Baseclasses for Targets

Baseclass for all matrices

class diaGrabber.target._matrix.matrixBase(sourceClassList)

Bases: diaGrabber.target._matrixMethods.matrixMethods

Parameters:sourceClassList (tuple, list) – One or more instances of source-classes

Base-Class for all matix-like-targets. Includes every method that is equal for them.

Using more source-classes can be usefull to:

• combine (same merge-dimensions)
• compare (different merge-dimensions)

values. When more sources are used each source has to have the same basis (with same names and units) Different ranges and resolutions will be fitted. If different sources includes mergeDimensions of the same name (and unit) their values are assembled. Depending on the number of used basis- and mergeDimensions all matrix-targets create three different matrices:

• basisMatrix (1D-numpy.array)
• mergeMatrix (nD-numpy.array)
• densityMatrix (nD-numpy.array)

...

_assign(sourceClass, merge_to_matrix)

Assign all self.merge_values to the self.mergeMatrix Get the position/intensity of a value

_buildMatrices()

create:

• mergeMatrix - a list of nD-arrays containing nan (later overridden bymerge-values
• densityMatrix - a list of nD-arrays containing the number of overridden-merge-values
• basisMatrix - a list of 1D-arrays containing th range of all basis-values

_checkMinMax()

get minMax-range for all unlimited dimensions

_combineMergeDims()

_fill(readout_one_line, end_readOut)

Intrinsic method to readout all sources and to fill the matrix.

_fitBasisDims()

_getReadoutEveryNLine()

because every source-file has a identically value for it we can take the first one

_prepareFill()

_setReadoutEveryNLine(readoutEveryNLine)

Try to set the value _readout_every_n_line in every given source-class. If a source-class donst has this attribute, restore the original value.

fill()

Readout the whole source, then continue.

fillInteractive(plotInstance, **kwargs)

Fill the matrix with the source-values and plot the progress. Therefore a plotInstance which is able to plot interactive is needed. kwargs can be those from the plot-method of the used ‘plotInstance’

load(name, folder='', ftype='bin')

Load previous saved matrices. Only ftype=’bin’ is supported at the moment.

save(**kwargs)

Save the following matrices (of all mergeDimensions) to file:

• basisMatrix
• mergeMatrix
• densityMatrix

Required kwargs (“keyword arguments”) are:

Keyword	Type	Example	Description
name	string	“test”	prename of the saved files.

Optional kwargs (“keyword arguments”) are:

Keyword	Type	Default	Description
folder	string	“”	Name of the folder to save in
ftype	string	“bin”	“bin”: output is saved in computer-readable binary-form, “txt”: output is saved in a human-readable-form

Methods to process filled matrices

class diaGrabber.target._matrixMethods.matrixMethods

Bases: object

This class includes a list of methods inherited (and hence callable) by all matrix-like targets.

_multiDimMeshgrid()

like np.meshgrid but can also produce multi-dimensional meshgrids takes list of arrays, where len(list)=nBasis

autoZoom(**kwargs)

Required kwargs (“keyword arguments”) are:

Keyword	Type	Example	Description
mergeName	str	myMergeName	the name of the merge-dim to do the method on
value	float/string	max	The merge-value to zoom in. Type ‘min’ or ‘max’ to use the equivalent extrem-value in the matrix
scale	string	‘relative’ OR ‘absolute’
level	float	0.3	The relative zoom-level 0.3 means +-30% around the zoom-point

Optional kwargs (“keyword arguments”) are:

Keyword	Type	Default	Description
basisNames	list(basisNames)	[{all}]	Which basisDimensions get a new scale.
operator	string	“==”	The zoom-point is defined as the first point in matrix where a value in “==” (equal), “>” (bigger) etc. than the given value

copyMerge(presentMergeName, newMergeName)

copy an existent mergeDim, including its merge- and densityMatrix return the copied mergeDim

interpolateFast(**kwargs)

interpolate NaNs (empty points) in matrix Optional kwargs (“keyword arguments”) are:

Keyword	Type	Default	Description
mergeName	list(mergeDim)	[{all}]	one or more merge-dims to do the method on
method	str	‘nearest’	{“nearest”, “linear”, “cubic”}

interpolateFine(**kwargs)

interpolate NaNs (empty points) in matrix. In contrast to interpolateFast() this function is comparatively slow. Therefore it can take a some minutes to finish interpolation on mergeMatrices that have reslutions > 30 in each basisDimension. However this function enables you to:

• blurring between points (focusExponent). Thus it is possible to get smooth intersections between heavy scattered values.
• extrapolate
• limit the maximum interpolation/extrapolation distance (related to the unit of the chosen basisDimension)
• weight distances in each basisDimension

Optional kwargs (“keyword arguments”) are:

Keyword	Type	Default	Description
mergeName	list(mergeDim)	[{all}]	one or more merge-dims to do the method on
focusExponent	float	10	xxxxx
evalPointDensity	bool	True	xxxxxxxx
maxDistance	dict	{None}	{basisName:maxDistance,..}
distanceFactor	dict	{1}	{basisName:factor,..}

\[moment = 1/distance^{focusExponent}\]

posterize(**kwargs)

This method discretize/posterize the values in the mergeMatrix (of a given mergeDimension) to a given ammount of values (e.g. nValues= 4 ) or to a given list or values (e.g. values = [1,2,4])

Optional kwargs (“keyword arguments”) are:

Keyword	Type	Default	Description
mergeName	list(mergeNames)	[{all}]	one or more merge-dims to do the method on
nValues	int	5	the ammount of different values
values	list	None	given different values

transformDim(**kwargs)

Keyword	Type	Default	Description
mergeName	list(mergeDim)	[{all}]	one or more merge-dims to do the method on
rebuildMatrix	bool	False	xxxxxxxxxx

transformMatrixToPoints(givenMultiDimMeshgrid=None, mergeIndex=0)

transform all not-empty parts of a matrix to discrete points

transformPointsToMatrix(points, merge, mergeIndex=0)