3.7

TOFTOFConvertTofToDeltaE v1

../_images/TOFTOFConvertTofToDeltaE-v1_dlg.png

TOFTOFConvertTofToDeltaE dialog.

Summary

Converts X-axis units from TOF to energy transfer dE.

Properties

Name Direction Type Default Description
InputWorkspace Input MatrixWorkspace Mandatory Input Sample workspace
EPPTable Input TableWorkspace   Input EPP table (optional). May be produced by FindEPP algorithm.
OutputWorkspace Output Workspace Mandatory Name of the workspace that will contain the result

Description

Warning

This algorithm will be deprecated in the next version of Mantid. Please, use ConvertUnits v1 and ConvertToDistribution v1 instead. To correct time-of-flight considering the fitted elastic peak position, use algorithm CorrectTOF v1.

Converts X-axis units of the given workspace or group of workspaces from time-of-flight to energy transfer. Conversion is performed in a following way. The new X-axis data (\Delta E, meV) are calculated as

\Delta E = \frac{1}{2} C m_n L^2\cdot\left(\frac{1}{t_{el}^2} - \frac{1}{t^2}\right)

where L is the sample-detector distance, m_n is the neutron mass, t_{el} is the time-of-flight corresponding to the elastic peak and t is the time-of-flight from sample to detector.

t=t_0 - t_1

where t_0 is the total TOF corresponding to the bin boundaries of the X data in the input workspace and t_1 is the TOF from source to sample. Coefficient C is related to the unit conversion and calculated as

C = \frac{10^{12}\cdot 10^3}{1.6\cdot 10^{-19}}

where 1.6\cdot 10^{-19} is the coefficient to convert energy from eV to Joule, 10^3 is the coefficient to convert eV to meV and 10^{12} is the coefficient to convert \mu\mathrm{sec}^2 to \mathrm{seconds}^2.

In contrast to the ConvertUnits v1, this algorithm calculates the new Y values I_E(\Delta E) as

I_E (\Delta E) = \frac{t_c^3}{C\cdot m_n\cdot L^2\cdot\Delta t}\cdot I(t)

where t_c is the time-of-flight corresponding to the bin centre in the X data in the input workspace, \Delta t is the time channel width, and I(t) are the Y data in the given input workspace.

This algorithm offers two options for calculation of the elastic peak position t_{el}:

  1. If EPPTable is not given, position of the elastic peak will be taken from the EPP sample log.
  2. If EPPTable is given, position of the elastic peak will be taken from the PeakCentre column.

If position of the elastic peak cannot be determined or t_{el} = 0 for a particular detector, this detector will be masked in the output workspace and warning will be produced.

Restrictions on the input workspaces

  • The unit of the X-axis must be Time-of-flight.

  • Workspace must contain following sample logs: channel_width, EPP, TOF1.

  • Workpace must have an instrument set.

  • If table EPPTable is given:

    1. number of rows of the table must match to the number of histograms of the input workspace.
    2. table must have the PeakCentre column.

Note

The input EPPTable can be produced using the FindEPP v1 algorithm.

Usage

Example 1: Convert using the default option.

import numpy

# create workspace with appropriate sample logs
ws_tof = CreateSampleWorkspace(Function="User Defined", UserDefinedFunction="name=LinearBackground, \
            A0=0.3;name=Gaussian, PeakCentre=8000, Height=5, Sigma=75", NumBanks=2, BankPixelWidth=1,
            XMin=6005.75, XMax=9995.75, BinWidth=10.5, BankDistanceFromSample=4.0, SourceDistanceFromSample=1.4)

lognames="channel_width,EPP,TOF1"
logvalues="10.5,190.0,2123.34"
AddSampleLogMultiple(ws_tof, lognames, logvalues)

ws_dE=TOFTOFConvertTofToDeltaE(ws_tof)

print "Unit of X-axis before conversion: ", ws_tof.getAxis(0).getUnit().unitID()
print "Unit of X-axis after conversion: ",  ws_dE.getAxis(0).getUnit().unitID()
print "First 5 X values before conversion: ", ws_tof.readX(0)[:5]
print "First 5 X values after conversion: ", numpy.round(ws_dE.readX(0)[:5], 2)

Output:

Unit of X-axis before conversion:  TOF
Unit of X-axis after conversion:  DeltaE
First 5 X values before conversion:  [ 6005.75  6016.25  6026.75  6037.25  6047.75]
First 5 X values after conversion:  [-3.13 -3.1  -3.07 -3.04 -3.01]

Example 2: Convert using the elastic peak positions from table

import numpy

# create workspace with appropriate sample logs
ws_tof = CreateSampleWorkspace(Function="User Defined", UserDefinedFunction="name=LinearBackground, \
            A0=0.3;name=Gaussian, PeakCentre=8000, Height=5, Sigma=75", NumBanks=2, BankPixelWidth=1,
            XMin=6005.75, XMax=9995.75, BinWidth=10.5, BankDistanceFromSample=4.0, SourceDistanceFromSample=1.4)

lognames="channel_width,EPP,TOF1"
logvalues="10.5,190.0,2100.34"
AddSampleLogMultiple(ws_tof, lognames, logvalues)

# create a table with elastic peak positions
table=FindEPP(ws_tof)
# run unit conversion
ws_dE=TOFTOFConvertTofToDeltaE(ws_tof, EPPTable=table)

print "Unit of X-axis before conversion: ", ws_tof.getAxis(0).getUnit().unitID()
print "Unit of X-axis after conversion: ",  ws_dE.getAxis(0).getUnit().unitID()
print "First 5 X values before conversion: ", ws_tof.readX(0)[:5]
print "First 5 X values after conversion: ", numpy.round(ws_dE.readX(0)[:5], 2)

Output:

Unit of X-axis before conversion:  TOF
Unit of X-axis after conversion:  DeltaE
First 5 X values before conversion:  [ 6005.75  6016.25  6026.75  6037.25  6047.75]
First 5 X values after conversion:  [-3.08 -3.06 -3.03 -3.   -2.97]

Categories: Algorithms | Workflow\MLZ\TOFTOF | Transforms\Units | CorrectionFunctions