def _fitCurvesPerBank(self, vanWS, banks, spline_breaks):
"""
Fits one curve to every bank (where for every bank the data fitted is the result of
summing up all the spectra of the bank). The fitting is done in d-spacing.
@param vanWS :: Vanadium run workspace to fit, expected in TOF units as they are archived
@param banks :: list of banks to consider which is normally all the banks of the instrument
@param spline_breaks :: number of break points when fitting spline functions
@returns a workspace with fitting results for all banks (3 spectra per bank). The spectra
are in dSpacing units.
"""
curves = {}
for b in banks:
indices = EnggUtils.getWsIndicesForBank(vanWS, b)
if not indices:
# no indices at all for this bank, not interested in it, don't add it to the dictionary
# (as when doing Calibrate (not-full)) which does CropData() the original workspace
continue
wsToFit = EnggUtils.cropData(self, vanWS, indices)
wsToFit = EnggUtils.convertToDSpacing(self, wsToFit)
wsToFit = EnggUtils.sumSpectra(self, wsToFit)
fitWS = self._fitBankCurve(wsToFit, b, spline_breaks)
curves.update({b: fitWS})
curvesWS = self._prepareCurvesWS(curves)
return curvesWS
def _fitCurvesPerBank(self, vanWS, banks, spline_breaks):
"""
Fits one curve to every bank (where for every bank the data fitted is the result of
summing up all the spectra of the bank). The fitting is done in d-spacing.
@param vanWS :: Vanadium run workspace to fit, expected in TOF units as they are archived
@param banks :: list of banks to consider which is normally all the banks of the instrument
@param spline_breaks :: number of break points when fitting spline functions
@returns a workspace with fitting results for all banks (3 spectra per bank). The spectra
are in dSpacing units.
"""
curves = {}
for b in banks:
indices = EnggUtils.getWsIndicesForBank(vanWS, b)
if not indices:
# no indices at all for this bank, not interested in it, don't add it to the dictionary
# (as when doing Calibrate (not-full)) which does CropData() the original workspace
continue
wsToFit = EnggUtils.cropData(self, vanWS, indices)
wsToFit = EnggUtils.convertToDSpacing(self, wsToFit)
wsToFit = EnggUtils.sumSpectra(self, wsToFit)
fitWS = self._fitBankCurve(wsToFit, b, spline_breaks)
curves.update({b: fitWS})
curvesWS = self._prepareCurvesWS(curves)
return curvesWS
def PyExec(self):
# Get the run workspace
wks = self.getProperty('InputWorkspace').value
# Get spectra indices either from bank or direct list of indices, checking for errors
bank = self.getProperty('Bank').value
spectra = self.getProperty(self.INDICES_PROP_NAME).value
indices = EnggUtils.getWsIndicesFromInProperties(wks, bank, spectra)
detPos = self.getProperty("DetectorPositions").value
nreports = 5
if detPos:
nreports += 1
prog = Progress(self, start=0, end=1, nreports=nreports)
# Leave only the data for the bank/spectra list requested
prog.report('Selecting spectra from input workspace')
wks = EnggUtils.cropData(self, wks, indices)
prog.report('Masking some bins if requested')
self._mask_bins(wks,
self.getProperty('MaskBinsXMins').value,
self.getProperty('MaskBinsXMaxs').value)
prog.report('Preparing input workspace with vanadium corrections')
# Leave data for the same bank in the vanadium workspace too
vanWS = self.getProperty('VanadiumWorkspace').value
vanIntegWS = self.getProperty('VanIntegrationWorkspace').value
vanCurvesWS = self.getProperty('VanCurvesWorkspace').value
EnggUtils.applyVanadiumCorrections(self, wks, indices, vanWS,
vanIntegWS, vanCurvesWS)
# Apply calibration
if detPos:
self._applyCalibration(wks, detPos)
# Convert to dSpacing
wks = EnggUtils.convertToDSpacing(self, wks)
prog.report('Summing spectra')
# Sum the values across spectra
wks = EnggUtils.sumSpectra(self, wks)
prog.report('Preparing output workspace')
# Convert back to time of flight
wks = EnggUtils.convertToToF(self, wks)
prog.report('Normalizing input workspace if needed')
if self.getProperty('NormaliseByCurrent').value:
self._normalize_by_current(wks)
# OpenGenie displays distributions instead of pure counts (this is done implicitly when
# converting units), so I guess that's what users will expect
self._convertToDistr(wks)
self.setProperty("OutputWorkspace", wks)
def PyExec(self):
# Get the run workspace
wks = self.getProperty('InputWorkspace').value
# Get spectra indices either from bank or direct list of indices, checking for errors
bank = self.getProperty('Bank').value
spectra = self.getProperty(self.INDICES_PROP_NAME).value
indices = EnggUtils.getWsIndicesFromInProperties(wks, bank, spectra)
detPos = self.getProperty("DetectorPositions").value
nreports = 5
if detPos:
nreports += 1
prog = Progress(self, start=0, end=1, nreports=nreports)
# Leave only the data for the bank/spectra list requested
prog.report('Selecting spectra from input workspace')
wks = EnggUtils.cropData(self, wks, indices)
prog.report('Masking some bins if requested')
self._mask_bins(wks, self.getProperty('MaskBinsXMins').value, self.getProperty('MaskBinsXMaxs').value)
prog.report('Preparing input workspace with vanadium corrections')
# Leave data for the same bank in the vanadium workspace too
vanWS = self.getProperty('VanadiumWorkspace').value
vanIntegWS = self.getProperty('VanIntegrationWorkspace').value
vanCurvesWS = self.getProperty('VanCurvesWorkspace').value
EnggUtils.applyVanadiumCorrections(self, wks, indices, vanWS, vanIntegWS, vanCurvesWS)
# Apply calibration
if detPos:
self._applyCalibration(wks, detPos)
# Convert to dSpacing
wks = EnggUtils.convertToDSpacing(self, wks)
prog.report('Summing spectra')
# Sum the values across spectra
wks = EnggUtils.sumSpectra(self, wks)
prog.report('Preparing output workspace')
# Convert back to time of flight
wks = EnggUtils.convertToToF(self, wks)
prog.report('Normalizing input workspace if needed')
if self.getProperty('NormaliseByCurrent').value:
self._normalize_by_current(wks)
# OpenGenie displays distributions instead of pure counts (this is done implicitly when
# converting units), so I guess that's what users will expect
self._convertToDistr(wks)
self.setProperty("OutputWorkspace", wks)
def PyExec(self):
import EnggUtils
# Get the run workspace
ws = self.getProperty('InputWorkspace').value
# Get spectra indices either from bank or direct list of indices, checking for errors
bank = self.getProperty('Bank').value
spectra = self.getProperty(self.INDICES_PROP_NAME).value
indices = EnggUtils.getWsIndicesFromInProperties(ws, bank, spectra)
# Leave the data for the bank we are interested in only
ws = EnggUtils.cropData(self, ws, indices)
# Apply calibration
detPos = self.getProperty("DetectorPositions").value
if detPos:
self._applyCalibration(ws, detPos)
# Leave data for the same bank in the vanadium workspace too
vanWS = self.getProperty("VanadiumWorkspace").value
# if it is raw data (not precalculated curve), needs to be cropped
if EnggUtils.vanadiumWorkspaceIsPrecalculated(ws):
vanWS = EnggUtils.cropData(self, vanWS, indices)
# These corrections rely on ToF<->Dspacing conversions, so they're done after the calibration step
vanFittingWS = EnggUtils.applyVanadiumCorrection(self, ws, vanWS,
self.getProperty('VanadiumIntegWorkspace').value)
# Convert to dSpacing
ws = EnggUtils.convertToDSpacing(self, ws)
# Sum the values
ws = EnggUtils.sumSpectra(self, ws)
# Convert back to time of flight
ws = EnggUtils.convertToToF(self, ws)
# OpenGenie displays distributions instead of pure counts (this is done implicitly when
# converting units), so I guess that's what users will expect
self._convertToDistr(ws)
self.setProperty("OutputWorkspace", ws)
# optinally, generate the workspace with per-bank vanadium fitting curves
outVanWSName = self.getPropertyValue('OutVanadiumCurveFits')
if outVanWSName:
mtd[outVanWSName] = vanFittingWS
def _divideByCurves(self, ws, curves):
"""
Expects a workspace in ToF units. All operations are done in-place (the workspace is
input/output). For every bank-curve pair, divides the corresponding spectra in the
workspace by the (simulated) fitted curve. The division is done in d-spacing (the
input workspace is converted to d-spacing inside this method, but results are converted
back to ToF before returning from this method). The curves workspace is expected in
d-spacing units (since it comes from fitting a sum of spectra for a bank or group of
detectors).
This method is capable of dealing with workspaces with range and bin size different from
the range and bin size of the curves. It will rebin the curves workspace to match the
input 'ws' workspace (using the algorithm RebinToWorkspace).
@param ws :: workspace with (sample) spectra to divide by curves fitted to Vanadium spectra
@param curves :: dictionary of fitting workspaces (in d-spacing), one per bank. The keys are
the bank identifier and the values are their fitting workspaces. The fitting workspaces are
expected as returned by the algorithm 'Fit': 3 spectra: original data, simulated data with fit,
difference between original and simulated data.
"""
# Note that this division could use the algorithm 'Divide'
# This is simple and more efficient than using divide workspace, which requires
# cropping separate workspaces, dividing them separately, then appending them
# with AppendSpectra, etc.
ws = EnggUtils.convertToDSpacing(self, ws)
for b in curves:
# process all the spectra (indices) in one bank
fittedCurve = curves[b]
idxs = EnggUtils.getWsIndicesForBank(ws, b)
if not idxs:
pass
# This RebinToWorkspace is required here: normal runs will have narrower range of X values,
# and possibly different bin size, as compared to (long) Vanadium runs. Same applies to short
# Ceria runs (for Calibrate -non-full) and even long Ceria runs (for Calibrate-Full).
rebinnedFitCurve = self._rebinToMatchWS(fittedCurve, ws)
for i in idxs:
# take values of the second spectrum of the workspace (fit simulation - fitted curve)
ws.setY(i, np.divide(ws.dataY(i), rebinnedFitCurve.readY(1)))
# finally, convert back to ToF
EnggUtils.convertToToF(self, ws)
def _divideByCurves(self, ws, curves):
"""
Expects a workspace in ToF units. All operations are done in-place (the workspace is
input/output). For every bank-curve pair, divides the corresponding spectra in the
workspace by the (simulated) fitted curve. The division is done in d-spacing (the
input workspace is converted to d-spacing inside this method, but results are converted
back to ToF before returning from this method). The curves workspace is expected in
d-spacing units (since it comes from fitting a sum of spectra for a bank or group of
detectors).
This method is capable of dealing with workspaces with range and bin size different from
the range and bin size of the curves. It will rebin the curves workspace to match the
input 'ws' workspace (using the algorithm RebinToWorkspace).
@param ws :: workspace with (sample) spectra to divide by curves fitted to Vanadium spectra
@param curves :: dictionary of fitting workspaces (in d-spacing), one per bank. The keys are
the bank identifier and the values are their fitting workspaces. The fitting workspaces are
expected as returned by the algorithm 'Fit': 3 spectra: original data, simulated data with fit,
difference between original and simulated data.
"""
# Note that this division could use the algorithm 'Divide'
# This is simple and more efficient than using divide workspace, which requires
# cropping separate workspaces, dividing them separately, then appending them
# with AppendSpectra, etc.
ws = EnggUtils.convertToDSpacing(self, ws)
for b in curves:
# process all the spectra (indices) in one bank
fittedCurve = curves[b]
idxs = EnggUtils.getWsIndicesForBank(ws, b)
if not idxs:
pass
# This RebinToWorkspace is required here: normal runs will have narrower range of X values,
# and possibly different bin size, as compared to (long) Vanadium runs. Same applies to short
# Ceria runs (for Calibrate -non-full) and even long Ceria runs (for Calibrate-Full).
rebinnedFitCurve = self._rebinToMatchWS(fittedCurve, ws)
for i in idxs:
# take values of the second spectrum of the workspace (fit simulation - fitted curve)
ws.setY(i, np.divide(ws.dataY(i), rebinnedFitCurve.readY(1)))
# finally, convert back to ToF
EnggUtils.convertToToF(self, ws)
def PyExec(self):
# Get the run workspace
wks = self.getProperty('InputWorkspace').value
# Get spectra indices either from bank or direct list of indices, checking for errors
bank = self.getProperty('Bank').value
spectra = self.getProperty(self.INDICES_PROP_NAME).value
indices = EnggUtils.getWsIndicesFromInProperties(wks, bank, spectra)
# Leave the data for the bank we are interested in only
wks = EnggUtils.cropData(self, wks, indices)
prog = Progress(self, start=0, end=1, nreports=3)
prog.report('Preparing input workspace')
# Leave data for the same bank in the vanadium workspace too
vanWS = self.getProperty('VanadiumWorkspace').value
vanIntegWS = self.getProperty('VanIntegrationWorkspace').value
vanCurvesWS = self.getProperty('VanCurvesWorkspace').value
EnggUtils.applyVanadiumCorrections(self, wks, indices, vanWS,
vanIntegWS, vanCurvesWS)
# Apply calibration
detPos = self.getProperty("DetectorPositions").value
if detPos:
self._applyCalibration(wks, detPos)
# Convert to dSpacing
wks = EnggUtils.convertToDSpacing(self, wks)
prog.report('Summing spectra')
# Sum the values
wks = EnggUtils.sumSpectra(self, wks)
prog.report('Preparing output workspace')
# Convert back to time of flight
wks = EnggUtils.convertToToF(self, wks)
# OpenGenie displays distributions instead of pure counts (this is done implicitly when
# converting units), so I guess that's what users will expect
self._convertToDistr(wks)
self.setProperty("OutputWorkspace", wks)
def PyExec(self):
# Get the run workspace
wks = self.getProperty('InputWorkspace').value
# Get spectra indices either from bank or direct list of indices, checking for errors
bank = self.getProperty('Bank').value
spectra = self.getProperty(self.INDICES_PROP_NAME).value
indices = EnggUtils.getWsIndicesFromInProperties(wks, bank, spectra)
# Leave the data for the bank we are interested in only
wks = EnggUtils.cropData(self, wks, indices)
prog = Progress(self, start=0, end=1, nreports=3)
prog.report('Preparing input workspace')
# Leave data for the same bank in the vanadium workspace too
vanWS = self.getProperty('VanadiumWorkspace').value
vanIntegWS = self.getProperty('VanIntegrationWorkspace').value
vanCurvesWS = self.getProperty('VanCurvesWorkspace').value
EnggUtils.applyVanadiumCorrections(self, wks, indices, vanWS, vanIntegWS, vanCurvesWS)
# Apply calibration
detPos = self.getProperty("DetectorPositions").value
if detPos:
self._applyCalibration(wks, detPos)
# Convert to dSpacing
wks = EnggUtils.convertToDSpacing(self, wks)
prog.report('Summing spectra')
# Sum the values
wks = EnggUtils.sumSpectra(self, wks)
prog.report('Preparing output workspace')
# Convert back to time of flight
wks = EnggUtils.convertToToF(self, wks)
# OpenGenie displays distributions instead of pure counts (this is done implicitly when
# converting units), so I guess that's what users will expect
self._convertToDistr(wks)
self.setProperty("OutputWorkspace", wks)
