def runTest(self):
ws = DirectILLCollectData('ILL/IN6/164192.nxs',
ElasticChannel='Default Elastic Channel',
FlatBkg='Flat Bkg OFF',
Normalisation='Normalisation OFF')
for i in range(ws.getNumberHistograms()):
ws.dataY(i).fill(1)
dE = ConvertUnits(ws, 'DeltaE', 'Direct')
corr = DetectorEfficiencyCorUser(dE)
Ei = corr.run().get('Ei').value
def det_corr(x):
high = x > 5.113
low = x <= 5.113
c = numpy.empty_like(x)
c[high] = 0.94 * (1. - numpy.exp(-3.284 / numpy.sqrt(x[high])))
c[low] = numpy.exp(-0.0565 / numpy.sqrt(x[low])) * (
1. - numpy.exp(-3.284 / numpy.sqrt(x[low])))
return c
corr_at_Ei = det_corr(numpy.array([Ei]))[0]
for i in range(corr.getNumberHistograms()):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
numpy.testing.assert_almost_equal(corr.readY(i),
corr_at_Ei / det_corr(e))
def runTest(self):
ws = DirectILLCollectData('ILL/IN4/084446.nxs', ElasticChannel='Default Elastic Channel',
FlatBkg='Flat Bkg OFF', Normalisation='Normalisation OFF')
for i in range(ws.getNumberHistograms()):
ws.dataY(i).fill(1)
dE = ConvertUnits(ws, 'DeltaE', 'Direct')
corr = DetectorEfficiencyCorUser(dE)
Ei = corr.run().get('Ei').value
def rosace_corr(x):
return 1.0 - numpy.exp(-6.1343 / numpy.sqrt(x))
def wide_angle_corr(x):
return 0.951 * numpy.exp(-0.0887 / numpy.sqrt(x)) * (1 - numpy.exp(-5.597 / numpy.sqrt(x)))
def eff_factor(x, corr_func):
return corr_func(Ei) / corr_func(x)
# Wide-angle detectors are at ws indices 0-299
for i in range(0, 300):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
assert_almost_equal(corr.readY(i), eff_factor(e, wide_angle_corr))
# Rosace detectors are at ws indices 300-395
for i in range(300, 396):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
assert_almost_equal(corr.readY(i), eff_factor(e, rosace_corr))
def runTest(self):
config['default.facility'] = 'ILL'
config['default.instrument'] = 'IN4'
DirectILLCollectData(Run='ILL/IN4/085801-085802.nxs',
OutputWorkspace='vanadium',
OutputEPPWorkspace='vanadium-epps',
OutputRawWorkspace='vanadium-raw',
MonitorPeakWidthInSigmas=3.0)
DirectILLIntegrateVanadium(InputWorkspace='vanadium',
OutputWorkspace='integrated',
EPPWorkspace='vanadium-epps')
DirectILLDiagnostics(
InputWorkspace='vanadium-raw',
OutputWorkspace='diagnostics',
SubalgorithmLogging='Logging ON',
EPPWorkspace='vanadium-epps',
)
# Samples
DirectILLCollectData(Run='ILL/IN4/087294+087295.nxs',
OutputWorkspace='sample',
OutputIncidentEnergyWorkspace='Ei',
OutputElasticChannelWorkspace='Elp',
MonitorPeakWidthInSigmas=3.0)
# Containers
DirectILLCollectData(Run='ILL/IN4/087306-087309.nxs',
OutputWorkspace='container',
IncidentEnergyWorkspace='Ei',
ElasticChannelWorkspace='Elp',
MonitorPeakWidthInSigmas=3.0)
geometry = {
'Shape': 'HollowCylinder',
'Height': 4.0,
'InnerRadius': 1.9,
'OuterRadius': 2.0,
'Center': [0.0, 0.0, 0.0]
}
material = {'ChemicalFormula': 'Cd S', 'SampleNumberDensity': 0.01}
SetSample('sample', geometry, material)
DirectILLSelfShielding(InputWorkspace='sample',
OutputWorkspace='corrections',
EventsPerPoint=20000)
DirectILLApplySelfShielding(
InputWorkspace='sample',
OutputWorkspace='corrected',
SelfShieldingCorrectionWorkspace='corrections',
EmptyContainerWorkspace='container')
DirectILLReduction(InputWorkspace='corrected',
OutputWorkspace='SofQW',
IntegratedVanadiumWorkspace='integrated',
DiagnosticsWorkspace='diagnostics')
CropWorkspace(InputWorkspace='SofQW',
OutputWorkspace='cropped',
XMin=1.,
XMax=2.75,
StartWorkspaceIndex=83,
EndWorkspaceIndex=222)
# The 'run_title' property has been deliberately erased from the test numor.
# We need to add it manually because Save/LoadNexus will do the same for
# the reference file.
mtd['cropped'].mutableRun().addProperty('run_title', '', True)
def runTest(self):
ws = DirectILLCollectData('ILL/IN4/084446.nxs', ElasticChannel='Default Elastic Channel',
FlatBkg='Flat Bkg OFF', Normalisation='Normalisation OFF')
for i in range(ws.getNumberHistograms()):
ws.dataY(i).fill(1)
dE = ConvertUnits(ws, 'DeltaE', 'Direct')
corr = DetectorEfficiencyCorUser(dE)
Ei = corr.run().get('Ei').value
def rosace_corr(x):
return 1.0 - numpy.exp(-6.1343 / numpy.sqrt(x))
def wide_angle_corr(x):
return 0.951 * numpy.exp(-0.0887 / numpy.sqrt(x)) * (1 - numpy.exp(-5.597 / numpy.sqrt(x)))
def eff_factor(x, corr_func):
return corr_func(Ei) / corr_func(x)
# Wide-angle detectors are at ws indices 0-299
for i in range(0, 300):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
numpy.testing.assert_almost_equal(corr.readY(i), eff_factor(e, wide_angle_corr))
# Rosace detectors are at ws indices 300-395
for i in range(300, 396):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
numpy.testing.assert_almost_equal(corr.readY(i), eff_factor(e, rosace_corr))
def runTest(self):
config['default.facility'] = 'ILL'
config['default.instrument'] = 'IN5'
DirectILLCollectData(
Run='ILL/IN5/095893.nxs',
OutputWorkspace='vanadium',
OutputEPPWorkspace='vanadium-epps',
)
DirectILLDiagnostics(InputWorkspace='vanadium',
OutputWorkspace='diagnostics',
MaskedComponents='tube_320')
DirectILLTubeBackground(InputWorkspace='vanadium',
OutputWorkspace='bkg',
EPPWorkspace='vanadium-epps',
DiagnosticsWorkspace='diagnostics')
Subtract(LHSWorkspace='vanadium',
RHSWorkspace='bkg',
OutputWorkspace='vanadium')
DeleteWorkspace('bkg')
DirectILLIntegrateVanadium(InputWorkspace='vanadium',
OutputWorkspace='integrated',
EPPWorkspace='vanadium-epps')
DeleteWorkspace('vanadium')
DeleteWorkspace('vanadium-epps')
DirectILLCollectData(Run='ILL/IN5/096003.nxs',
OutputWorkspace='sample',
OutputEppWorkspace='epps')
DirectILLTubeBackground(InputWorkspace='sample',
OutputWorkspace='bkg',
EPPWorkspace='epps',
DiagnosticsWorkspace='diagnostics')
Subtract(LHSWorkspace='sample',
RHSWorkspace='bkg',
OutputWorkspace='sample')
DirectILLReduction(InputWorkspace='sample',
OutputWorkspace='SofQW',
IntegratedVanadiumWorkspace='integrated',
DiagnosticsWorkspace='diagnostics')
CropWorkspace(InputWorkspace='SofQW',
OutputWorkspace='cropped',
XMin=0.5,
XMax=2.1,
StartWorkspaceIndex=375,
EndWorkspaceIndex=720)
# The 'run_title' property has been deliberately erased from the test numor.
# We need to add it manually because Save/LoadNexus will do the same for
# the reference file.
mtd['cropped'].mutableRun().addProperty('run_title', '', True)
def runTest(self):
ws = DirectILLCollectData('ILL/IN5/104007.nxs', ElasticChannel='Default Elastic Channel',
FlatBkg='Flat Bkg OFF', Normalisation='Normalisation OFF')
for i in range(ws.getNumberHistograms()):
ws.dataY(i).fill(1)
dE = ConvertUnits(ws, 'DeltaE', 'Direct')
corr = DetectorEfficiencyCorUser(dE)
Ei = corr.run().get('Ei').value
def tube_corr(x):
return 1. - numpy.exp(-5.6 / numpy.sqrt(x))
corr_at_Ei = tube_corr(Ei)
for i in range(corr.getNumberHistograms()):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
assert_almost_equal(corr.readY(i), corr_at_Ei / tube_corr(e))
def runTest(self):
ws = DirectILLCollectData('ILL/IN5/104007.nxs', ElasticChannel='Default Elastic Channel',
FlatBkg='Flat Bkg OFF', Normalisation='Normalisation OFF')
for i in range(ws.getNumberHistograms()):
ws.dataY(i).fill(1)
dE = ConvertUnits(ws, 'DeltaE', 'Direct')
corr = DetectorEfficiencyCorUser(dE)
Ei = corr.run().get('Ei').value
def tube_corr(x):
return 1. - numpy.exp(-5.6 / numpy.sqrt(x))
corr_at_Ei = tube_corr(Ei)
for i in range(corr.getNumberHistograms()):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
numpy.testing.assert_almost_equal(corr.readY(i), corr_at_Ei / tube_corr(e))
def runTest(self):
config['default.facility'] = 'ILL'
config['default.instrument'] = 'IN6'
DirectILLCollectData(Run='ILL/IN6/164192.nxs',
OutputWorkspace='vanadium',
OutputEPPWorkspace='vanadium-epps',
OutputRawWorkspace='vanadium-raw')
DirectILLIntegrateVanadium(InputWorkspace='vanadium',
OutputWorkspace='integrated',
EPPWorkspace='vanadium-epps')
DirectILLDiagnostics(
InputWorkspace='vanadium-raw',
OutputWorkspace='diagnostics',
EPPWorkspace='vanadium-epps',
)
# Simulate sample with vanadium
DirectILLCollectData(Run='ILL/IN6/164192.nxs',
OutputWorkspace='sample')
DirectILLReduction(InputWorkspace='sample',
OutputWorkspace='SofQW',
IntegratedVanadiumWorkspace='integrated',
EnergyRebinningParams='-100, 0.01, 4.',
DiagnosticsWorkspace='diagnostics')
CropWorkspace(InputWorkspace='SofQW',
OutputWorkspace='cropped',
XMin=0.7,
XMax=2.1,
StartWorkspaceIndex=9588,
EndWorkspaceIndex=10280)
# GetEiMonDet produces slightly different results on different system. We better
# check the calibrated energy logs here and set them to fixed values to
# enable CompareWorkspaces to do its job. This hack could be removed later if
# CompareWorkspaces supported tolerances for sample log comparison.
ws = mtd['cropped']
run = ws.mutableRun()
self.assertAlmostEqual(run.getProperty('Ei').value, 4.72233, places=4)
run.addProperty('Ei', 4.72, True)
self.assertAlmostEqual(run.getProperty('wavelength').value,
4.16207,
places=4)
run.addProperty('wavelength', 4.16, True)
# The 'run_title' property has been deliberately erased from the test numor.
# We need to add it manually because Save/LoadNexus will do the same for
# the reference file.
mtd['cropped'].mutableRun().addProperty('run_title', '', True)
def setUpClass(cls):
workspace = DirectILLCollectData(
'ILL/IN4/084446.nxs',
EPPCreationMethod='Calculate EPP',
IncidentEnergyCalibration='Energy Calibration OFF',
FlatBkg='Flat Bkg OFF',
Normalisation='Normalisation OFF',
StoreInADS=False)
cls._sqw = DirectILLReduction(workspace,
OutputWorkspace='unused',
StoreInADS=False)
def runTest(self):
ws = DirectILLCollectData('ILL/IN6/164192.nxs', ElasticChannel='Default Elastic Channel',
FlatBkg='Flat Bkg OFF', Normalisation='Normalisation OFF')
for i in range(ws.getNumberHistograms()):
ws.dataY(i).fill(1)
dE = ConvertUnits(ws, 'DeltaE', 'Direct')
corr = DetectorEfficiencyCorUser(dE)
Ei = corr.run().get('Ei').value
def det_corr(x):
high = x > 5.113
low = x <= 5.113
c = numpy.empty_like(x)
c[high] = 0.94 * (1. - numpy.exp(-3.284/numpy.sqrt(x[high])))
c[low] = numpy.exp(-0.0565 / numpy.sqrt(x[low])) * (1.- numpy.exp(-3.284 / numpy.sqrt(x[low])))
return c
corr_at_Ei = det_corr(numpy.array([Ei]))[0]
for i in range(corr.getNumberHistograms()):
x = (corr.readX(i)[:-1] + corr.readX(i)[1:]) / 2.
e = Ei - x
numpy.testing.assert_almost_equal(corr.readY(i), corr_at_Ei / det_corr(e))
def runTest(self):
run = 'ILL/IN5/176053.nxs'
DirectILLCollectData(Run=run,
Normalisation='Normalisation Time',
OutputIncidentEnergyWorkspace='Ei',
OutputElasticChannelWorkspace='Elc',
OutputWorkspace='raw',
OutputEPPWorkspace='Epp')
ws = Load(run, ConvertToTOF=True)
self.ecrase(ws)
DirectILLCollectData(InputWorkspace='ws',
Normalisation='Normalisation Time',
IncidentEnergyWorkspace='Ei',
ElasticChannelWorkspace='Elc',
OutputWorkspace='Eone')
DirectILLReduction(InputWorkspace='Eone',
EnergyRebinning='a',
QBinningParams='',
OutputWorkspace='red')
def test_plotconstE_and_plotconstQ_plot_equal_value_at_crossing(self):
DirectILLCollectData(
Run='ILL/IN4/084447.nxs',
OutputWorkspace='sample',
IncidentEnergyCalibration='Energy Calibration OFF',
FlatBkg='Flat Bkg OFF',
)
DirectILLReduction(InputWorkspace='sample', OutputWorkspace='reduced')
Q = 2.5
figure, axes, cuts = directtools.plotconstQ('reduced', Q, 0.01)
lineDataQ = axes.get_lines()[0].get_data()
E = 2.2
figure, axes, cuts = directtools.plotconstE('reduced', E, 0.01)
lineDataE = axes.get_lines()[0].get_data()
indexE = numpy.argmin(numpy.abs(lineDataQ[0] - E))
indexQ = numpy.argmin(numpy.abs(lineDataE[0] - Q))
self.assertEquals(lineDataQ[1][indexE], lineDataE[1][indexQ])