def _convert_to_angle(self, w, name):
"""
Output the integrated intensity for each elastic detector versus
detector angle with the neutron beam.
Masked elastic detectors are assigned a zero intensity
Parameters
----------
w: Mantid.MatrixWorkspace2D
name: str
Name of output workspace
Returns
-------
Mantid.MatrixWorkspace2D
"""
id_s, id_e = 16386, 17534 # start and end for elastic detector ID's
_t_w_name = tws('convert_to_angle')
_t_w = Integration(w, OutputWorkspace=_t_w_name)
sp = _t_w.spectrumInfo()
x, y, e = [list(), list(), list()]
for i in range(_t_w.getNumberHistograms()):
id_i = _t_w.getDetector(i).getID()
if id_s <= id_i <= id_e:
x.append(np.degrees(sp.twoTheta(i)))
if sp.isMasked(i) is True:
y.append(0.0)
e.append(1.0)
else:
y.append(_t_w.readY(i)[0])
e.append(_t_w.readE(i)[0])
x = np.asarray(x)
y = np.asarray(y)
e = np.asarray(e)
od = np.argsort(x) # order in ascending angles
title = 'Angle between detector and incoming neutron beam'
_t_w = CreateWorkspace(DataX=x[od],
DataY=y[od],
DataE=e[od],
NSpec=1,
UnitX='Degrees',
WorkspaceTitle=title,
OutputWorkspace=_t_w_name)
RenameWorkspace(_t_w, OutputWorkspace=name)
return _t_w
def PyExec(self):
from mantid.simpleapi import CropWorkspace, Integration, DeleteWorkspace
in_ws = self.getPropertyValue("InputWorkspace")
min_wavelength = self.getPropertyValue("StartWavelength")
keep_workspaces = self.getPropertyValue("KeepIntermediateWorkspaces")
# Crop off lower wavelengths where the signal is also lower.
cropped_ws = CropWorkspace(InputWorkspace=in_ws,
XMin=float(min_wavelength))
# Integrate over the higher wavelengths after cropping.
summed_ws = Integration(InputWorkspace=cropped_ws)
# Loop through each histogram, and fetch out each intensity value from the single bin to generate a list of all values.
n_histograms = summed_ws.getNumberHistograms()
y_data = np.empty([n_histograms])
for i in range(0, n_histograms):
intensity = summed_ws.readY(i)[0]
y_data[i] = intensity
#Remove the background
y_data = self.__remove_background(y_data)
#Find the peaks
peak_index_list = self.__find_peak_spectrum_numbers(y_data, summed_ws)
#Reverse the order so that it goes from high spec number to low spec number
peak_index_list.reverse()
n_peaks_found = len(peak_index_list)
output_ws = WorkspaceFactory.createTable("TableWorkspace")
output_ws.addColumn("int", "Reflected Spectrum Number")
if n_peaks_found > 2:
raise PeakFindingException("Found more than two peaks.")
elif n_peaks_found == 0:
raise PeakFindingException("No peaks found")
elif n_peaks_found == 1:
output_ws.addRow(peak_index_list)
elif n_peaks_found == 2:
output_ws.addColumn("int", "Transmission Spectrum Number")
output_ws.addRow(peak_index_list)
if int(keep_workspaces) == 0:
DeleteWorkspace(Workspace=cropped_ws)
DeleteWorkspace(Workspace=summed_ws)
self.setProperty("OutputWorkspace", output_ws)
def PyExec(self):
from mantid.simpleapi import CropWorkspace, Integration, DeleteWorkspace
in_ws = self.getPropertyValue("InputWorkspace")
min_wavelength = self.getPropertyValue("StartWavelength")
keep_workspaces = self.getPropertyValue("KeepIntermediateWorkspaces")
# Crop off lower wavelengths where the signal is also lower.
cropped_ws = CropWorkspace(InputWorkspace=in_ws,XMin=float(min_wavelength))
# Integrate over the higher wavelengths after cropping.
summed_ws = Integration(InputWorkspace=cropped_ws)
# Loop through each histogram, and fetch out each intensity value from the single bin to generate a list of all values.
n_histograms = summed_ws.getNumberHistograms()
y_data = np.empty([n_histograms])
for i in range(0, n_histograms):
intensity = summed_ws.readY(i)[0]
y_data[i] = intensity
#Remove the background
y_data = self.__remove_background(y_data)
#Find the peaks
peak_index_list = self.__find_peak_spectrum_numbers(y_data, summed_ws)
#Reverse the order so that it goes from high spec number to low spec number
peak_index_list.reverse()
n_peaks_found = len(peak_index_list)
output_ws = WorkspaceFactory.createTable("TableWorkspace")
output_ws.addColumn("int", "Reflected Spectrum Number")
if n_peaks_found > 2:
raise PeakFindingException("Found more than two peaks.")
elif n_peaks_found == 0:
raise PeakFindingException("No peaks found")
elif n_peaks_found == 1:
output_ws.addRow(peak_index_list)
elif n_peaks_found == 2:
output_ws.addColumn("int", "Transmission Spectrum Number")
output_ws.addRow(peak_index_list)
if int(keep_workspaces) == 0:
DeleteWorkspace(Workspace=cropped_ws)
DeleteWorkspace(Workspace=summed_ws)
self.setProperty("OutputWorkspace", output_ws)
def _convert_to_angle(self, w):
"""
Output the integrated intensity for each elastic detector versus
detector angle with the neutron beam.
Masked elastic detectors are assigned a zero intensity
Parameters
----------
w: Mantid.MatrixWorkspace2D
Returns
-------
Mantid.MatrixWorkspace2D
"""
id_s, id_e = 16386, 17534 # start and end for elastic detector ID's
_t_w = Integration(w)
sp = _t_w.spectrumInfo()
x, y, e = [list(), list(), list()]
for i in range(_t_w.getNumberHistograms()):
id_i = _t_w.getDetector(i).getID()
if id_s <= id_i <= id_e:
x.append(np.degrees(sp.twoTheta(i)))
if sp.isMasked(i) is True:
y.append(0.0)
e.append(1.0)
else:
y.append(_t_w.readY(i)[0])
e.append(_t_w.readE(i)[0])
x = np.asarray(x)
y = np.asarray(y)
e = np.asarray(e)
od = np.argsort(x) # order in ascending angles
title = 'Angle between detector and incoming neutron beam'
_t_w = CreateWorkspace(DataX=x[od], DataY=y[od], DataE=e[od],
NSpec=1, UnitX='Degrees',
WorkspaceTitle=title)
return _t_w
