def test_late_rebinning(self):
run_monitors=CreateSampleWorkspace(Function='Multiple Peaks', NumBanks=4, BankPixelWidth=1, NumEvents=100000, XUnit='Energy',
XMin=3, XMax=200, BinWidth=0.1)
LoadInstrument(run_monitors,InstrumentName='MARI')
ConvertUnits(InputWorkspace='run_monitors', OutputWorkspace='run_monitors', Target='TOF')
run_monitors = mtd['run_monitors']
tof = run_monitors.dataX(3)
tMin = tof[0]
tMax = tof[-1]
run = CreateSampleWorkspace( Function='Multiple Peaks',WorkspaceType='Event',NumBanks=8, BankPixelWidth=1, NumEvents=100000,
XUnit='TOF',xMin=tMin,xMax=tMax)
LoadInstrument(run,InstrumentName='MARI')
wb_ws = Rebin(run,Params=[tMin,1,tMax],PreserveEvents=False)
# References used to test against ordinary reduction
ref_ws = Rebin(run,Params=[tMin,1,tMax],PreserveEvents=False)
ref_ws_monitors = CloneWorkspace('run_monitors')
# just in case, wb should work without clone too.
wb_clone = CloneWorkspace(wb_ws)
# Run Mono
tReducer = DirectEnergyConversion(run.getInstrument())
tReducer.energy_bins = [-20,0.2,60]
ei_guess = 67.
mono_s = tReducer.mono_sample(run, ei_guess,wb_ws)
#
mono_ref = tReducer.mono_sample(ref_ws, ei_guess,wb_clone)
rez = CheckWorkspacesMatch(mono_s,mono_ref)
self.assertEqual(rez,'Success!')
def test_late_rebinning(self):
run_monitors = CreateSampleWorkspace(Function='Multiple Peaks',
NumBanks=4,
BankPixelWidth=1,
NumEvents=100000,
XUnit='Energy',
XMin=3,
XMax=200,
BinWidth=0.1)
LoadInstrument(run_monitors,
InstrumentName='MARI',
RewriteSpectraMap=True)
ConvertUnits(InputWorkspace='run_monitors',
OutputWorkspace='run_monitors',
Target='TOF')
run_monitors = mtd['run_monitors']
tof = run_monitors.dataX(3)
tMin = tof[0]
tMax = tof[-1]
run = CreateSampleWorkspace(Function='Multiple Peaks',
WorkspaceType='Event',
NumBanks=8,
BankPixelWidth=1,
NumEvents=100000,
XUnit='TOF',
xMin=tMin,
xMax=tMax)
LoadInstrument(run, InstrumentName='MARI', RewriteSpectraMap=True)
run.setMonitorWorkspace(run_monitors)
wb_ws = Rebin(run, Params=[tMin, 1, tMax], PreserveEvents=False)
# References used to test against ordinary reduction
ref_ws = Rebin(run, Params=[tMin, 1, tMax], PreserveEvents=False)
ref_ws_monitors = CloneWorkspace('run_monitors')
ref_ws.setMonitorWorkspace(ref_ws_monitors)
# just in case, wb should work without clone too.
wb_clone = CloneWorkspace(wb_ws)
# Run Mono
tReducer = DirectEnergyConversion(run.getInstrument())
tReducer.energy_bins = [-20, 0.2, 60]
ei_guess = 67.
mono_s = tReducer.mono_sample(run, ei_guess, wb_ws)
#
mono_ref = tReducer.mono_sample(ref_ws, ei_guess, wb_clone)
rez = CompareWorkspaces(mono_s, mono_ref)
self.assertTrue(rez[0])
def test_late_rebinning(self):
run_monitors = CreateSampleWorkspace(
Function="Multiple Peaks",
NumBanks=4,
BankPixelWidth=1,
NumEvents=100000,
XUnit="Energy",
XMin=3,
XMax=200,
BinWidth=0.1,
)
LoadInstrument(run_monitors, InstrumentName="MARI", RewriteSpectraMap=True)
ConvertUnits(InputWorkspace="run_monitors", OutputWorkspace="run_monitors", Target="TOF")
run_monitors = mtd["run_monitors"]
tof = run_monitors.dataX(3)
tMin = tof[0]
tMax = tof[-1]
run = CreateSampleWorkspace(
Function="Multiple Peaks",
WorkspaceType="Event",
NumBanks=8,
BankPixelWidth=1,
NumEvents=100000,
XUnit="TOF",
xMin=tMin,
xMax=tMax,
)
LoadInstrument(run, InstrumentName="MARI", RewriteSpectraMap=True)
run.setMonitorWorkspace(run_monitors)
wb_ws = Rebin(run, Params=[tMin, 1, tMax], PreserveEvents=False)
# References used to test against ordinary reduction
ref_ws = Rebin(run, Params=[tMin, 1, tMax], PreserveEvents=False)
ref_ws_monitors = CloneWorkspace("run_monitors")
ref_ws.setMonitorWorkspace(ref_ws_monitors)
# just in case, wb should work without clone too.
wb_clone = CloneWorkspace(wb_ws)
# Run Mono
tReducer = DirectEnergyConversion(run.getInstrument())
tReducer.energy_bins = [-20, 0.2, 60]
ei_guess = 67.0
mono_s = tReducer.mono_sample(run, ei_guess, wb_ws)
#
mono_ref = tReducer.mono_sample(ref_ws, ei_guess, wb_clone)
rez = CheckWorkspacesMatch(mono_s, mono_ref)
self.assertEqual(rez, "Success!")
