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 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 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 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
