python.toolsExtended Namespace Reference

Functions
	buildAlphaVector (filename)
	Wrapper for buildCoefficientVectorFromFile.
	buildCoefficientVectorFromFile (filename)
	Builds the data vector that hold the coefficients fo either the ansatzfuctions or the node base re.sub(regex, replacement, subject)
	buildNodevalueVector (filename)
	Wrapper for buildCoefficientVectorFromFile.
	buildTrainingVector (data)
	Builds the training data vector.
	compareBBTMatrices (m1, m2)
	Compares, if two BBT matrices are "almost" equal.
	compareBTMatrices (m1, m2)
	Compares, if two BT matrices are "almost" equal.
	compareResultFiles (file1, file2)
	Compares two files and calculates the maximum difference between the values.
	doDehierarchisation (alpha, grid)
	hierarchisation of the node base values on a grid
	doHierarchisation (node_values, grid)
	hierarchisation of the node base values on a grid
	evalFunction (function, points)
	evalutes a given function
	generateBBTMatrix (factory, training, verbose=False)
	Generates the BBT DM Matrix for a given grid using numpy.
	generateBBTMatrixPython (factory, training, verbose=False)
	Generates the BBT DM Matrix for a given grid only using python arrays.
	generateBTMatrix (factory, training, verbose=False)
	Generates the BT DM Matrix for a given grid using numpy.
	generateBTMatrixPython (factory, training, verbose=False)
	Generates the BT DM Matrix for a given grid only using python arrays.
	generateCMatrix (factory, verbose=False)
	Generates the Laplace Matrix for a given grid using numpy.
	openFile (filename)
	Opens a file and returns the stored data.
	printNDFunction (filename, filenameValue, grid, alpha, resolution)
	This allows to evaluate a multidimensional function.
	printPoint (p, grid, alpha, fout, foutvalue)
	Here a evaluate point on a Sparse Grid is written to a file.
	printRefNDFunction (filename, filenameValue, function, resolution, dim)
	This allows to evaluate a multidimensional function.
	printRefPoint (points, dim, function, fout, foutvalue)
	Writes reference points to a given file.
	readDataVector (filename)
	Reads a DataVector.
	readReferenceMatrix (storage, filename)
	Reads a Reference matrix and returns it.
	recGenPrintRefVector (dim_rem, dim, points, function, resolution, fout, foutvalue)
	Recursive generation of the function's coordinate string.
	recGenPrintVector (dim_rem, p, grid, alpha, resolution, fout, foutvalue)
	Evaluates a mutlidimensional function on a Sparse Grid.
	testHierarchisationResults (node1, node2)
	tests the correctness of the hierarchisation and dehierachisation
	writeMatrixToFile (filename, matrix, n, m)
	Writes matrix stored in numpy format into a file.

Function Documentation

buildAlphaVector()

python.toolsExtended.buildAlphaVector

(

filename

)

Wrapper for buildCoefficientVectorFromFile.

Parameters

filename

name of the ARFF file that contains the ansatzfunction coefficients

Returns

a instance of a DataVector that stores ansatzfunction coefficients

References python.toolsExtended.buildCoefficientVectorFromFile().

buildCoefficientVectorFromFile()

python.toolsExtended.buildCoefficientVectorFromFile

(

filename

)

Builds the data vector that hold the coefficients fo either the ansatzfuctions or the node base re.sub(regex, replacement, subject)

Parameters

filename

name of the ARFF file that contains the coefficients

Returns

a instance of a DataVector that stores coefficients

Referenced by python.toolsExtended.buildAlphaVector(), and python.toolsExtended.buildNodevalueVector().

buildNodevalueVector()

python.toolsExtended.buildNodevalueVector

(

filename

)

Wrapper for buildCoefficientVectorFromFile.

Parameters

filename

name of the ARFF file that contains the node base coefficients

Returns

a instance of a DataVector that stores node base coefficients

References python.toolsExtended.buildCoefficientVectorFromFile().

buildTrainingVector()

python.toolsExtended.buildTrainingVector

(

data

)

Builds the training data vector.

Parameters

data	a list of lists that contains the points a the training data set, coordinate-wise

Returns

a instance of a DataVector that stores the training data

compareBBTMatrices()

python.toolsExtended.compareBBTMatrices	(		m1,
			m2
	)

Compares, if two BBT matrices are "almost" equal.

Has to handle the problem that the underlying grid was ordered differently. Uses heuristics, e.g. whether the diagonal elements and row and column sums match. and prints the result for each element

Parameters

m1	the first matrix
m2	the second matrix

compareBTMatrices()

python.toolsExtended.compareBTMatrices	(		m1,
			m2
	)

Compares, if two BT matrices are "almost" equal.

Has to handle the problem that the underlying grid was ordered differently. Uses heuristics, e.g. whether the row and column sums match. and prints the result for each element

Parameters

m1	the first matrix
m2	the second matrix

compareResultFiles()

python.toolsExtended.compareResultFiles	(		file1,
			file2
	)

Compares two files and calculates the maximum difference between the values.

Parameters

file1	the first file
file2	the second file

Returns

the maximum detected difference between two components

doDehierarchisation()

python.toolsExtended.doDehierarchisation	(		alpha,
			grid
	)

hierarchisation of the node base values on a grid

Parameters

alpha	DataVector that holds the coefficients of the sparse grid's ansatzfunctions
grid	thee grid matching to the alpha vector

doHierarchisation()

python.toolsExtended.doHierarchisation	(		node_values,
			grid
	)

hierarchisation of the node base values on a grid

Parameters

node_values	DataVector that holds the coefficients of the function's node base
grid	the grid matching to the node_vector

evalFunction()

python.toolsExtended.evalFunction	(		function,
			points
	)

evalutes a given function

Parameters

function	a string the gives the function; x1...xn must be the names of the placeholders
points	sorted list of the coordinates (x1...xn) of evaluation point

Returns

returns the function value at points

Referenced by python.toolsExtended.printRefPoint().

generateBBTMatrix()

python.toolsExtended.generateBBTMatrix	(		factory,
			training,
			verbose = False
	)

Generates the BBT DM Matrix for a given grid using numpy.

Parameters

factory	the grid object
training	DataVector to contains the used training data
verbose	default:False prints some additional information

generateBBTMatrixPython()

python.toolsExtended.generateBBTMatrixPython	(		factory,
			training,
			verbose = False
	)

Generates the BBT DM Matrix for a given grid only using python arrays.

Parameters

factory	the grid object
training	DataVector to contains the used training data
verbose	default:False prints some additional information

generateBTMatrix()

python.toolsExtended.generateBTMatrix	(		factory,
			training,
			verbose = False
	)

Generates the BT DM Matrix for a given grid using numpy.

Parameters

factory	the grid object
training	DataVector to contains the used training data
verbose	default:False prints some additional information

generateBTMatrixPython()

python.toolsExtended.generateBTMatrixPython	(		factory,
			training,
			verbose = False
	)

Generates the BT DM Matrix for a given grid only using python arrays.

Parameters

factory	the grid object
training	DataVector to contains the used training data
verbose	default:False prints some additional information

generateCMatrix()

python.toolsExtended.generateCMatrix	(		factory,
			verbose = False
	)

Generates the Laplace Matrix for a given grid using numpy.

Parameters

factory	the grid object
verbose	default:False prints some additional information

openFile()

python.toolsExtended.openFile

(

filename

)

Opens a file and returns the stored data.

Parameters

filename

of file to open

Returns

the data stored in the file

printNDFunction()

python.toolsExtended.printNDFunction	(		filename,
			filenameValue,
			grid,
			alpha,
			resolution
	)

This allows to evaluate a multidimensional function.

Parameters

filename	filename of file with coordinates and function values
filenameValue	filename of file with function values only
grid	reference to the Sparse Grid
alpha	hierarchical surplus of the Sparse Grid's Ansatzfunctions
resolution	number of evaluating points

References python.toolsExtended.recGenPrintVector().

printPoint()

python.toolsExtended.printPoint	(		p,
			grid,
			alpha,
			fout,
			foutvalue
	)

Here a evaluate point on a Sparse Grid is written to a file.

Parameters

p	DataVector containing the coordinates of the point
grid	reference to the Sparse Grid
alpha	hierarchical surplus of the Sparse Grid's Ansatzfunctions
fout	filehandle to result file, containing the coordinates and value
foutvalue	filehandle to resultfile, containing only the value

Referenced by python.toolsExtended.recGenPrintVector().

printRefNDFunction()

python.toolsExtended.printRefNDFunction	(		filename,
			filenameValue,
			function,
			resolution,
			dim
	)

This allows to evaluate a multidimensional function.

Parameters

filename	filename of file with coordinates and function values
filenameValue	filename of file with function values only
function	string that describes the function to evaluate
resolution	number of evaluating points
dim	dimension of function

References python.toolsExtended.recGenPrintRefVector().

printRefPoint()

python.toolsExtended.printRefPoint	(		points,
			dim,
			function,
			fout,
			foutvalue
	)

Writes reference points to a given file.

Parameters

points	string containing the evaluation potins
dim	the dimension of the function
function	string that describes the function to evaluate
fout	filehandle to result file, containing the coordinates and value
foutvalue	filehandle to resultfile, containing only the value

References python.toolsExtended.evalFunction().

Referenced by python.toolsExtended.recGenPrintRefVector().

readDataVector()

python.toolsExtended.readDataVector

(

filename

)

Reads a DataVector.

Parameters

filename

the filename of the file that contains the data

Returns

returns a data Vector

readReferenceMatrix()

python.toolsExtended.readReferenceMatrix	(		storage,
			filename
	)

Reads a Reference matrix and returns it.

Parameters

storage	storage of the grid
filename	the filename of the file that contains the reference data

Returns

returns a python array with the reference matrix

References python.tools.gzOpen().

recGenPrintRefVector()

python.toolsExtended.recGenPrintRefVector	(		dim_rem,
			dim,
			points,
			function,
			resolution,
			fout,
			foutvalue
	)

Recursive generation of the function's coordinate string.

Parameters

dim_rem	remaining dimensions
dim	dimension of function
points	current coordinate string
function	string that describes the function to evaluate
resolution	number of supporting points
fout	filehandle to result file, containing the coordinates and value
foutvalue	filehandle to resultfile, containing only the value

References python.toolsExtended.printRefPoint(), and python.toolsExtended.recGenPrintRefVector().

Referenced by python.toolsExtended.printRefNDFunction(), and python.toolsExtended.recGenPrintRefVector().

recGenPrintVector()

python.toolsExtended.recGenPrintVector	(		dim_rem,
			p,
			grid,
			alpha,
			resolution,
			fout,
			foutvalue
	)

Evaluates a mutlidimensional function on a Sparse Grid.

Parameters

dim_rem	remaining dimensions
p	DataVector containing the coordinates of the point
grid	reference to the Sparse Grid
alpha	hierarchical surplus of the Sparse Grid's Ansatzfunctions
resolution	number of evaluating points
fout	filehandle to result file, containing the coordinates and value
foutvalue	filehandle to resultfile, containing only the value

References python.toolsExtended.printPoint(), and python.toolsExtended.recGenPrintVector().

Referenced by python.toolsExtended.printNDFunction(), and python.toolsExtended.recGenPrintVector().

testHierarchisationResults()

python.toolsExtended.testHierarchisationResults	(		node1,
			node2
	)

tests the correctness of the hierarchisation and dehierachisation

Parameters

node1	the vector of the node base values before hierarchisation and dehierarchisation
node2	the vector of the node base values after hierarchisation and dehierarchisation

Returns

maximum error during the transformations

writeMatrixToFile()

python.toolsExtended.writeMatrixToFile	(		filename,
			matrix,
			n,
			m
	)

Writes matrix stored in numpy format into a file.

Parameters

filename	file's filename to which the data is written
matrix	the matrix that should be stored
n	number of rows
m	number of columns