本文整理匯總了Python中Direct.DirectEnergyConversion.DirectEnergyConversion.mono_sample方法的典型用法代碼示例。如果您正苦於以下問題：Python DirectEnergyConversion.mono_sample方法的具體用法？Python DirectEnergyConversion.mono_sample怎麽用？Python DirectEnergyConversion.mono_sample使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類Direct.DirectEnergyConversion.DirectEnergyConversion的用法示例。
在下文中一共展示了DirectEnergyConversion.mono_sample方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_late_rebinning
# 需要導入模塊: from Direct.DirectEnergyConversion import DirectEnergyConversion [as 別名]
# 或者: from Direct.DirectEnergyConversion.DirectEnergyConversion import mono_sample [as 別名]
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!')示例2: test_late_rebinning
# 需要導入模塊: from Direct.DirectEnergyConversion import DirectEnergyConversion [as 別名]
# 或者: from Direct.DirectEnergyConversion.DirectEnergyConversion import mono_sample [as 別名]
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!")