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BivariateNormal¶
Description¶
Provides a peak shape function interface for a peak on one time slice of a Rectangular detector.
The Normal(..) is the Normal probability density function. Its integral over all x(col) and y(row) values is one. This means that Intensity is the total intensity with background removed.
Attributes (nonfitting parameters)¶
Name 
Type 
Default 
Description 

CalcVariances 
There is only one Attribute: CalcVariances. This attribute is boolean.
If true, the variances are calculated from the data, given the means, variances and covariance. Otherwise they will become parameters and fit.
CalcVariances = true gives better/more stable results for peaks interior to the Rectangular Detector. For peaks close to the edge, CalcVariances should be false.
Properties (fitting parameters)¶
Name 
Default 
Description 

Background 
0.0 

Intensity 
0.0 

Mcol 
0.0 
Mean column(x) value 
Mrow 
0.0 
Mean row(y) value 
Background  The background of the peak
Intensity  The intensity of data for the peak on this time slice
Mcol  The col(x) of the center of the peak
Mrow  The row(y) of the center of the peak on this slice
—— If CalcVariances is false, the following 3 parameters are also fit———
SScol The variance of the column(x) values in the peak for this time slice
SSrow  The variance of the row(y) values in the peak for this time slice
SSrc  The covariance of the row(x) and column(y) values in the peak for this time slice
Usage¶
The workspace can be “any” MatrixWorkspace where
dataY(1) is the column(x) values for the pixels to be considered
dataY(2) is the row(y) values for the pixels to be considered
dataY(0)is the experimental data at the corresponding row and column for a panel and time slice( or merged time slices or…)
The data can have missing row and column values and need not represent a square or contiguous subregion of a panel
The values for out in function1D are, for each pixel, the difference of V(see formula) and dataY(0).
Categories: FitFunctions  Peak
Source¶
C++ header: BivariateNormal.h
C++ source: BivariateNormal.cpp