEvalStdin().

split_DataVector_by_proportion()

def python.tools.split_DataVector_by_proportion	(		data,
			proportion
	)

References python.tools.split_DataVectors_by_proportion_stratified().

split_DataVectors_by_proportion_stratified()

def python.tools.split_DataVectors_by_proportion_stratified	(		data,
			classes,
			proportion
	)

Referenced by python.classifier.performFoldNew(), and python.tools.split_DataVector_by_proportion().

split_n_folds()

def python.tools.split_n_folds	(		data,
			num_partitions,
			seed = None
	)

Referenced by python.classifier.doFold().

split_n_folds_sequential()

def python.tools.split_n_folds_sequential	(		data,
			num_partitions
	)

Referenced by python.classifier.doFolds().

split_n_folds_stratified()

def python.tools.split_n_folds_stratified	(		data,
			num_partitions,
			seed = None
	)

Referenced by python.classifier.doFoldr(), and python.classifier.doFoldStratified().

writeAlphaARFF()

def python.tools.writeAlphaARFF	(		filename,
			alpha
	)

References python.tools.gzOpen().

Referenced by python.classifier.doNormal(), python.classifier.doTest(), python.uq.dists.optimization.estimateDensitySGDE.estimateDensitySGDE(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.sampleGrids(), python.tools.writeCheckpoint(), and python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.writeCheckpoints().

writeCheckpoint()

def python.tools.writeCheckpoint	(		filename,
			grid,
			alpha,
			adaption = None,
			fold = None
	)

References python.tools.writeAlphaARFF(), and python.tools.writeGrid().

Referenced by python.classifier.doTest(), python.classifier.performFold(), python.classifier.performFoldNew(), python.classifier.performFoldRegression(), and python.classifier.run().

writeDataARFF()

def python.tools.writeDataARFF	(		data,
			merge = False
	)

References python.tools.gzOpen().

Referenced by python.classifier.doApply(), python.classifier.doEval(), python.uq.dists.optimization.estimateDensityDTrees.estimateDensityDTrees(), python.uq.dists.optimization.estimateDensityKDE.estimateDensityKDE(), python.uq.dists.optimization.estimateDensitySGDE.estimateDensitySGDE(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.sampleGrids(), python.uq.analysis.mc.MCAnalysis.MCAnalysis.writeMoments(), python.uq.analysis.Analysis.Analysis.writeMoments(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.writeSensitivityValues(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.writeStats(), and python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.writeSurplusesLevelWise().

writeDataMaple()

def python.tools.writeDataMaple	(		data,
			merge
	)

References sgpp::combigrid.join().

writeDataVectorMaple()

def python.tools.writeDataVectorMaple	(		data,
			filename,
			format = "%s",
			maple_name = "X",
			check = True
	)

References sgpp::combigrid.join(), and python.tools.writeStringToFile().

writeGnuplot()

def python.tools.writeGnuplot	(		filename,
			grid,
			alpha,
			resolution,
			mode = "w",
			data = None,
			fvals = None
	)

References sgpp::op_factory.createOperationEval(), and python.tools.gzOpen().

Referenced by python.classifier.doNormal(), and python.classifier.doTest().

writeGnuplotFctn()

def python.tools.writeGnuplotFctn	(		filename,
			dim,
			fctn,
			resolution,
			mode = "w"
	)

References python.tools.gzOpen().

writeGnuplotGrid()

def python.tools.writeGnuplotGrid	(		filename,
			grid
	)

References analyse_erg.file.

writeGrid()

def python.tools.writeGrid	(		filename,
			grid
	)

References python.tools.gzOpen().

Referenced by python.uq.operations.forcePositivity.estimateDensity.EstimateDensityAlgorithm.computeHierarchicalCoefficients(), python.classifier.doNormal(), python.classifier.doTest(), python.tools.writeCheckpoint(), and python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.writeCheckpoints().

writeLockFile()

def python.tools.writeLockFile	(		filename,
			txt,
			mode = "a"
	)

References python.tools.gzOpen().

Referenced by python.tools.writeStats().

writeNormfile()

def python.tools.writeNormfile	(		filename,
			border,
			minvals,
			maxvals
	)

References sgpp::combigrid.join(), and python.tools.writeStringToFile().

Referenced by python.tools.normalize().

writeStats()

def python.tools.writeStats	(		filename,
			txt,
			mode = "a"
	)

References python.tools.writeLockFile().

Referenced by python.classifier.doTest(), python.classifier.performFold(), python.classifier.performFoldNew(), and python.classifier.performFoldRegression().

writeStringToFile()

def python.tools.writeStringToFile	(		s,
			filename,
			check = True
	)

References python.tools.gzOpen().

Referenced by python.tools.writeDataVectorMaple(), and python.tools.writeNormfile().

Variable Documentation

ARFF

int python.tools.ARFF = 1

base_types

dictionary python.tools.base_types

Initial value:

=  {
    #    "linear" : {"base" : SLinearBase, "b" : SGridOperationB, "t" : test_dataset_linear, "laplace" : SGridOperationLaplace},
    #    "modlinear" : {"base" : SLinearModifiedBase, "b" : SGridModOperationB, "t" : test_dataset_modlin},
    #    "poly" : {"base" : "SPolyBase", },
}

CModes

dictionary python.tools.CModes

Initial value:

=  {
    "laplace": "Classical Laplacian. See OpLaplaceAdaptive",
    "identity": "Identity matrix, most efficient.",
    "identity_no_level1": "Identity matrix, most efficient. But do not penalize Level 1",
    "anisotropicpenalty": "Preferres quadratical supports. See OperationRegularizationDiagonal.",
    "levelsum": "Sum of the levels, scaled by the gridlevel (usually 2 for adaptive SGs).",
    "isotropicpenalty": "Energy-norm-like SGs. See OperationRegularizationDiagonal.",
    "rowsum": "Sum of the rows of classical Laplacian. See OpLaplaceAdaptive",
    "hkmix": "H^k_mix norm; requires parameter Hk",
    "h0hklaplace": "Pseudo-Laplace with H^k in one, and 'H^0' in the remaining dimensions each; requires paramer Hk"}

NOTAFILE

int python.tools.NOTAFILE = -1

SIMPLE

int python.tools.SIMPLE = 0