def __init__(self, instrumentName, web_var=None):
""" sets properties defaults for the instrument with Name
and define if wrapper runs from web services or not
"""
# internal variable, indicating if we should try to wait for input files to appear
self._wait_for_file = False
#The property defines the run number, to validate. If defined, switches reduction wrapper from
#reduction to validation mode
self._run_number_to_validate = None
# internal variable, used in system tests to validate workflow,
# with waiting for files. It is the holder to the function
# used during debugging "wait for files" workflow
# instead of Pause algorithm
self._debug_wait_for_files_operation = None
# tolerance to change in some tests if default is not working well
self._tolerr = None
# The variables which are set up from web interface or to be exported to
# web interface
if web_var:
self._run_from_web = True
else:
self._run_from_web = False
self._wvs = ReductionWrapper.var_holder(web_var)
# Initialize reduced for given instrument
self.reducer = DirectEnergyConversion(instrumentName)
#
web_vars = self._wvs.get_all_vars()
if web_vars:
self.reducer.prop_man.set_input_parameters(**web_vars)
def test_get_abs_normalization_factor(self) :
mono_ws = CreateSampleWorkspace(NumBanks=1, BankPixelWidth=4, NumEvents=10000,XUnit='DeltaE',XMin=-5,XMax=15,BinWidth=0.1,function='Flat background')
LoadInstrument(mono_ws,InstrumentName='MARI', RewriteSpectraMap=True)
tReducer = DirectEnergyConversion(mono_ws.getInstrument())
tReducer.prop_man.incident_energy = 5.
tReducer.prop_man.monovan_integr_range=[-10,10]
tReducer.wb_run = mono_ws
(nf1,nf2,nf3,nf4) = tReducer.get_abs_normalization_factor(PropertyManager.wb_run,5.)
self.assertAlmostEqual(nf1,0.58561121802167193,7)
self.assertAlmostEqual(nf1,nf2)
self.assertAlmostEqual(nf2,nf3)
self.assertAlmostEqual(nf3,nf4)
# check warning. WB spectra with 0 signal indicate troubles.
mono_ws = CreateSampleWorkspace(NumBanks=1, BankPixelWidth=4, NumEvents=10000,XUnit='DeltaE',XMin=-5,XMax=15,BinWidth=0.1,function='Flat background')
LoadInstrument(mono_ws,InstrumentName='MARI', RewriteSpectraMap=True)
sig = mono_ws.dataY(0)
sig[:]=0
tReducer.wb_run = mono_ws
(nf1,nf2,nf3,nf4) = tReducer.get_abs_normalization_factor(PropertyManager.wb_run,5.)
self.assertAlmostEqual(nf1,0.585611218022,7)
self.assertAlmostEqual(nf1,nf2)
self.assertAlmostEqual(nf2,nf3)
self.assertAlmostEqual(nf3,nf4)
def test_remove_empty_bg(self):
# create test workspace
wksp = CreateSampleWorkspace(Function='Multiple Peaks',
WorkspaceType='Event',
NumBanks=3,
BankPixelWidth=1,
NumEvents=100,
XUnit='TOF',
XMin=2000,
XMax=20000,
BinWidth=1)
CloneWorkspace(wksp, OutputWorkspace='bg_ws')
AddSampleLog(Workspace=wksp,
LogName='gd_prtn_chrg',
LogText='10',
LogType='Number')
AddSampleLog(Workspace='bg_ws',
LogName='gd_prtn_chrg',
LogText='100',
LogType='Number')
# Prepare reducer
tReducer = DirectEnergyConversion('MAR')
tReducer.prop_man.sample_run = wksp
tReducer.prop_man.empty_bg_run = 'bg_ws'
tReducer.remove_empty_background()
ws = PropertyManager.sample_run.get_workspace()
self.assertTrue(ws.run().hasProperty('empty_bg_removed'))
resWs = 0.9 * wksp
difr = CompareWorkspaces(resWs, ws)
self.assertTrue(difr.Result)
def test_sum_monitors(self):
# create test workspace
monitor_ws=CreateSampleWorkspace(Function='Multiple Peaks', NumBanks=6, BankPixelWidth=1,\
NumEvents=100000, XUnit='Energy', XMin=3, XMax=200, BinWidth=0.1)
ConvertUnits(InputWorkspace=monitor_ws, OutputWorkspace='monitor_ws', Target='TOF')
# Rebin to "formally" make common bin boundaries as it is not considered as such
#any more after converting units (Is this a bug?)
xx = monitor_ws.readX(0)
x_min = min(xx[0],xx[-1])
x_max= max(xx[0],xx[-1])
x_step = (x_max-x_min)/(len(xx)-1)
monitor_ws = Rebin(monitor_ws,Params=[x_min,x_step,x_max])
monitor_ws = mtd['monitor_ws']
#
# keep this workspace for second test below -- clone and give
# special name for RunDescriptor to recognize as monitor workspace for
# fake data workspace we will provide.
_TMPmonitor_ws_monitors = CloneWorkspace(monitor_ws)
# Estimate energy from two monitors
ei,mon1_peak,mon1_index,tzero = \
GetEi(InputWorkspace=monitor_ws, Monitor1Spec=1,Monitor2Spec=4,
EnergyEstimate=62.2,FixEi=False)
self.assertAlmostEqual(ei,62.1449,3)
# Provide instrument parameter, necessary to define
# DirectEnergyConversion class properly
SetInstrumentParameter(monitor_ws,ParameterName='fix_ei',ParameterType='Number',Value='0')
SetInstrumentParameter(monitor_ws,DetectorList=[1,2,3,6],ParameterName='DelayTime',\
ParameterType='Number',Value='0.5')
SetInstrumentParameter(monitor_ws,ParameterName='mon2_norm_spec',\
ParameterType='Number',Value='1')
# initiate test reducer
tReducer = DirectEnergyConversion(monitor_ws.getInstrument())
tReducer.prop_man.ei_mon_spectra= ([1,2,3],6)
tReducer.prop_man.normalise_method = 'current'
tReducer.prop_man.mon2_norm_spec = 2
ei_mon_spectra = tReducer.prop_man.ei_mon_spectra
ei_mon_spectra,monitor_ws = tReducer.sum_monitors_spectra(monitor_ws,ei_mon_spectra)
#
# Check GetEi with summed monitors. Try to run separately.
ei1,mon1_peak,mon1_index,tzero = \
GetEi(InputWorkspace=monitor_ws, Monitor1Spec=1,Monitor2Spec=6,
EnergyEstimate=62.2,FixEi=False)
self.assertAlmostEqual(ei1,ei,2)
# Second test Check get_ei as part of the reduction
tReducer.prop_man.ei_mon_spectra= ([1,2,3],[4,5,6])
tReducer.prop_man.fix_ei = False
# DataWorkspace == monitor_ws data workspace is not used anyway. The only thing we
# use it for is to retrieve monitor workspace from Mantid using its name
ei2,mon1_peak2=tReducer.get_ei(monitor_ws,62.2)
self.assertAlmostEqual(ei2,64.95,2)
ei2b,mon1_peak2=tReducer.get_ei(monitor_ws,62.2)
self.assertAlmostEqual(ei2b,64.95,2)
def test_multirep_mode(self):
# create test workspace
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)
MoveInstrumentComponent(Workspace='run', ComponentName='Detector', DetectorID=1102,Z=1)
# MoveInstrumentComponent(Workspace='run', ComponentName='Detector', DetectorID=1103,Z=4)
# MoveInstrumentComponent(Workspace='run', ComponentName='Detector', DetectorID=1104,Z=5)
# do second
run2 = CloneWorkspace(run)
run2_monitors = CloneWorkspace(run_monitors)
wb_ws = Rebin(run,Params=[tMin,1,tMax],PreserveEvents=False)
# Run multirep
tReducer = DirectEnergyConversion(run.getInstrument())
tReducer.prop_man.run_diagnostics=True
tReducer.hard_mask_file=None
tReducer.map_file=None
tReducer.save_format=None
tReducer.multirep_tof_specta_list = [4,5]
result = tReducer.convert_to_energy(wb_ws,run,[67.,122.],[-2,0.02,0.8])
self.assertEqual(len(result),2)
ws1=result[0]
self.assertEqual(ws1.getAxis(0).getUnit().unitID(),'DeltaE')
x = ws1.readX(0)
self.assertAlmostEqual(x[0],-2*67.)
self.assertAlmostEqual(x[-1],0.8*67.)
ws2=result[1]
self.assertEqual(ws2.getAxis(0).getUnit().unitID(),'DeltaE')
x = ws2.readX(0)
self.assertAlmostEqual(x[0],-2*122.)
self.assertAlmostEqual(x[-1],0.8*122.)
# test another ws
# rename samples from previous workspace to avoid deleting them on current run
for ind,item in enumerate(result):
result[ind]=RenameWorkspace(item,OutputWorkspace='SampleRez#'+str(ind))
#
result2 = tReducer.convert_to_energy(None,run2,[67.,122.],[-2,0.02,0.8])
rez = CheckWorkspacesMatch(result[0],result2[0])
self.assertEqual(rez,'Success!')
rez = CheckWorkspacesMatch(result[1],result2[1])
self.assertEqual(rez,'Success!')
def test_do_white_wb(self) :
wb_ws = CreateSampleWorkspace(NumBanks=1, BankPixelWidth=4, NumEvents=10000)
#LoadParameterFile(Workspace=wb_ws,ParameterXML = used_parameters)
LoadInstrument(wb_ws,InstrumentName='MARI', RewriteSpectraMap=True)
tReducer = DirectEnergyConversion(wb_ws.getInstrument())
white_ws = tReducer.do_white(wb_ws, None, None)
self.assertTrue(white_ws)
def test_diagnostics_wb(self):
wb_ws = CreateSampleWorkspace(NumBanks=1, BankPixelWidth=4, NumEvents=10000)
LoadInstrument(wb_ws,InstrumentName='MARI', RewriteSpectraMap=True)
tReducer = DirectEnergyConversion(wb_ws.getInstrument())
mask_workspace=tReducer.diagnose(wb_ws)
self.assertTrue(mask_workspace)
api.AnalysisDataService.clear()
def test_tof_range(self):
run = CreateSampleWorkspace(Function='Multiple Peaks',
NumBanks=6,
BankPixelWidth=1,
NumEvents=10,
XUnit='Energy',
XMin=5,
XMax=75,
BinWidth=0.2)
LoadInstrument(run, InstrumentName='MARI', RewriteSpectraMap=True)
red = DirectEnergyConversion(run.getInstrument())
red.prop_man.incident_energy = 26.2
red.prop_man.energy_bins = [-20, 0.1, 20]
red.prop_man.multirep_tof_specta_list = [4, 5, 6]
MoveInstrumentComponent(Workspace='run',
ComponentName='Detector',
DetectorID=1102,
Z=3)
MoveInstrumentComponent(Workspace='run',
ComponentName='Detector',
DetectorID=1103,
Z=6)
run_tof = ConvertUnits(run, Target='TOF', EMode='Elastic')
tof_range = red.find_tof_range_for_multirep(run_tof)
self.assertEqual(len(tof_range), 3)
x = run_tof.readX(3)
xMin = min(x)
x = run_tof.readX(5)
xMax = max(x)
self.assertGreater(tof_range[0], xMin)
# self.assertAlmostEqual(tof_range[1],dt)
self.assertLess(tof_range[2], xMax)
# check another working mode
red.prop_man.multirep_tof_specta_list = 4
red.prop_man.incident_energy = 47.505
red.prop_man.energy_bins = [-20, 0.1, 45]
tof_range1 = red.find_tof_range_for_multirep(run_tof)
self.assertGreater(tof_range1[0], xMin)
self.assertLess(tof_range1[2], xMax)
self.assertLess(tof_range1[2], tof_range[2])
self.assertLess(tof_range1[0], tof_range[0])
self.assertLess(tof_range1[1], tof_range[1])
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_energy_to_TOF_range(self):
ws = Load(Filename='MAR11001.raw',LoadMonitors='Include')
en_range = [0.8*13,13,1.2*13]
detIDs=[1,2,3,10]
red = DirectEnergyConversion()
TRange = red.get_TOF_for_energies(ws,en_range,detIDs)
for ind,detID in enumerate(detIDs):
tof = TRange[ind]
y = [1]*(len(tof)-1)
ind = ws.getIndexFromSpectrumNumber(detID)
ExtractSingleSpectrum(InputWorkspace=ws, OutputWorkspace='_ws_template', WorkspaceIndex=ind)
CreateWorkspace(OutputWorkspace='TOF_WS',NSpec = 1,DataX=tof,DataY=y,UnitX='TOF',ParentWorkspace='_ws_template')
EnWs=ConvertUnits(InputWorkspace='TOF_WS',Target='Energy',EMode='Elastic')
eni = EnWs.dataX(0)
for samp,rez in zip(eni,en_range): self.assertAlmostEqual(samp,rez)
# Now Test shifted:
ei,mon1_peak,mon1_index,tzero = GetEi(InputWorkspace=ws, Monitor1Spec=int(2), Monitor2Spec=int(3),EnergyEstimate=13)
ScaleX(InputWorkspace='ws',OutputWorkspace='ws',Operation="Add",Factor=-mon1_peak,InstrumentParameter="DelayTime",Combine=True)
ws = mtd['ws']
mon1_det = ws.getDetector(1)
mon1_pos = mon1_det.getPos()
src_name = ws.getInstrument().getSource().getName()
MoveInstrumentComponent(Workspace='ws',ComponentName= src_name, X=mon1_pos.getX(), Y=mon1_pos.getY(), Z=mon1_pos.getZ(), RelativePosition=False)
# Does not work for monitor 2 as it has been moved to mon2 position and there all tof =0
detIDs=[1,3,10]
TRange1 = red.get_TOF_for_energies(ws,en_range,detIDs)
for ind,detID in enumerate(detIDs):
tof = TRange1[ind]
y = [1]*(len(tof)-1)
ind = ws.getIndexFromSpectrumNumber(detID)
ExtractSingleSpectrum(InputWorkspace=ws, OutputWorkspace='_ws_template', WorkspaceIndex=ind)
CreateWorkspace(OutputWorkspace='TOF_WS',NSpec = 1,DataX=tof,DataY=y,UnitX='TOF',ParentWorkspace='_ws_template')
EnWs=ConvertUnits(InputWorkspace='TOF_WS',Target='Energy',EMode='Elastic')
eni = EnWs.dataX(0)
for samp,rez in zip(eni,en_range): self.assertAlmostEqual(samp,rez)
def test_abs_multirep_with_bkg_and_bleed(self):
# create test workspace
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)
AddSampleLog(run,LogName='gd_prtn_chrg',LogText='1.',LogType='Number')
run.setMonitorWorkspace(run_monitors)
# build "monovanadium"
mono = CloneWorkspace(run)
mono_monitors = CloneWorkspace(run_monitors)
mono.setMonitorWorkspace(mono_monitors)
# build "White-beam"
wb_ws = Rebin(run,Params=[tMin,1,tMax],PreserveEvents=False)
# build "second run" to ensure repeated execution
run2 = CloneWorkspace(run)
run2_monitors = CloneWorkspace(run_monitors)
run2.setMonitorWorkspace(run2_monitors)
# Run multirep
tReducer = DirectEnergyConversion(run.getInstrument())
tReducer.prop_man.run_diagnostics=True
tReducer.hard_mask_file=None
tReducer.map_file=None
tReducer.prop_man.check_background = True
tReducer.prop_man.background_range=[0.99*tMax,tMax]
tReducer.prop_man.monovan_mapfile=None
tReducer.save_format=None
tReducer.prop_man.normalise_method='monitor-2'
tReducer.prop_man.bleed = True
tReducer.norm_mon_integration_range=[tMin,tMax]
AddSampleLog(run,LogName='good_frames',LogText='1.',LogType='Number Series')
result = tReducer.convert_to_energy(wb_ws,run,[67.,122.],[-2,0.02,0.8],None,mono)
self.assertEqual(len(result),2)
ws1=result[0]
self.assertEqual(ws1.getAxis(0).getUnit().unitID(),'DeltaE')
x = ws1.readX(0)
self.assertAlmostEqual(x[0],-2*67.)
self.assertAlmostEqual(x[-1],0.8*67.)
ws2=result[1]
self.assertEqual(ws2.getAxis(0).getUnit().unitID(),'DeltaE')
x = ws2.readX(0)
self.assertAlmostEqual(x[0],-2*122.)
self.assertAlmostEqual(x[-1],0.8*122.)
# test another ws
# rename samples from previous workspace to avoid deleting them on current run
for ind,item in enumerate(result):
result[ind]=RenameWorkspace(item,OutputWorkspace='SampleRez#'+str(ind))
#
AddSampleLog(run2,LogName='goodfrm',LogText='1',LogType='Number')
result2 = tReducer.convert_to_energy(None,run2)
rez = CheckWorkspacesMatch(result[0],result2[0])
self.assertEqual(rez,'Success!')
rez = CheckWorkspacesMatch(result[1],result2[1])
self.assertEqual(rez,'Success!')
def setUp(self):
if self.reducer == None or type(self.reducer) != type(DirectEnergyConversion):
self.reducer = DirectEnergyConversion("MAR")
