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.. properties::
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 <http://www.mantidproject.org/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 :ref:`algm-LoadDNSLegacy` for single crystal diffraction data.
.. seealso:: :ref:`LoadDNSLegacy <algm-LoadDNSLegacy>`, :ref:`LoadWANDSCD <algm-LoadWANDSCD>` and :ref:`ConvertWANDSCDtoQ <algm-ConvertWANDSCDtoQ>`.
**Output**
As a result, two workspaces are created:
- `OutputWorkspace` contains the raw neutron counts.
- `NormalizationWorkspace` contains the choosen normalization data (either monitor counts or experiment duration time).
Both workspaces have :math:`(H,K,L,dE)` dimensions. The metadata are loaded into time series sample logs.
.. note::
For the further data reduction :ref:`algm-BinMD` 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 <http://www.mantidproject.org/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 <http://www.mantidproject.org/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:**
.. testcode:: LoadDNSSCDEx1
# 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:**
.. testoutput:: LoadDNSSCDEx1
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
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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:**
.. testcode:: LoadDNSSCDEx2
# 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:**
.. testoutput:: LoadDNSSCDEx2
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.
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**Example 3 - Load sample rotation angles from the table**
.. testcode:: LoadDNSSCDEx3
# 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'
data_raw = BinMD(ws, AxisAligned='0', BasisVector0=bvec0, BasisVector1=bvec1, BasisVector2=bvec2,
BasisVector3=bvec3, OutputExtents=extents, OutputBins=bins, NormalizeBasisVectors='0')
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:**
.. testoutput:: LoadDNSSCDEx3
Output Workspace Type is: MDEventWorkspace<MDEvent,4>
It has 240 events and 4 dimensions.
Reduced Workspace Type is: MDHistoWorkspace
Signal at some points: 0.0035, 0.0033, 0.0035
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