python.datasetAnalysis Namespace Reference

Variables
	action
	args
dictionary	class_count = {}
	class_values = list(class_count.keys())
	dataset = readDataARFF(filename)
	dest
	dim = len(dataset["data"])
	ftype = isARFFFile(filename)
	help
	mean = total_sum / numpoints
	numpoints = len(dataset["data"][0])
	options
	parser = OptionParser()
	sample_stddev = math.sqrt(unbiased_variance)
	total_sum = sum(dataset["data"][i])
	type
	unbiased_variance = sum([(x-mean)**2 for x in dataset["data"][i]]) / (numpoints-1)

Variable Documentation

action

python.datasetAnalysis.action

args

python.datasetAnalysis.args

class_count

dictionary python.datasetAnalysis.class_count = {}

class_values

python.datasetAnalysis.class_values = list(class_count.keys())

dataset

python.datasetAnalysis.dataset = readDataARFF(filename)

dest

python.datasetAnalysis.dest

dim

python.datasetAnalysis.dim = len(dataset["data"])

ftype

python.datasetAnalysis.ftype = isARFFFile(filename)

Referenced by sgpp::base::GridDataBase.GridDataBase(), and sgpp::base::GridDataBase.load().

help

python.datasetAnalysis.help

mean

python.datasetAnalysis.mean = total_sum / numpoints

Referenced by python.uq.analysis.mc.MCAnalysis.MCAnalysis.computeMean(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.computeMean(), sgpp::base::OperationFirstMomentLinearBoundary.doQuadrature(), sgpp::combigrid::FullGridVarianceSummationStrategy< V >.eval(), sgpp::base::StdNormalDistribution.getDensity(), sgpp::base::GaussHermiteQuadRule1D.getLevelPointsAndWeightsNormalized(), sgpp::datadriven::AlgorithmAdaBoostBase.getMeanGridPoint(), sgpp::base::StdNormalDistribution.getNormedDensity(), python.uq.analysis.asgc.anova.hdmrAnalytic.HDMRAnalytic.getSortedPermutations(), python.uq.analysis.asgc.anova.hdmrAnalytic.HDMRAnalytic.getVarianceDecomposition(), python.utils.pca_normalize_dataset.remove_outliers(), and python.uq.analysis.asgc.anova.hdmrAnalytic.HDMRAnalytic.setVerbose().

numpoints

python.datasetAnalysis.numpoints = len(dataset["data"][0])

options

python.datasetAnalysis.options

parser

python.datasetAnalysis.parser = OptionParser()

sample_stddev

python.datasetAnalysis.sample_stddev = math.sqrt(unbiased_variance)

total_sum

python.datasetAnalysis.total_sum = sum(dataset["data"][i])

type

python.datasetAnalysis.type

unbiased_variance

python.datasetAnalysis.unbiased_variance = sum([(x-mean)**2 for x in dataset["data"][i]]) / (numpoints-1)