LoadDNSSCD v1

../_images/LoadDNSSCD-v1_dlg.png

LoadDNSSCD dialog.

Summary

Load a list of DNS .d_dat files into a MDEventWorkspace.

Properties

Name Direction Type Default Description
Filenames Input list of str lists Mandatory Select one or more DNS SCD .d_dat files to load.Files must be measured at the same conditions. Allowed extensions: [‘.d_dat’]
OutputWorkspace Output MDEventWorkspace Mandatory An output MDEventWorkspace.
NormalizationWorkspace Output MDEventWorkspace Mandatory An output normalization MDEventWorkspace.
Normalization Input string monitor Algorithm will create a separate normalization workspace. Choose whether it should contain monitor counts or time. Allowed values: [‘monitor’, ‘time’]
a Input number 1 Lattice parameter a in Angstrom
b Input number 1 Lattice parameter b in Angstrom
c Input number 1 Lattice parameter c in Angstrom
alpha Input number 90 Angle between b and c in degrees
beta Input number 90 Angle between a and c in degrees
gamma Input number 90 Angle between a and b in degrees
OmegaOffset Input number 0 Angle in degrees between (HKL1) and the beam axisif the goniometer is at zero.
HKL1 Input dbl list 1,1,0 Indices of the vector in reciprocal space in the horizontal plane at angle Omegaoffset, if the goniometer is at zero.
HKL2 Input dbl list 0,0,1 Indices of a second vector in reciprocal space in the horizontal plane not parallel to HKL1
TwoThetaLimits Input dbl list 0,180 Range (min, max) of scattering angles (2theta, in degrees) to consider. Everything out of this range will be cut.
LoadHuberFrom Input TableWorkspace   A table workspace to load a list of raw sample rotation angles. Huber angles given in the data files will be ignored.
SaveHuberTo Output TableWorkspace   A workspace name to save a list of raw sample rotation angles.
ElasticChannel Input number 0 Elastic channel number. Only for TOF data.
DeltaEmin Input number -10 Minimal energy transfer to consider. Should be <=0. Only for TOF data.

Description

Warning

This algorithm does not perform any consistency check of the input data. It is the users responsibility to choose a physically reasonable dataset.

This algorithm loads a list of DNS .d_dat data files into a MDEventWorkspace. If the algorithm fails to process a file, this file will be ignored. In this case the algorithm produces a warning and continues to process further files. Only if no valid files are provided, the algorithm terminates with an error message.

This algorithm is meant to replace the LoadDNSLegacy v1 for single crystal diffraction data.

Output

As a result, two workspaces are created:

  • OutputWorkspace contains the raw neutron counts.
  • NormalizationWorkspace contains the chosen normalization data (either monitor counts or experiment duration time).

Both workspaces have (H,K,L,dE) dimensions. The metadata are loaded into time series sample logs.

Note

For the further data reduction BinMD v1 should be used to bin the data.

Restrictions

  • This algorithm only supports the DNS instrument in its configuration with one detector bank (polarisation analysis).
  • This algorithm does not allow to merge datasets with different number of TOF channels.

Data replication

For standard data (vanadium, NiCr, background) the sample rotation angle is assumed to be not important. These data are typically measured only for one sample rotation angle. The algorithm can replicate these data for the same sample rotation angles as a single crystal sample has been measured. For this purpose optional input fields SaveHuberTo and LoadHuberFrom can be used.

  • SaveHuberTo should contain a name of the TableWorkspace where sample rotation angles (Huber) read from the data files will be saved. If the specified workspace exists, it will be overwritten.
  • LoadHuberFrom should contain a name of the TableWorkspace. The workspace must exist and contain one column with the name Huber(degrees), where the sample rotation angles are specified.

Note

If LoadHuberFrom option is applied, sample rotation angles in the data files will be ignored. Only sample rotation angles from the table will be considered.

Usage

Example 1 - Load a DNS .d_dat file to MDEventWorkspace:

# data file.
filename = "dn134011vana.d_dat"

# lattice parameters
a = 5.0855
b = 5.0855
c = 14.0191
omega_offset = 225.0
hkl1="1,0,0"
hkl2="0,0,1"
alpha=90.0
beta=90.0
gamma=120.0

# load data to MDEventWorkspace
ws, ws_norm, huber_ws = LoadDNSSCD(FileNames=filename, NormalizationWorkspace='ws_norm',
                                   Normalization='monitor', a=a, b=b, c=c, alpha=alpha, beta=beta, gamma=gamma,
                                   OmegaOffset=omega_offset, HKL1=hkl1, HKL2=hkl2, SaveHuberTo='huber_ws')

# print output workspace information
print("Output Workspace Type is:  {}".format(ws.id()))
print("It has {0} events and {1} dimensions:".format(ws.getNEvents(), ws.getNumDims()))
for i in range(ws.getNumDims()):
    dimension = ws.getDimension(i)
    print("Dimension {0} has name: {1}, id: {2}, Range: {3:.2f} to {4:.2f} {5}".format(i,
          dimension.getDimensionId(),
          dimension.name,
          dimension.getMinimum(),
          dimension.getMaximum(),
          dimension.getUnits()))

# print information about the table workspace
print ("TableWorkspace '{0}' has {1} row in the column '{2}'.".format(huber_ws.name(),
                                                                      huber_ws.rowCount(),
                                                                      huber_ws.getColumnNames()[0]))
print("It contains sample rotation angle {} degrees".format(huber_ws.cell(0, 0)))

Output:

Output Workspace Type is:  MDEventWorkspace<MDEvent,4>
It has 24 events and 4 dimensions:
Dimension 0 has name: H, id: H, Range: -15.22 to 15.22 r.l.u
Dimension 1 has name: K, id: K, Range: -15.22 to 15.22 r.l.u
Dimension 2 has name: L, id: L, Range: -41.95 to 41.95 r.l.u
Dimension 3 has name: DeltaE, id: DeltaE, Range: -10.00 to 4.64 r.l.u
TableWorkspace 'huber_ws' has 1 row in the column 'Huber(degrees)'.
It contains sample rotation angle 79.0 degrees

Example 2 - Specify scattering angle limits:

# data file.
filename = "dn134011vana.d_dat"

# lattice parameters
a = 5.0855
b = 5.0855
c = 14.0191
omega_offset = 225.0
hkl1="1,0,0"
hkl2="0,0,1"
alpha=90.0
beta=90.0
gamma=120.0

# scattering angle limits, degrees
tth_limits = "20,70"

# load data to MDEventWorkspace
ws, ws_norm, huber_ws = LoadDNSSCD(FileNames=filename, NormalizationWorkspace='ws_norm',
                                   Normalization='monitor', a=a, b=b, c=c, alpha=alpha, beta=beta, gamma=gamma,
                                   OmegaOffset=omega_offset, HKL1=hkl1, HKL2=hkl2, TwoThetaLimits=tth_limits)

# print output workspace information
print("Output Workspace Type is:  {}".format(ws.id()))
print("It has {0} events and {1} dimensions.".format(ws.getNEvents(), ws.getNumDims()))

# print normalization workspace information
print("Normalization Workspace Type is:  {}".format(ws_norm.id()))
print("It has {0} events and {1} dimensions.".format(ws_norm.getNEvents(), ws_norm.getNumDims()))

Output:

Output Workspace Type is:  MDEventWorkspace<MDEvent,4>
It has 10 events and 4 dimensions.
Normalization Workspace Type is:  MDEventWorkspace<MDEvent,4>
It has 10 events and 4 dimensions.

Example 3 - Load sample rotation angles from the table

# data file.
filename = "dn134011vana.d_dat"

# construct table workspace with 10 raw sample rotation angles from 70 to 170 degrees
table = CreateEmptyTableWorkspace()
table.addColumn( "double", "Huber(degrees)")
for huber in range(70, 170, 10):
    table.addRow([huber])

# lattice parameters
a = 5.0855
b = 5.0855
c = 14.0191
omega_offset = 225.0
hkl1="1,0,0"
hkl2="0,0,1"
alpha=90.0
beta=90.0
gamma=120.0

# load data to MDEventWorkspace
ws, ws_norm, huber_ws = LoadDNSSCD(FileNames=filename, NormalizationWorkspace='ws_norm',
                                   Normalization='monitor', a=a, b=b, c=c, alpha=alpha, beta=beta, gamma=gamma,
                                   OmegaOffset=omega_offset, HKL1=hkl1, HKL2=hkl2, LoadHuberFrom=table)

# print output workspace information
print("Output Workspace Type is:  {}".format(ws.id()))
print("It has {0} events and {1} dimensions.".format(ws.getNEvents(), ws.getNumDims()))

# setting for the BinMD algorithm
bvec0 = '[100],unit,1,0,0,0'
bvec1 = '[001],unit,0,0,1,0'
bvec2 = '[010],unit,0,1,0,0'
bvec3 = 'dE,meV,0,0,0,1'
extents = '-2,1.5,-0.2,6.1,-10,10,-10,4.6'
bins = '10,10,1,1'
# bin the data
data_raw = BinMD(ws, AxisAligned='0', BasisVector0=bvec0, BasisVector1=bvec1, BasisVector2=bvec2,
                 BasisVector3=bvec3, OutputExtents=extents, OutputBins=bins, NormalizeBasisVectors='0')
# bin normalization
data_norm = BinMD(ws_norm, AxisAligned='0', BasisVector0=bvec0, BasisVector1=bvec1, BasisVector2=bvec2,
                  BasisVector3=bvec3, OutputExtents=extents, OutputBins=bins, NormalizeBasisVectors='0')
# normalize data
data = data_raw/data_norm

# print reduced workspace information
print("Reduced Workspace Type is:  {}".format(data.id()))
print("It has {} dimensions.".format(data.getNumDims()))
s =  data.getSignalArray()
print("Signal at some points: {0:.4f}, {1:.4f}, {2:.4f}".format(
      float(s[7,1][0]), float(s[7,2][0]), float(s[7,3][0])))

Output:

Output Workspace Type is:  MDEventWorkspace<MDEvent,4>
It has 240 events and 4 dimensions.
Reduced Workspace Type is:  MDHistoWorkspace
It has 4 dimensions.
Signal at some points: 0.0035, 0.0033, 0.0035

Categories: Algorithm Index | MDAlgorithms\DataHandling

Source

C++ source: LoadDNSSCD.cpp (last modified: 2018-12-14)

C++ header: LoadDNSSCD.h (last modified: 2018-10-05)