def test_crop_range(self):
original_ws = Load(Filename='INTER00013460')
# Crop out one spectra
temp_ws = ConvertToWavelength.crop_range(original_ws, (0, original_ws.getNumberHistograms()-2))
self.assertEqual(original_ws.getNumberHistograms()-1, temp_ws.getNumberHistograms())
# Crop out all but 2 spectra from start and end.
temp_ws = ConvertToWavelength.crop_range(original_ws, ( (0, 1), (3, 4) ) )
self.assertEqual(2, temp_ws.getNumberHistograms())
# Crop out all but 2 spectra from start and end. Exactly the same as above, but slightly different tuple syntax
temp_ws = ConvertToWavelength.crop_range(original_ws, ( ( (0, 1), (3, 4) ) ))
self.assertEqual(2, temp_ws.getNumberHistograms())
# Crop out all but 1 spectra
temp_ws = ConvertToWavelength.crop_range(original_ws, ( (1, 3) ) )
self.assertEqual(3, temp_ws.getNumberHistograms())
# First and last dectors are cropped off, so indexes go 2-4 rather than 1-5
self.assertEqual(2, temp_ws.getDetector(0).getID())
self.assertEqual(3, temp_ws.getDetector(1).getID())
self.assertEqual(4, temp_ws.getDetector(2).getID())
# Test resilience to junk inputs
self.assertRaises(ValueError, ConvertToWavelength.crop_range, original_ws, 'a')
self.assertRaises(ValueError, ConvertToWavelength.crop_range, original_ws, (1,2,3))
def test_convert(self):
ws = Load(Filename='INTER00013460')
converter = ConvertToWavelength(ws)
monitor_ws, detector_ws = converter.convert(
wavelength_min=0.0,
wavelength_max=10.0,
detector_workspace_indexes=(2, 4),
monitor_workspace_index=0,
correct_monitor=True,
bg_min=2.0,
bg_max=8.0)
self.assertEqual(1, monitor_ws.getNumberHistograms(),
"Wrong number of spectra in monitor workspace")
self.assertEqual(3, detector_ws.getNumberHistograms(),
"Wrong number of spectra in detector workspace")
self.assertEqual("Wavelength",
detector_ws.getAxis(0).getUnit().unitID())
self.assertEqual("Wavelength",
monitor_ws.getAxis(0).getUnit().unitID())
x_min, x_max = ConvertToWavelengthTest.cropped_x_range(detector_ws, 0)
self.assertTrue(x_min >= 0.0)
self.assertTrue(x_max <= 10.0)
def test_crop_range(self):
original_ws = Load(Filename='INTER00013460')
# Crop out one spectra
temp_ws = ConvertToWavelength.crop_range(original_ws, (0, original_ws.getNumberHistograms()-2))
self.assertEqual(original_ws.getNumberHistograms()-1, temp_ws.getNumberHistograms())
# Crop out all but 2 spectra from start and end.
temp_ws = ConvertToWavelength.crop_range(original_ws, ( (0, 1), (3, 4) ) )
self.assertEqual(2, temp_ws.getNumberHistograms())
# Crop out all but 2 spectra from start and end. Exactly the same as above, but slightly different tuple syntax
temp_ws = ConvertToWavelength.crop_range(original_ws, ( ( (0, 1), (3, 4) ) ))
self.assertEqual(2, temp_ws.getNumberHistograms())
# Crop out all but 1 spectra
temp_ws = ConvertToWavelength.crop_range(original_ws, ( (1, 3) ) )
self.assertEqual(3, temp_ws.getNumberHistograms())
# First and last dectors are cropped off, so indexes go 2-4 rather than 1-5
self.assertEqual(2, temp_ws.getDetector(0).getID())
self.assertEqual(3, temp_ws.getDetector(1).getID())
self.assertEqual(4, temp_ws.getDetector(2).getID())
# Test resilience to junk inputs
self.assertRaises(ValueError, ConvertToWavelength.crop_range, original_ws, 'a')
self.assertRaises(ValueError, ConvertToWavelength.crop_range, original_ws, (1,2,3))
def test_convert(self):
ws = Load(Filename='INTER00013460')
converter = ConvertToWavelength(ws)
monitor_ws, detector_ws = converter.convert(wavelength_min=0.0, wavelength_max=10.0, detector_workspace_indexes = (2,4), monitor_workspace_index=0, correct_monitor=True, bg_min=2.0, bg_max=8.0)
self.assertEqual(1, monitor_ws.getNumberHistograms(), "Wrong number of spectra in monitor workspace")
self.assertEqual(3, detector_ws.getNumberHistograms(), "Wrong number of spectra in detector workspace")
self.assertEqual("Wavelength", detector_ws.getAxis(0).getUnit().unitID())
self.assertEqual("Wavelength", monitor_ws.getAxis(0).getUnit().unitID())
x_min, x_max = ConvertToWavelengthTest.cropped_x_range(detector_ws, 0)
self.assertTrue(x_min >= 0.0)
self.assertTrue(x_max <= 10.0)
def test_construction_from_single_ws_name(self):
ws = CreateWorkspace(DataY=[1, 2, 3], DataX=[1, 2, 3])
converter = ConvertToWavelength(ws.name())
self.assertNotEqual(converter, None,
"Should have been able to make a valid converter from a single workspace name")
DeleteWorkspace(ws)
def test_conversion_throws_with_min_wavelength_greater_or_equal_to_max_wavelength(
self):
ws = CreateWorkspace(DataY=[1, 2, 3], DataX=[1, 2, 3])
converter = ConvertToWavelength(ws)
self.assertRaises(ValueError, converter.convert, 1.0, 0.0, (), 0)
self.assertRaises(ValueError, converter.convert, 1.0, 1.0, (), 0)
DeleteWorkspace(ws)
def test_construction_from_many_workspace_names(self):
ws1 = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
ws2 = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
converter = ConvertToWavelength([ws1.name(), ws2.name()])
self.assertNotEqual(converter, None, "Should have been able to make a valid converter from many workspace objects")
DeleteWorkspace(ws1)
DeleteWorkspace(ws2)
def test_construction_from_semicolon_separated_workspaces(self):
ws1 = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
ws2 = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
colon_separated_names = "%s: %s" % (ws1.name(), ws2.name())
converter = ConvertToWavelength(colon_separated_names)
self.assertNotEqual(converter, None, "Should have been able to make a valid converter from many : separated workspace objects")
DeleteWorkspace(ws1)
DeleteWorkspace(ws2)
def test_construction_from_single_ws(self):
ws = CreateWorkspace(DataY=[1, 2, 3], DataX=[1, 2, 3])
converter = ConvertToWavelength(ws)
self.assertTrue(
converter != None,
"Should have been able to make a valid converter from a single workspace"
)
DeleteWorkspace(ws)
def test_sum_workspaces(self):
ws1 = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
ws2 = CloneWorkspace(ws1)
ws3 = CloneWorkspace(ws1)
sum = ConvertToWavelength.sum_workspaces([ws1, ws2, ws3])
self.assertEqual(set([3,6,9]), set(sum.readY(0)), "Fail to sum workspaces correctly")
DeleteWorkspace(ws1)
DeleteWorkspace(ws2)
DeleteWorkspace(ws3)
DeleteWorkspace(sum)
def test_sum_workspaces(self):
ws1 = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
ws2 = CloneWorkspace(ws1)
ws3 = CloneWorkspace(ws1)
sum = ConvertToWavelength.sum_workspaces([ws1, ws2, ws3])
self.assertEqual(set([3,6,9]), set(sum.readY(0)), "Fail to sum workspaces correctly")
DeleteWorkspace(ws1)
DeleteWorkspace(ws2)
DeleteWorkspace(ws3)
DeleteWorkspace(sum)
def test_construction_from_comma_separated_workspaces(self):
ws1 = CreateWorkspace(DataY=[1, 2, 3], DataX=[1, 2, 3])
ws2 = CreateWorkspace(DataY=[1, 2, 3], DataX=[1, 2, 3])
comma_separated_names = "%s, %s" % (ws1.getName(), ws2.getName())
converter = ConvertToWavelength(comma_separated_names)
self.assertTrue(
converter != None,
"Should have been able to make a valid converter from many , separated workspace objects"
)
DeleteWorkspace(ws1)
DeleteWorkspace(ws2)
def quick(run, theta=None, pointdet=True, roi=[0, 0], db=[0, 0], trans='', polcorr=False, usemon=-1, outputType='pd',
debug=False, stitch_start_overlap=10, stitch_end_overlap=12, stitch_params=[1.5, 0.02, 17],
detector_component_name='point-detector', sample_component_name='some-surface-holder',
correct_positions=True, tof_prefix="_"):
'''
Original quick parameters fetched from IDF
'''
run_ws = ConvertToWavelength.to_workspace(run, ws_prefix=tof_prefix)
idf_defaults = get_defaults(run_ws, polcorr)
i0_monitor_index = idf_defaults['I0MonitorIndex']
multi_detector_start = idf_defaults['MultiDetectorStart']
lambda_min = idf_defaults['LambdaMin']
lambda_max = idf_defaults['LambdaMax']
point_detector_start = idf_defaults['PointDetectorStart']
point_detector_stop = idf_defaults['PointDetectorStop']
multi_detector_start = idf_defaults['MultiDetectorStart']
background_min = idf_defaults['MonitorBackgroundMin']
background_max = idf_defaults['MonitorBackgroundMax']
int_min = idf_defaults['MonitorIntegralMin']
int_max = idf_defaults['MonitorIntegralMax']
correction_strategy = idf_defaults['AlgoritmicCorrection']
crho = None
calpha = None
cAp = None
cPp = None
if polcorr and (polcorr != PolarisationCorrection.NONE):
crho = idf_defaults['crho']
calpha = idf_defaults['calpha']
cAp = idf_defaults['cAp']
cPp = idf_defaults['cPp']
return quick_explicit(run=run, i0_monitor_index=i0_monitor_index, lambda_min=lambda_min, lambda_max=lambda_max, \
point_detector_start=point_detector_start, point_detector_stop=point_detector_stop, \
multi_detector_start=multi_detector_start, background_min=background_min,
background_max=background_max, \
int_min=int_min, int_max=int_max, theta=theta, pointdet=pointdet, roi=roi, db=db, trans=trans, \
debug=debug, correction_strategy=correction_strategy,
stitch_start_overlap=stitch_start_overlap, \
stitch_end_overlap=stitch_end_overlap, stitch_params=stitch_params, polcorr=polcorr,
crho=crho, calpha=calpha, cAp=cAp, cPp=cPp, \
detector_component_name=detector_component_name, sample_component_name=sample_component_name,
correct_positions=correct_positions)
def quick(run, theta=None, pointdet=True, roi=[0, 0], db=[0, 0], trans='', polcorr=False, usemon=-1, outputType='pd',
debug=False, stitch_start_overlap=10, stitch_end_overlap=12, stitch_params=[1.5, 0.02, 17],
detector_component_name='point-detector', sample_component_name='some-surface-holder',
correct_positions=True, tof_prefix="_"):
'''
Original quick parameters fetched from IDF
'''
run_ws = ConvertToWavelength.to_workspace(run, ws_prefix=tof_prefix)
idf_defaults = get_defaults(run_ws, polcorr)
i0_monitor_index = idf_defaults['I0MonitorIndex']
multi_detector_start = idf_defaults['MultiDetectorStart']
lambda_min = idf_defaults['LambdaMin']
lambda_max = idf_defaults['LambdaMax']
point_detector_start = idf_defaults['PointDetectorStart']
point_detector_stop = idf_defaults['PointDetectorStop']
multi_detector_start = idf_defaults['MultiDetectorStart']
background_min = idf_defaults['MonitorBackgroundMin']
background_max = idf_defaults['MonitorBackgroundMax']
int_min = idf_defaults['MonitorIntegralMin']
int_max = idf_defaults['MonitorIntegralMax']
correction_strategy = idf_defaults['AlgoritmicCorrection']
crho = None
calpha = None
cAp = None
cPp = None
if polcorr and (polcorr != PolarisationCorrection.NONE):
crho = idf_defaults['crho']
calpha = idf_defaults['calpha']
cAp = idf_defaults['cAp']
cPp = idf_defaults['cPp']
return quick_explicit(run=run, i0_monitor_index=i0_monitor_index, lambda_min=lambda_min, lambda_max=lambda_max,
point_detector_start=point_detector_start, point_detector_stop=point_detector_stop,
multi_detector_start=multi_detector_start, background_min=background_min,
background_max=background_max,
int_min=int_min, int_max=int_max, theta=theta, pointdet=pointdet, roi=roi, db=db, trans=trans,
debug=debug, correction_strategy=correction_strategy,
stitch_start_overlap=stitch_start_overlap,
stitch_end_overlap=stitch_end_overlap, stitch_params=stitch_params, polcorr=polcorr,
crho=crho, calpha=calpha, cAp=cAp, cPp=cPp,
detector_component_name=detector_component_name, sample_component_name=sample_component_name,
correct_positions=correct_positions)
def test_conversion_throws_with_some_flat_background_params_but_not_all(self):
ws = CreateWorkspace(DataY=[1,2,3], DataX=[1,2,3])
converter = ConvertToWavelength(ws)
self.assertRaises(ValueError, converter.convert, 0.0, 1.0, (), 0, True)
DeleteWorkspace(ws)
def make_trans_corr(transrun, stitch_start_overlap, stitch_end_overlap, stitch_params,
lambda_min=None, lambda_max=None, background_min=None,
background_max=None, int_min=None, int_max=None, detector_index_ranges=None,
i0_monitor_index=None):
'''
Make the transmission correction workspace.
'''
# Check to see whether all optional inputs have been provide. If not we have to get them from the IDF.
if not all((lambda_min, lambda_max, background_min, background_max, int_min, int_max, detector_index_ranges, i0_monitor_index)):
logger.notice("make_trans_corr: Fetching missing arguments from the IDF")
instrument_source = transrun
if isinstance(transrun, str):
instrument_source = transrun.split(',')[0]
trans_ws = ConvertToWavelength.to_workspace(instrument_source)
idf_defaults = get_defaults(trans_ws)
# Fetch defaults for anything not specified
if not i0_monitor_index:
i0_monitor_index = idf_defaults['I0MonitorIndex']
if not lambda_min:
lambda_min = idf_defaults['LambdaMin']
if not lambda_max:
lambda_max = idf_defaults['LambdaMax']
if not detector_index_ranges:
point_detector_start = idf_defaults['PointDetectorStart']
point_detector_stop = idf_defaults['PointDetectorStop']
detector_index_ranges = (point_detector_start, point_detector_stop)
if not background_min:
background_min = idf_defaults['MonitorBackgroundMin']
if not background_max:
background_max = idf_defaults['MonitorBackgroundMax']
if not int_min:
int_min = idf_defaults['MonitorIntegralMin']
if not int_max:
int_max = idf_defaults['MonitorIntegralMax']
transWS = None
if isinstance(transrun, str) and (',' in transrun):
slam = transrun.split(',')[0]
llam = transrun.split(',')[1]
print "Transmission runs: ", transrun
to_lam = ConvertToWavelength(slam)
_monitor_ws_slam, _detector_ws_slam = to_lam.convert(wavelength_min=lambda_min, wavelength_max=lambda_max, detector_workspace_indexes=detector_index_ranges, monitor_workspace_index=i0_monitor_index, correct_monitor=True, bg_min=background_min, bg_max=background_max )
_i0p_slam = RebinToWorkspace(WorkspaceToRebin=_monitor_ws_slam, WorkspaceToMatch=_detector_ws_slam)
_mon_int_trans = Integration(InputWorkspace=_i0p_slam, RangeLower=int_min, RangeUpper=int_max)
_detector_ws_slam = Divide(LHSWorkspace=_detector_ws_slam, RHSWorkspace=_mon_int_trans)
to_lam = ConvertToWavelength(llam)
_monitor_ws_llam, _detector_ws_llam = to_lam.convert(wavelength_min=lambda_min, wavelength_max=lambda_max, detector_workspace_indexes=detector_index_ranges, monitor_workspace_index=i0_monitor_index, correct_monitor=True, bg_min=background_min, bg_max=background_max )
_i0p_llam = RebinToWorkspace(WorkspaceToRebin=_monitor_ws_llam, WorkspaceToMatch=_detector_ws_llam)
_mon_int_trans = Integration(InputWorkspace=_i0p_llam, RangeLower=int_min,RangeUpper=int_max)
_detector_ws_llam = Divide(LHSWorkspace=_detector_ws_llam, RHSWorkspace=_mon_int_trans)
print stitch_start_overlap, stitch_end_overlap, stitch_params
transWS, outputScaling = Stitch1D(LHSWorkspace=_detector_ws_slam, RHSWorkspace=_detector_ws_llam, StartOverlap=stitch_start_overlap,\
EndOverlap=stitch_end_overlap, Params=stitch_params)
transWS = RenameWorkspace(InputWorkspace=transWS, OutputWorkspace="TRANS_" + slam + "_" + llam)
else:
to_lam = ConvertToWavelength(transrun)
_monitor_ws_trans, _detector_ws_trans = to_lam.convert(wavelength_min=lambda_min, wavelength_max=lambda_max, detector_workspace_indexes=detector_index_ranges, monitor_workspace_index=i0_monitor_index, correct_monitor=True, bg_min=background_min, bg_max=background_max )
_i0p_trans = RebinToWorkspace(WorkspaceToRebin=_monitor_ws_trans, WorkspaceToMatch=_detector_ws_trans)
_mon_int_trans = Integration( InputWorkspace=_i0p_trans, RangeLower=int_min, RangeUpper=int_max )
transWS = Divide( LHSWorkspace=_detector_ws_trans, RHSWorkspace=_mon_int_trans )
transWS = RenameWorkspace(InputWorkspace=transWS, OutputWorkspace="TRANS_" + transrun)
return transWS
def quick_explicit(run, i0_monitor_index, lambda_min, lambda_max, background_min, background_max, int_min, int_max,
point_detector_start=0, point_detector_stop=0, multi_detector_start=0, theta=None,
pointdet=True,roi=[0,0], db=[0,0], trans='', debug=False, correction_strategy=NullCorrectionStrategy(),
stitch_start_overlap=None, stitch_end_overlap=None, stitch_params=None,
polcorr=False, crho=None, calpha=None, cAp=None, cPp=None, detector_component_name='point-detector',
sample_component_name='some-surface-holder', correct_positions=True ):
'''
Version of quick where all parameters are explicitly provided.
'''
_sample_ws = ConvertToWavelength.to_single_workspace(run)
nHist = _sample_ws.getNumberHistograms()
to_lam = ConvertToWavelength(run)
if pointdet:
detector_index_ranges = (point_detector_start, point_detector_stop)
else:
detector_index_ranges = (multi_detector_start, nHist-1)
_monitor_ws, _detector_ws = to_lam.convert(wavelength_min=lambda_min, wavelength_max=lambda_max,
detector_workspace_indexes=detector_index_ranges,
monitor_workspace_index=i0_monitor_index, correct_monitor=True,
bg_min=background_min, bg_max=background_max )
inst = _sample_ws.getInstrument()
# Some beamline constants from IDF
print i0_monitor_index
print nHist
if run=='0':
RunNumber = '0'
else:
RunNumber = groupGet(_sample_ws.getName(),'samp','run_number')
if not pointdet:
# Proccess Multi-Detector; assume MD goes to the end:
# if roi or db are given in the function then sum over the apropriate channels
print "This is a multidetector run."
_I0M = RebinToWorkspace(WorkspaceToRebin=_monitor_ws,WorkspaceToMatch=_detector_ws)
IvsLam = _detector_ws / _I0M
if (roi != [0,0]) :
ReflectedBeam = SumSpectra(InputWorkspace=IvsLam, StartWorkspaceIndex=roi[0], EndWorkspaceIndex=roi[1])
if (db != [0,0]) :
DirectBeam = SumSpectra(InputWorkspace=_detector_ws, StartWorkspaceIndex=db[0], EndWorkspaceIndex=db[1])
ReflectedBeam = ReflectedBeam / DirectBeam
polCorr(polcorr, IvsLam, crho, calpha, cAp, cPp)
if theta and correct_positions:
IvsQ = l2q(ReflectedBeam, detector_component_name, theta, sample_component_name)
else:
IvsQ = ConvertUnits(InputWorkspace=ReflectedBeam, Target="MomentumTransfer")
# Single Detector processing-------------------------------------------------------------
else:
print "This is a Point-Detector run."
# handle transmission runs
# process the point detector reflectivity
_I0P = RebinToWorkspace(WorkspaceToRebin=_monitor_ws,WorkspaceToMatch=_detector_ws)
IvsLam = Scale(InputWorkspace=_detector_ws,Factor=1)
if not trans:
print "No transmission file. Trying default exponential/polynomial correction..."
IvsLam = correction_strategy.apply(_detector_ws)
IvsLam = Divide(LHSWorkspace=IvsLam, RHSWorkspace=_I0P)
else: # we have a transmission run
_monInt = Integration(InputWorkspace=_I0P,RangeLower=int_min,RangeUpper=int_max)
IvsLam = Divide(LHSWorkspace=_detector_ws,RHSWorkspace=_monInt)
names = mtd.getObjectNames()
IvsLam = transCorr(trans, IvsLam, lambda_min, lambda_max, background_min, background_max,
int_min, int_max, detector_index_ranges, i0_monitor_index, stitch_start_overlap,
stitch_end_overlap, stitch_params )
IvsLam = polCorr(polcorr, IvsLam, crho, calpha, cAp, cPp)
# Convert to I vs Q
# check if detector in direct beam
if theta == None or theta == 0 or theta == '':
inst = groupGet('IvsLam','inst')
detLocation=inst.getComponentByName(detector_component_name).getPos()
sampleLocation=inst.getComponentByName(sample_component_name).getPos()
detLocation=inst.getComponentByName(detector_component_name).getPos()
source=inst.getSource()
beamPos = sampleLocation - source.getPos()
theta = groupGet(str(_sample_ws),'samp','theta')
if not theta:
theta = inst.getComponentByName(detector_component_name).getTwoTheta(sampleLocation, beamPos)*180.0/math.pi/2.0
print "Det location: ", detLocation, "Calculated theta = ",theta
if correct_positions: # detector is not in correct place
# Get detector angle theta from NeXuS
logger.information('The detectorlocation is not at Y=0')
print 'Nexus file theta =', theta
IvsQ = l2q(IvsLam, detector_component_name, theta, sample_component_name)
else:
IvsQ = ConvertUnits(InputWorkspace=IvsLam,OutputWorkspace="IvsQ",Target="MomentumTransfer")
else:
if correct_positions:
theta = float(theta)
try:
IvsQ = l2q(IvsLam, detector_component_name, theta, sample_component_name)
except AttributeError:
logger.warning("detector_component_name " + detector_component_name + " is unknown")
IvsQ = ConvertUnits(InputWorkspace=IvsLam,OutputWorkspace="IvsQ",Target="MomentumTransfer")
else:
IvsQ = ConvertUnits(InputWorkspace=IvsLam,OutputWorkspace="IvsQ",Target="MomentumTransfer")
RenameWorkspace(InputWorkspace=IvsLam,OutputWorkspace=RunNumber+'_IvsLam')
if isinstance(IvsLam, WorkspaceGroup):
counter = 0
for ws in IvsLam:
RenameWorkspace(ws, OutputWorkspace=RunNumber+'_IvsLam_'+str(counter))
counter += 1
RenameWorkspace(InputWorkspace=IvsQ,OutputWorkspace=RunNumber+'_IvsQ')
# delete all temporary workspaces unless in debug mode (debug=1)
if not debug:
cleanup()
if mtd.doesExist('IvsLam'):
DeleteWorkspace('IvsLam')
return mtd[RunNumber+'_IvsLam'], mtd[RunNumber+'_IvsQ'], theta
def autoreduce(RBno,cycle, transRun=[], runRange=[], oldList=[], auto=0, angles=[], diagnostics=False):
if not runRange:
rlist = INTERsearch(RBno, cycle, diagnostics=diagnostics)
else:
rlist = INTERsearch(RBno, cycle, runRange, diagnostics=diagnostics)
tupsort = make_tuples(rlist)
sortedList = sort_runs(tupsort)
newList = [item for item in sortedList if item not in oldList]
for sample in newList:
wq_list=[]
overlapLow=[]
overlapHigh=[]
index=0
for item in sample:
runno = item[0]
angle = item[1]
runnos=string.split(runno,'+')
runnos = [int(i) for i in runnos] # check if runs have been added together
try:
angle=float(angle)
except ValueError:
angle=0.0
print "Could not determine theta! Skipping run."
if len(runRange) and not len(set(runRange) & set(runnos)):
angle=0.0 # will be skipped below
if float(angle)>0.0:
ws = ConvertToWavelength.to_workspace(runno+'.raw', ws_prefix="")
if not mtd.doesExist(runno+'_IvsQ'):
th = angle
#if len(transRun)>1 and index>0:
if len(transRun)>1:
if not angles:
angle=angle
else:
try:
angle=angles[index]
except:
print("Not enough angles specified.")
#angle=angles[1]
try:
transmRun=transRun[index]
cutoff = INTERexptype()[index]
print(cutoff,"=cutoff")
ReflectometryReductionOneAuto(InputWorkspace=ws, FirstTransmissionRun=transmRun, WavelengthMin=cutoff, thetaIn=angle, OutputWorkspaceBinned=runno+'_IvsQ_binned', OutputWorkspace=runno+'_IvsQ', OutputWorkspaceWavelength=runno+'_IvsLam')
wq=mtd[runno+'_IvsQ']
th = angle
except:
print("Not enough transmission runs specified or transmission workspace doesn't exist, for run "+str(ws))
else:
if not angles:
angle=angle
#else:
#angle=angles[0]
#cutoff = INTERexptype()
cutoff = INTERexptype()[index]
print(cutoff,"=cutoff")
ReflectometryReductionOneAuto(InputWorkspace=ws, FirstTransmissionRun=transRun[0], thetaIn=angle, WavelengthMin=cutoff, OutputWorkspaceBinned=runno+'_IvsQ_binned', OutputWorkspace=runno+'_IvsQ', OutputWorkspaceWavelength=runno+'_IvsLam')
wq=mtd[runno+'_IvsQ']
th = angle
else:
wq=mtd[runno+'_IvsQ']
th=angle
wq_list.append(runno+'_IvsQ')
inst = wq.getInstrument()
lmin = 1.8 #inst.getNumberParameter('LambdaMin')[0] + 1
lmax = 15 #inst.getNumberParameter('LambdaMax')[0] - 2
qmin = 4 * math.pi / lmax * math.sin(th * math.pi / 180)
qmax = 4 * math.pi / lmin * math.sin(th * math.pi / 180)
overlapLow.append(qmin)
overlapHigh.append(qmax)
dqq = NRCalculateSlitResolution(Workspace=wq)
index=index+1
if len(wq_list):
w1 = getWorkspace(wq_list[0])
w2 = getWorkspace(wq_list[-1])
Qmin = min(w1.readX(0))
Qmax = max(w2.readX(0))
Qmax = 0.3
#print Qmin, Qmax, dqq
#print overlapHigh
if len(wq_list)>1:
outputwksp = string.split(wq_list[0],sep='_')[0] + '_' + string.split(wq_list[-1],sep='_')[0][3:]
else:
outputwksp = string.split(wq_list[0],sep='_')[0] + '_IvsQ_binned'
SaveAscii(InputWorkspace=outputwksp,Filename=savepath+outputwksp+'.dat',Separator='Space',ColumnHeader=False,ScientificFormat=True,WriteSpectrumID=False)
if not mtd.doesExist(outputwksp):
wcomb = combineDataMulti(wq_list,outputwksp , overlapLow, overlapHigh,Qmin, Qmax, -dqq, 0, keep=True)
SaveAscii(InputWorkspace=outputwksp,Filename=savepath+outputwksp+'.dat',Separator='Space',ColumnHeader=False,ScientificFormat=True,WriteSpectrumID=False)
return sortedList
def quick_explicit(run,
i0_monitor_index,
lambda_min,
lambda_max,
background_min,
background_max,
int_min,
int_max,
point_detector_start=0,
point_detector_stop=0,
multi_detector_start=0,
theta=None,
pointdet=True,
roi=[0, 0],
db=[0, 0],
trans='',
debug=False,
correction_strategy=NullCorrectionStrategy(),
stitch_start_overlap=None,
stitch_end_overlap=None,
stitch_params=None,
polcorr=False,
crho=None,
calpha=None,
cAp=None,
cPp=None,
detector_component_name='point-detector',
sample_component_name='some-surface-holder',
correct_positions=True):
'''
Version of quick where all parameters are explicitly provided.
'''
_sample_ws = ConvertToWavelength.to_single_workspace(run)
nHist = _sample_ws.getNumberHistograms()
to_lam = ConvertToWavelength(run)
if pointdet:
detector_index_ranges = (point_detector_start, point_detector_stop)
else:
detector_index_ranges = (multi_detector_start, nHist - 1)
_monitor_ws, _detector_ws = to_lam.convert(
wavelength_min=lambda_min,
wavelength_max=lambda_max,
detector_workspace_indexes=detector_index_ranges,
monitor_workspace_index=i0_monitor_index,
correct_monitor=True,
bg_min=background_min,
bg_max=background_max)
inst = _sample_ws.getInstrument()
# Some beamline constants from IDF
print(i0_monitor_index)
print(nHist)
if run == '0':
RunNumber = '0'
else:
RunNumber = groupGet(_sample_ws.name(), 'samp', 'run_number')
if not pointdet:
# Proccess Multi-Detector; assume MD goes to the end:
# if roi or db are given in the function then sum over the apropriate channels
print("This is a multidetector run.")
_I0M = RebinToWorkspace(WorkspaceToRebin=_monitor_ws,
WorkspaceToMatch=_detector_ws)
IvsLam = _detector_ws / _I0M
if (roi != [0, 0]):
ReflectedBeam = SumSpectra(InputWorkspace=IvsLam,
StartWorkspaceIndex=roi[0],
EndWorkspaceIndex=roi[1])
if (db != [0, 0]):
DirectBeam = SumSpectra(InputWorkspace=_detector_ws,
StartWorkspaceIndex=db[0],
EndWorkspaceIndex=db[1])
ReflectedBeam = ReflectedBeam / DirectBeam
polCorr(polcorr, IvsLam, crho, calpha, cAp, cPp)
if theta and correct_positions:
IvsQ = l2q(ReflectedBeam, detector_component_name, theta,
sample_component_name)
else:
IvsQ = ConvertUnits(InputWorkspace=ReflectedBeam,
Target="MomentumTransfer")
# Single Detector processing-------------------------------------------------------------
else:
print("This is a Point-Detector run.")
# handle transmission runs
# process the point detector reflectivity
_I0P = RebinToWorkspace(WorkspaceToRebin=_monitor_ws,
WorkspaceToMatch=_detector_ws)
IvsLam = Scale(InputWorkspace=_detector_ws, Factor=1)
if not trans:
print(
"No transmission file. Trying default exponential/polynomial correction..."
)
IvsLam = correction_strategy.apply(_detector_ws)
IvsLam = Divide(LHSWorkspace=IvsLam, RHSWorkspace=_I0P)
else: # we have a transmission run
_monInt = Integration(InputWorkspace=_I0P,
RangeLower=int_min,
RangeUpper=int_max)
IvsLam = Divide(LHSWorkspace=_detector_ws, RHSWorkspace=_monInt)
IvsLam = transCorr(trans, IvsLam, lambda_min, lambda_max,
background_min, background_max, int_min,
int_max, detector_index_ranges,
i0_monitor_index, stitch_start_overlap,
stitch_end_overlap, stitch_params)
IvsLam = polCorr(polcorr, IvsLam, crho, calpha, cAp, cPp)
# Convert to I vs Q
# check if detector in direct beam
if theta is None or theta == 0 or theta == '':
inst = groupGet('IvsLam', 'inst')
detLocation = inst.getComponentByName(
detector_component_name).getPos()
sampleLocation = inst.getComponentByName(
sample_component_name).getPos()
detLocation = inst.getComponentByName(
detector_component_name).getPos()
source = inst.getSource()
beamPos = sampleLocation - source.getPos()
theta = groupGet(str(_sample_ws), 'samp', 'theta')
if not theta:
theta = inst.getComponentByName(
detector_component_name).getTwoTheta(
sampleLocation, beamPos) * 180.0 / math.pi / 2.0
print("Det location: ", detLocation, "Calculated theta = ", theta)
if correct_positions: # detector is not in correct place
# Get detector angle theta from NeXuS
logger.information('The detectorlocation is not at Y=0')
print('Nexus file theta =', theta)
IvsQ = l2q(IvsLam, detector_component_name, theta,
sample_component_name)
else:
IvsQ = ConvertUnits(InputWorkspace=IvsLam,
OutputWorkspace="IvsQ",
Target="MomentumTransfer")
else:
if correct_positions:
theta = float(theta)
try:
IvsQ = l2q(IvsLam, detector_component_name, theta,
sample_component_name)
except AttributeError:
logger.warning("detector_component_name " +
detector_component_name + " is unknown")
IvsQ = ConvertUnits(InputWorkspace=IvsLam,
OutputWorkspace="IvsQ",
Target="MomentumTransfer")
else:
IvsQ = ConvertUnits(InputWorkspace=IvsLam,
OutputWorkspace="IvsQ",
Target="MomentumTransfer")
RenameWorkspace(InputWorkspace=IvsLam,
OutputWorkspace=RunNumber + '_IvsLam')
if isinstance(IvsLam, WorkspaceGroup):
counter = 0
for ws in IvsLam:
RenameWorkspace(ws,
OutputWorkspace=RunNumber + '_IvsLam_' +
str(counter))
counter += 1
RenameWorkspace(InputWorkspace=IvsQ, OutputWorkspace=RunNumber + '_IvsQ')
# delete all temporary workspaces unless in debug mode (debug=1)
if not debug:
cleanup()
if mtd.doesExist('IvsLam'):
DeleteWorkspace('IvsLam')
return mtd[RunNumber + '_IvsLam'], mtd[RunNumber + '_IvsQ'], theta
def make_trans_corr(transrun,
stitch_start_overlap,
stitch_end_overlap,
stitch_params,
lambda_min=None,
lambda_max=None,
background_min=None,
background_max=None,
int_min=None,
int_max=None,
detector_index_ranges=None,
i0_monitor_index=None):
'''
Make the transmission correction workspace.
'''
# Check to see whether all optional inputs have been provide. If not we have to get them from the IDF.
if not all((lambda_min, lambda_max, background_min, background_max,
int_min, int_max, detector_index_ranges, i0_monitor_index)):
logger.notice(
"make_trans_corr: Fetching missing arguments from the IDF")
instrument_source = transrun
if isinstance(transrun, str):
instrument_source = transrun.split(',')[0]
trans_ws = ConvertToWavelength.to_workspace(instrument_source)
idf_defaults = get_defaults(trans_ws)
# Fetch defaults for anything not specified
if not i0_monitor_index:
i0_monitor_index = idf_defaults['I0MonitorIndex']
if not lambda_min:
lambda_min = idf_defaults['LambdaMin']
if not lambda_max:
lambda_max = idf_defaults['LambdaMax']
if not detector_index_ranges:
point_detector_start = idf_defaults['PointDetectorStart']
point_detector_stop = idf_defaults['PointDetectorStop']
detector_index_ranges = (point_detector_start, point_detector_stop)
if not background_min:
background_min = idf_defaults['MonitorBackgroundMin']
if not background_max:
background_max = idf_defaults['MonitorBackgroundMax']
if not int_min:
int_min = idf_defaults['MonitorIntegralMin']
if not int_max:
int_max = idf_defaults['MonitorIntegralMax']
transWS = None
if isinstance(transrun, str) and (',' in transrun):
slam = transrun.split(',')[0]
llam = transrun.split(',')[1]
print("Transmission runs: ", transrun)
to_lam = ConvertToWavelength(slam)
_monitor_ws_slam, _detector_ws_slam = to_lam.convert(
wavelength_min=lambda_min,
wavelength_max=lambda_max,
detector_workspace_indexes=detector_index_ranges,
monitor_workspace_index=i0_monitor_index,
correct_monitor=True,
bg_min=background_min,
bg_max=background_max)
_i0p_slam = RebinToWorkspace(WorkspaceToRebin=_monitor_ws_slam,
WorkspaceToMatch=_detector_ws_slam)
_mon_int_trans = Integration(InputWorkspace=_i0p_slam,
RangeLower=int_min,
RangeUpper=int_max)
_detector_ws_slam = Divide(LHSWorkspace=_detector_ws_slam,
RHSWorkspace=_mon_int_trans)
to_lam = ConvertToWavelength(llam)
_monitor_ws_llam, _detector_ws_llam = to_lam.convert(
wavelength_min=lambda_min,
wavelength_max=lambda_max,
detector_workspace_indexes=detector_index_ranges,
monitor_workspace_index=i0_monitor_index,
correct_monitor=True,
bg_min=background_min,
bg_max=background_max)
_i0p_llam = RebinToWorkspace(WorkspaceToRebin=_monitor_ws_llam,
WorkspaceToMatch=_detector_ws_llam)
_mon_int_trans = Integration(InputWorkspace=_i0p_llam,
RangeLower=int_min,
RangeUpper=int_max)
_detector_ws_llam = Divide(LHSWorkspace=_detector_ws_llam,
RHSWorkspace=_mon_int_trans)
print(stitch_start_overlap, stitch_end_overlap, stitch_params)
transWS, _outputScaling = Stitch1D(LHSWorkspace=_detector_ws_slam,
RHSWorkspace=_detector_ws_llam,
StartOverlap=stitch_start_overlap,
EndOverlap=stitch_end_overlap,
Params=stitch_params)
transWS = RenameWorkspace(InputWorkspace=transWS,
OutputWorkspace="TRANS_" + slam + "_" + llam)
else:
to_lam = ConvertToWavelength(transrun)
_monitor_ws_trans, _detector_ws_trans = to_lam.convert(
wavelength_min=lambda_min,
wavelength_max=lambda_max,
detector_workspace_indexes=detector_index_ranges,
monitor_workspace_index=i0_monitor_index,
correct_monitor=True,
bg_min=background_min,
bg_max=background_max)
_i0p_trans = RebinToWorkspace(WorkspaceToRebin=_monitor_ws_trans,
WorkspaceToMatch=_detector_ws_trans)
_mon_int_trans = Integration(InputWorkspace=_i0p_trans,
RangeLower=int_min,
RangeUpper=int_max)
transWS = Divide(LHSWorkspace=_detector_ws_trans,
RHSWorkspace=_mon_int_trans)
transWS = RenameWorkspace(InputWorkspace=transWS,
OutputWorkspace="TRANS_" + transrun)
return transWS
