def PyExec(self):
input_ws = self.getProperty("InputWorkspace").value
eff_ws = self.getProperty("DetectorEfficiencyWorkspace").value
transposed = Transpose(InputWorkspace=eff_ws, StoreInADS=False)
efficiencies = transposed.extractY().flatten()
errors = transposed.extractE().flatten()
n_hist = input_ws.getNumberHistograms()
if n_hist % efficiencies.size != 0:
raise ValueError(
'Number of histograms in input workspace is not a multiple of number of entries in detector efficiency '
'workspace.')
n_time_indexes = n_hist / efficiencies.size
to_multiply = CreateWorkspace(DataY=np.repeat(efficiencies,
n_time_indexes),
DataE=np.repeat(errors, n_time_indexes),
DataX=np.zeros(n_hist),
NSpec=n_hist,
StoreInADS=False)
output = Multiply(
LHSWorkspace=input_ws,
RHSWorkspace=to_multiply,
OutputWorkspace=self.getPropertyValue("OutputWorkspace"))
# In the output we should mask the detectors where calibration constant is masked
det_IDs = ''
n_pixels_per_tube = eff_ws.getNumberHistograms()
for spectrum in range(n_pixels_per_tube):
if eff_ws.hasMaskedBins(spectrum):
masked = eff_ws.maskedBinsIndices(spectrum)
for bin in masked:
det_IDs += str(bin * n_pixels_per_tube + spectrum +
1) + ','
if det_IDs:
MaskDetectors(Workspace=output, DetectorList=det_IDs[:-1])
self.setProperty("OutputWorkspace", output)
def PyExec(self):
input_ws = self.getProperty("InputWorkspace").value
eff_ws = self.getProperty("DetectorEfficiencyWorkspace").value
transposed = Transpose(InputWorkspace=eff_ws, StoreInADS=False)
efficiencies = transposed.extractY().flatten()
errors = transposed.extractE().flatten()
n_hist = input_ws.getNumberHistograms()
if n_hist % efficiencies.size != 0:
raise ValueError('Number of histograms in input workspace is not a multiple of number of entries in detector efficiency '
'workspace.')
n_time_indexes = n_hist / efficiencies.size
to_multiply = CreateWorkspace(DataY=np.repeat(efficiencies, n_time_indexes), DataE=np.repeat(errors, n_time_indexes),
DataX=np.zeros(n_hist), NSpec=n_hist, StoreInADS=False)
output = Multiply(LHSWorkspace=input_ws, RHSWorkspace=to_multiply, OutputWorkspace=self.getPropertyValue("OutputWorkspace"))
# In the output we should mask the detectors where calibration constant is masked
det_IDs = ''
n_pixels_per_tube = eff_ws.getNumberHistograms()
for spectrum in range(n_pixels_per_tube):
if eff_ws.hasMaskedBins(spectrum):
masked = eff_ws.maskedBinsIndices(spectrum)
for bin in masked:
det_IDs += str(bin * n_pixels_per_tube + spectrum + 1) + ','
if det_IDs:
MaskDetectors(Workspace=output, DetectorList=det_IDs[:-1])
self.setProperty("OutputWorkspace", output)
def PyExec(self):
input_ws = self.getProperty("InputWorkspace").value
eff_ws = self.getProperty("DetectorEfficiencyWorkspace").value
transposed = Transpose(InputWorkspace=eff_ws, StoreInADS=False)
efficiencies = transposed.extractY().flatten()
errors = transposed.extractE().flatten()
n_hist = input_ws.getNumberHistograms()
if n_hist % efficiencies.size != 0:
raise ValueError('Number of histograms in input workspace is not a multiple of number of entries in detector efficiency '
'workspace.')
n_time_indexes = n_hist / efficiencies.size
to_multiply = CreateWorkspace(DataY=np.repeat(efficiencies, n_time_indexes),DataE=np.repeat(errors, n_time_indexes),
DataX=np.zeros(n_hist), NSpec=n_hist, StoreInADS=False)
output = Multiply(LHSWorkspace=input_ws, RHSWorkspace=to_multiply, OutputWorkspace=self.getPropertyValue("OutputWorkspace"))
self.setProperty("OutputWorkspace", output)
def PyExec(self):
input_ws = self.getProperty("InputWorkspace").value
eff_ws = self.getProperty("DetectorEfficiencyWorkspace").value
transposed = Transpose(InputWorkspace=eff_ws, StoreInADS=False)
efficiencies = transposed.extractY().flatten()
errors = transposed.extractE().flatten()
n_hist = input_ws.getNumberHistograms()
if n_hist % efficiencies.size != 0:
raise ValueError(
'Number of histograms in input workspace is not a multiple of number of entries in detector efficiency '
'workspace.')
n_time_indexes = n_hist / efficiencies.size
to_multiply = CreateWorkspace(DataY=np.repeat(efficiencies,
n_time_indexes),
DataE=np.repeat(errors, n_time_indexes),
DataX=np.zeros(n_hist),
NSpec=n_hist,
StoreInADS=False)
output = Multiply(
LHSWorkspace=input_ws,
RHSWorkspace=to_multiply,
OutputWorkspace=self.getPropertyValue("OutputWorkspace"))
self.setProperty("OutputWorkspace", output)