def setUpClass(self):
self.ws_MD_3D = CreateMDHistoWorkspace(
Dimensionality=3,
Extents='-3,3,-10,10,-1,1',
SignalInput=range(100),
ErrorInput=range(100),
NumberOfBins='5,5,4',
Names='Dim1,Dim2,Dim3',
Units='MomentumTransfer,EnergyTransfer,Angstrom',
OutputWorkspace='ws_MD_3D')
self.ws_MDE_3D = CreateMDWorkspace(Dimensions='3',
Extents='-3,3,-4,4,-5,5',
Names='h,k,l',
Units='rlu,rlu,rlu',
SplitInto='4',
OutputWorkspace='ws_MDE_3D')
FakeMDEventData('ws_MDE_3D',
PeakParams='100000,0,0,0,0.1',
RandomSeed='63759',
RandomizeSignal='1')
FakeMDEventData('ws_MDE_3D',
PeakParams='40000,1,0,0,0.1',
RandomSeed='63759',
RandomizeSignal='1')
self.ws2d_histo = CreateWorkspace(DataX=[10, 20, 30, 10, 20, 30],
DataY=[2, 3, 4, 5],
DataE=[1, 2, 3, 4],
NSpec=2,
Distribution=True,
UnitX='Wavelength',
VerticalAxisUnit='DeltaE',
VerticalAxisValues=[4, 6, 8],
OutputWorkspace='ws2d_histo')
def setUpClass(cls):
"""
Create fake workspaces, 3D and 2D
"""
# 3D
DeltaPDF3DTest_MDE = CreateMDWorkspace(Dimensions='3', Extents='-3.1,3.1,-3.1,3.1,-3.1,3.1', Names='[H,0,0],[0,K,0],[0,0,L]',
Units='rlu,rlu,rlu', SplitInto='4',Frames='HKL,HKL,HKL')
# Add Bragg peaks
for h in range(-3,4):
for k in range(-3,4):
for l in range(-3,4):
FakeMDEventData(DeltaPDF3DTest_MDE, PeakParams='100,'+str(h)+','+str(k)+','+str(l)+',0.1', RandomSeed='1337')
# Add addiontal peaks on [0.5,0.5,0.5] type positions
# This would correspond to negative substitutional correlations
for h in np.arange(-2.5,3):
for k in np.arange(-2.5,3):
for l in np.arange(-2.5,3):
FakeMDEventData(DeltaPDF3DTest_MDE, PeakParams='20,'+str(h)+','+str(k)+','+str(l)+',0.1', RandomSeed='13337')
BinMD(InputWorkspace='DeltaPDF3DTest_MDE', AlignedDim0='[H,0,0],-3.05,3.05,61', AlignedDim1='[0,K,0],-3.05,3.05,61',
AlignedDim2='[0,0,L],-3.05,3.05,61', OutputWorkspace='DeltaPDF3DTest_MDH')
# 2D
DeltaPDF3DTest_MDE_2 = CreateMDWorkspace(Dimensions='3', Extents='-3.1,3.1,-3.1,3.1,-0.1,0.1', Names='[H,0,0],[0,K,0],[0,0,L]',
Units='rlu,rlu,rlu', SplitInto='4',Frames='HKL,HKL,HKL')
# Add Bragg peaks
for h in range(-3,4):
for k in range(-3,4):
FakeMDEventData(DeltaPDF3DTest_MDE_2, PeakParams='100,'+str(h)+','+str(k)+',0,0.01', RandomSeed='1337')
# Add addiontal peaks on [0.5,0.5,0.5] type positions
# This would correspond to negative substitutional correlations
for h in np.arange(-2.5,3):
for k in np.arange(-2.5,3):
FakeMDEventData(DeltaPDF3DTest_MDE_2, PeakParams='20,'+str(h)+','+str(k)+',0,0.1', RandomSeed='13337')
BinMD(InputWorkspace='DeltaPDF3DTest_MDE_2', AlignedDim0='[H,0,0],-3.05,3.05,61', AlignedDim1='[0,K,0],-3.05,3.05,61',
AlignedDim2='[0,0,L],-0.1,0.1,1', OutputWorkspace='DeltaPDF3DTest_MDH_2')
def test_mdhisto_workspace_q(self):
from mantid.simpleapi import (CreateMDWorkspace, FakeMDEventData,
BinMD)
md_event = CreateMDWorkspace(Dimensions=3,
Extents=[-10, 10, -10, 10, -10, 10],
Names='Q_x,Q_y,Q_z',
Units='U,U,U',
Frames='QLab,QLab,QLab',
StoreInADS=False)
FakeMDEventData(InputWorkspace=md_event,
PeakParams=[100000, 0, 0, 0, 1],
StoreInADS=False) # Add Peak
md_histo = BinMD(InputWorkspace=md_event,
AlignedDim0='Q_y,-10,10,3',
AlignedDim1='Q_x,-10,10,4',
AlignedDim2='Q_z,-10,10,5',
StoreInADS=False)
histo_data_array = mantidcompat.convert_MDHistoWorkspace_to_data_array(
md_histo)
self.assertEqual(histo_data_array.coords[sc.Dim.Qx].values.shape,
(4, ))
self.assertEqual(histo_data_array.coords[sc.Dim.Qy].values.shape,
(3, ))
self.assertEqual(histo_data_array.coords[sc.Dim.Qz].values.shape,
(5, ))
self.assertEqual(histo_data_array.coords[sc.Dim.Qx].unit,
sc.units.dimensionless / sc.units.angstrom)
self.assertEqual(histo_data_array.coords[sc.Dim.Qy].unit,
sc.units.dimensionless / sc.units.angstrom)
self.assertEqual(histo_data_array.coords[sc.Dim.Qz].unit,
sc.units.dimensionless / sc.units.angstrom)
self.assertEquals(histo_data_array.values.shape, (3, 4, 5))
# Sum over 2 dimensions to simplify finding max.
max_1d = sc.sum(sc.sum(histo_data_array, dim=sc.Dim.Qy),
dim=sc.Dim.Qx).values
max_index = np.argmax(max_1d)
# Check position of max 'peak'
self.assertEqual(np.floor(len(max_1d) / 2), max_index)
# All events in central 'peak'
self.assertEqual(100000, max_1d[max_index])
self.assertTrue('nevents' in histo_data_array.attrs)
def runTest(self):
HelperTestingClass.__init__(self)
def scale_ws(ws):
ws = ws * 100
ws = CreateMDWorkspace(Dimensions='3',
EventType='MDEvent',
Extents='-10,10,-5,5,-1,1',
Names='Q_lab_x,Q_lab_y,Q_lab_z',
Units='1\\A,1\\A,1\\A')
FakeMDEventData(ws, UniformParams="1000000")
pres = SliceViewer(ws)
self._assertNoErrorInADSHandlerFromSeparateThread(partial(scale_ws, ws))
self._qapp.sendPostedEvents()
self.assertTrue(pres.view in self.find_widgets_of_type(str(type(pres.view))))
self.assertNotEqual(pres.ads_observer, None)
pres.view.close()
def test_view_updates_on_replace_when_model_properties_dont_change_mdeventws(
self):
def scale_ws(ws):
ws = ws * 100
ws = CreateMDWorkspace(Dimensions='3',
EventType='MDEvent',
Extents='-10,10,-5,5,-1,1',
Names='Q_lab_x,Q_lab_y,Q_lab_z',
Units='1\\A,1\\A,1\\A')
FakeMDEventData(ws, UniformParams="1000000")
pres = SliceViewer(ws)
self._assertNoErrorInADSHandlerFromSeparateThread(partial(
scale_ws, ws))
QApplication.sendPostedEvents()
self.assertTrue(
pres.view in self.find_widgets_of_type(str(type(pres.view))))
self.assertNotEqual(pres.ads_observer, None)
pres.view.close()
def test_mdhisto_workspace_many_dims(self):
from mantid.simpleapi import (CreateMDWorkspace, FakeMDEventData,
BinMD)
md_event = CreateMDWorkspace(
Dimensions=4,
Extents=[-10, 10, -10, 10, -10, 10, -10, 10],
Names='deltae,y,z,T',
Units='U,U,U,U',
StoreInADS=False)
FakeMDEventData(InputWorkspace=md_event,
PeakParams=[100000, 0, 0, 0, 0, 1],
StoreInADS=False) # Add Peak
md_histo = BinMD(InputWorkspace=md_event,
AlignedDim0='deltae,-10,10,3',
AlignedDim1='y,-10,10,4',
AlignedDim2='z,-10,10,5',
AlignedDim3='T,-10,10,7',
StoreInADS=False)
histo_data_array = scn.mantid.convert_MDHistoWorkspace_to_data_array(
md_histo)
self.assertEqual(4, len(histo_data_array.dims))
def runTest(self):
# Na Mn Cl3
# R -3 H (148)
# 6.592 6.592 18.585177 90 90 120
# UB/wavelength from /HFIR/HB3A/IPTS-25470/shared/autoreduce/HB3A_exp0769_scan0040.nxs
ub = np.array([[1.20297e-01, 1.70416e-01, 1.43000e-04],
[8.16000e-04, -8.16000e-04, 5.38040e-02],
[1.27324e-01, -4.05110e-02, -4.81000e-04]])
wavelength = 1.553
# create fake MDEventWorkspace, similar to what is expected from exp769 after loading with HB3AAdjustSampleNorm
MD_Q_sample = CreateMDWorkspace(
Dimensions='3',
Extents='-5,5,-5,5,-5,5',
Names='Q_sample_x,Q_sample_y,Q_sample_z',
Units='rlu,rlu,rlu',
Frames='QSample,QSample,QSample')
inst = LoadEmptyInstrument(InstrumentName='HB3A')
AddTimeSeriesLog(inst, 'omega', '2010-01-01T00:00:00', 0.)
AddTimeSeriesLog(inst, 'phi', '2010-01-01T00:00:00', 0.)
AddTimeSeriesLog(inst, 'chi', '2010-01-01T00:00:00', 0.)
MD_Q_sample.addExperimentInfo(inst)
SetUB(MD_Q_sample, UB=ub)
ol = OrientedLattice()
ol.setUB(ub)
sg = SpaceGroupFactory.createSpaceGroup("R -3")
hkl = []
sat_hkl = []
for h in range(0, 6):
for k in range(0, 6):
for l in range(0, 11):
if sg.isAllowedReflection([h, k, l]):
if h == k == l == 0:
continue
q = V3D(h, k, l)
q_sample = ol.qFromHKL(q)
if not np.any(np.array(q_sample) > 5):
hkl.append(q)
FakeMDEventData(
MD_Q_sample,
PeakParams='1000,{},{},{},0.05'.format(
*q_sample))
# satellite peaks at 0,0,+1.5
q = V3D(h, k, l + 1.5)
q_sample = ol.qFromHKL(q)
if not np.any(np.array(q_sample) > 5):
sat_hkl.append(q)
FakeMDEventData(
MD_Q_sample,
PeakParams='100,{},{},{},0.02'.format(
*q_sample))
# satellite peaks at 0,0,-1.5
q = V3D(h, k, l - 1.5)
q_sample = ol.qFromHKL(q)
if not np.any(np.array(q_sample) > 5):
sat_hkl.append(q)
FakeMDEventData(
MD_Q_sample,
PeakParams='100,{},{},{},0.02'.format(
*q_sample))
# Check that this fake workpsace gives us the expected UB
peaks = FindPeaksMD(MD_Q_sample,
PeakDistanceThreshold=1,
OutputType='LeanElasticPeak')
FindUBUsingFFT(peaks, MinD=5, MaxD=20)
ShowPossibleCells(peaks)
SelectCellOfType(peaks,
CellType='Rhombohedral',
Centering='R',
Apply=True)
OptimizeLatticeForCellType(peaks, CellType='Hexagonal', Apply=True)
found_ol = peaks.sample().getOrientedLattice()
self.assertAlmostEqual(found_ol.a(), 6.592, places=2)
self.assertAlmostEqual(found_ol.b(), 6.592, places=2)
self.assertAlmostEqual(found_ol.c(), 18.585177, places=2)
self.assertAlmostEqual(found_ol.alpha(), 90)
self.assertAlmostEqual(found_ol.beta(), 90)
self.assertAlmostEqual(found_ol.gamma(), 120)
# nuclear peaks
predict = HB3APredictPeaks(
MD_Q_sample,
Wavelength=wavelength,
ReflectionCondition='Rhombohedrally centred, obverse',
SatellitePeaks=True,
IncludeIntegerHKL=True)
predict = HB3AIntegratePeaks(MD_Q_sample, predict, 0.25)
self.assertEqual(predict.getNumberPeaks(), 66)
# check that the found peaks are expected
for n in range(predict.getNumberPeaks()):
HKL = predict.getPeak(n).getHKL()
self.assertTrue(HKL in hkl, msg=f"Peak {n} with HKL={HKL}")
# magnetic peaks
satellites = HB3APredictPeaks(
MD_Q_sample,
Wavelength=wavelength,
ReflectionCondition='Rhombohedrally centred, obverse',
SatellitePeaks=True,
ModVector1='0,0,1.5',
MaxOrder=1,
IncludeIntegerHKL=False)
satellites = HB3AIntegratePeaks(MD_Q_sample, satellites, 0.1)
self.assertEqual(satellites.getNumberPeaks(), 80)
# check that the found peaks are expected
for n in range(satellites.getNumberPeaks()):
HKL = satellites.getPeak(n).getHKL()
self.assertTrue(HKL in sat_hkl, msg=f"Peak {n} with HKL={HKL}")