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 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
