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PolynomialCorrection v1

../_images/PolynomialCorrection-v1_dlg.png

PolynomialCorrection dialog.

Summary

Corrects the data in a workspace by the value of a polynomial function which is evaluated at the X value of each data point.

See Also

OneMinusExponentialCor, MagFormFactorCorrection, ExponentialCorrection, PowerLawCorrection

Properties

Name

Direction

Type

Default

Description

InputWorkspace

Input

MatrixWorkspace

Mandatory

The name of the input workspace

OutputWorkspace

Output

MatrixWorkspace

Mandatory

The name to use for the output workspace (can be the same as the input one).

Coefficients

Input

dbl list

Mandatory

Array Property containing the coefficients of the polynomial correction function in ascending powers of X. Can be given as a comma separated list in string form.

Operation

Input

string

Multiply

The operation with which the correction is applied to the data (default: Multiply). Allowed values: [‘Multiply’, ‘Divide’]

Description

Corrects the data and error values on a workspace by the value of a polynomial function using the chosen operation. The correction factor is defined by

\[C = \sum_{i}^{N} c_i x_i\]

where N is the order of the polynomial specified by the length of the Coefficients property. The factor is evaluated at the x value of each data point (using the mid-point of the bin as the x value for histogram data.

Usage

Example: divide data by a quadratic:

# create histogram workspace
dataX = [0,1,2,3,4,5,6,7,8,9] # or use dataX=range(0,10)
dataY = [1,2,3,4,5,6,7,8,9]
dataE = [1,2,3,4,5,6,7,8,9]
data_ws = CreateWorkspace(dataX, dataY, DataE=dataE)

coefficients = [1., 3., 5.] #  1 + 3x + 5x^2
data_ws = PolynomialCorrection(data_ws, coefficients, Operation="Divide")

print("First 5 y values: {}".format(data_ws.readY(0)[0:5]))
print("First 5 error values: {}".format(data_ws.readE(0)[0:5]))

First 5 y values: [ 0.26666667  0.11940299  0.0754717   0.05498282  0.04319654]
First 5 error values: [ 0.26666667  0.11940299  0.0754717   0.05498282  0.04319654]

Example: multiply data by a linear:

# create histogram workspace
dataX = [0,1,2,3,4,5,6,7,8,9] # or use dataX=range(0,10)
dataY = [1,2,3,4,5,6,7,8,9]
dataE = [1,2,3,4,5,6,7,8,9]
data_ws = CreateWorkspace(dataX, dataY, DataE=dataE)

coefficients = [2., 4.] #  2 + 4x
data_ws = PolynomialCorrection(data_ws, coefficients, Operation="Multiply")

print("First 5 y values: {}".format(data_ws.readY(0)[0:5]))
print("First 5 error values: {}".format(data_ws.readE(0)[0:5]))

First 5 y values: [   4.   16.   36.   64.  100.]
First 5 error values: [   4.   16.   36.   64.  100.]

Categories: AlgorithmIndex | CorrectionFunctions

Source

C++ header: PolynomialCorrection.h

C++ source: PolynomialCorrection.cpp