def PyExec(self):
import EnginXUtils
ws = self._loadCalibrationRun()
ws = self._prepareWsForFitting(ws)
positionTable = self._createPositionsTable()
indices = EnginXUtils.getWsIndicesForBank(self.getProperty('Bank').value, ws)
prog = Progress(self, 0, 1, len(indices))
for i in indices:
_, difc = self._fitPeaks(ws, i)
det = ws.getDetector(i)
newPos = self._getCalibratedDetPos(difc, det, ws)
positionTable.addRow([det.getID(), newPos])
prog.report()
self.setProperty("DetectorPositions", positionTable)
def PyExec(self):
import EnginXUtils
ws = self._loadCalibrationRun()
ws = self._prepareWsForFitting(ws)
positionTable = self._createPositionsTable()
indices = EnginXUtils.getWsIndicesForBank(self.getProperty('Bank').value, ws)
prog = Progress(self, 0, 1, len(indices))
for i in indices:
_, difc = self._fitPeaks(ws, i)
det = ws.getDetector(i)
newPos = self._getCalibratedDetPos(difc, det, ws)
positionTable.addRow([det.getID(), newPos])
prog.report()
self.setProperty("DetectorPositions", positionTable)
def PyExec(self):
import EnginXUtils
# Get peaks in dSpacing from file
expectedPeaksD = EnginXUtils.readInExpectedPeaks(self.getPropertyValue("ExpectedPeaksFromFile"),
self.getProperty('ExpectedPeaks').value)
if len(expectedPeaksD) < 1:
raise ValueError("Cannot run this algorithm without any input expected peaks")
# Get expected peaks in TOF for the detector
inWS = self.getProperty("InputWorkspace").value
dimType = inWS.getXDimension().getName()
if self.EXPECTED_DIM_TYPE != dimType:
raise ValueError("This algorithm expects a workspace with %s X dimension, but "
"the X dimension of the input workspace is: '%s'" % (self.EXPECTED_DIM_TYPE, dimType))
wsIndex = self.getProperty("WorkspaceIndex").value
# FindPeaks will return a list of peaks sorted by the centre found. Sort the peaks as well,
# so we can match them with fitted centres later.
expectedPeaksToF = sorted(self._expectedPeaksInTOF(expectedPeaksD, inWS, wsIndex))
foundPeaks = self._peaksFromFindPeaks(inWS, expectedPeaksToF, wsIndex)
if foundPeaks.rowCount() < len(expectedPeaksToF):
txt = "Peaks effectively found: " + str(foundPeaks)[1:-1]
self.log().warning("Some peaks from the list of expected peaks were not found by the algorithm "
"FindPeaks which this algorithm uses to check that the data has the the "
"expected peaks. " + txt)
peaksTableName = self.getPropertyValue("OutFittedPeaksTable")
difc, zero = self._fitAllPeaks(inWS, wsIndex, (foundPeaks, expectedPeaksD), peaksTableName)
self._produceOutputs(difc, zero)
def PyExec(self):
import EnginXUtils
# Get the run workspace
ws = self.getProperty('InputWorkspace').value
indices = EnginXUtils.getWsIndicesFromInProperties(ws, self.getProperty('Bank').value,
self.getProperty(self.INDICES_PROP_NAME).value)
# Leave the data for the bank we are interested in only
ws = self._cropData(ws, indices)
# Apply calibration
self._applyCalibration(ws)
# Convert to dSpacing
ws = self._convertToDSpacing(ws)
# Sum the values
ws = self._sumSpectra(ws)
# Convert back to time of flight
ws = self._convertToTOF(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)
def _produceOutputs(self, difc, zero):
"""
Just fills in the output properties as requested
@param difc :: the difc GSAS parameter as fitted here
@param zero :: the zero GSAS parameter as fitted here
"""
import EnginXUtils
self.setProperty('Difc', difc)
self.setProperty('Zero', zero)
# make output table if requested
tblName = self.getPropertyValue("OutputParametersTableName")
if '' != tblName:
EnginXUtils.generateOutputParTable(tblName, difc, zero)
self.log().information("Output parameters added into a table workspace: %s" % tblName)
def PyExec(self):
# Get peaks in dSpacing from file, and check we have what we need, before doing anything
expectedPeaksD = EnginXUtils.readInExpectedPeaks(self.getPropertyValue("ExpectedPeaksFromFile"),
self.getProperty('ExpectedPeaks').value)
if len(expectedPeaksD) < 1:
raise ValueError("Cannot run this algorithm without any input expected peaks")
inWS = self.getProperty('Workspace').value
WSIndices = EnginXUtils.getWsIndicesFromInProperties(inWS, self.getProperty('Bank').value,
self.getProperty(self.INDICES_PROP_NAME).value)
rebinnedWS = self._prepareWsForFitting(inWS)
posTbl = self._calculateCalibPositionsTbl(rebinnedWS, WSIndices, expectedPeaksD)
# Produce 2 results: 'output table' and 'apply calibration' + (optional) calibration file
self.setProperty("OutDetPosTable", posTbl)
self._applyCalibrationTable(inWS, posTbl)
self._outputDetPosFile(self.getPropertyValue('OutDetPosFilename'), posTbl)
def PyExec(self):
import EnginXUtils
focussed_ws = self._focusRun(self.getProperty('InputWorkspace').value,
self.getProperty('Bank').value,
self.getProperty(self.INDICES_PROP_NAME).value)
# Get peaks in dSpacing from file
expectedPeaksD = EnginXUtils.readInExpectedPeaks(self.getPropertyValue("ExpectedPeaksFromFile"),
self.getProperty('ExpectedPeaks').value)
if len(expectedPeaksD) < 1:
raise ValueError("Cannot run this algorithm without any input expected peaks")
difc, zero = self._fitParams(focussed_ws, expectedPeaksD)
self._produceOutputs(difc, zero)
def _cropData(self, ws):
""" Crops the workspace so that only data for the specified bank is left.
NB: This assumes spectra for a bank are consequent.
"""
import EnginXUtils
indices = EnginXUtils.getWsIndicesForBank(self.getProperty("Bank").value, ws)
# Leave only spectra between min and max
alg = self.createChildAlgorithm("CropWorkspace")
alg.setProperty("InputWorkspace", ws)
alg.setProperty("StartWorkspaceIndex", min(indices))
alg.setProperty("EndWorkspaceIndex", max(indices))
alg.execute()
return alg.getProperty("OutputWorkspace").value
def _cropData(self, ws):
""" Crops the workspace so that only data for the specified bank is left.
NB: This assumes spectra for a bank are consequent.
"""
import EnginXUtils
indices = EnginXUtils.getWsIndicesForBank(self.getProperty('Bank').value, ws)
# Leave only spectra between min and max
alg = self.createChildAlgorithm('CropWorkspace')
alg.setProperty('InputWorkspace', ws)
alg.setProperty('StartWorkspaceIndex', min(indices))
alg.setProperty('EndWorkspaceIndex', max(indices))
alg.execute()
return alg.getProperty('OutputWorkspace').value
