diff --git a/scripts/Diffraction/isis_powder/polaris_routines/polaris_algs.py b/scripts/Diffraction/isis_powder/polaris_routines/polaris_algs.py
index d8335acdd19a3c5724542abbb7bbd1bf0ba7e79e..c762d67e8caa426bacacc056486ff21faba4e6b8 100644
--- a/scripts/Diffraction/isis_powder/polaris_routines/polaris_algs.py
+++ b/scripts/Diffraction/isis_powder/polaris_routines/polaris_algs.py
@@ -7,7 +7,6 @@
from __future__ import (absolute_import, division, print_function)
import numpy as np
-from mantid.api import WorkspaceGroup
import mantid.simpleapi as mantid
from isis_powder.routines import absorb_corrections, common
@@ -85,98 +84,51 @@ def save_unsplined_vanadium(vanadium_ws, output_path):
def generate_ts_pdf(run_number, focus_file_path, merge_banks=False, q_lims=None, cal_file_name=None):
focused_ws = _obtain_focused_run(run_number, focus_file_path)
- pdf_output = mantid.ConvertUnits(InputWorkspace=focused_ws.name(), Target="MomentumTransfer")
+ focused_ws = mantid.ConvertUnits(InputWorkspace=focused_ws.name(), Target="MomentumTransfer")
if merge_banks:
- group_bin_min = None
- group_bin_max = None
- group_bin_width = None
- for i in range(pdf_output.getNumberOfEntries()):
- x_array = pdf_output.getItem(i).readX(0)
- bin_min = x_array[0]
- bin_max = x_array[-1]
- bin_width = (x_array[-1] - x_array[0])/x_array.size
- binning = [bin_min, bin_width, bin_max]
- if not group_bin_min:
- group_bin_min = bin_min
- group_bin_max = bin_max
- group_bin_width = bin_width
- else:
- group_bin_min = min(group_bin_min, bin_min)
- group_bin_max = min(group_bin_max, bin_max)
- group_bin_width = min(group_bin_width, bin_width)
- fit_spectra = mantid.FitIncidentSpectrum(InputWorkspace=pdf_output.getItem(i),
- BinningForFit=binning,
- BinningForCalc=binning,
- FitSpectrumWith="GaussConvCubicSpline")
- placzek_self_scattering = mantid.CalculatePlaczekSelfScattering(InputWorkspace=fit_spectra)
- cal_workspace = mantid.LoadCalFile(
- InputWorkspace=placzek_self_scattering,
- CalFileName=cal_file_name,
- Workspacename='cal_workspace',
- MakeOffsetsWorkspace=False,
- MakeMaskWorkspace=False)
- focused_correction = None
- for spec_index in range(placzek_self_scattering.getNumberHistograms()):
- if cal_workspace.dataY(spec_index)[0] == i + 1:
- if focused_correction is None:
- focused_correction = placzek_self_scattering.dataY(spec_index)
- else:
- focused_correction = np.add(focused_correction, placzek_self_scattering.dataY(spec_index))
- mantid.CreateWorkspace(DataX=placzek_self_scattering.dataX(0),
- DataY=focused_correction,
- Distribution=True,
- UnitX='MomentumTransfer',
- OutputWorkspace='focused_correction_ws')
- mantid.Rebin(InputWorkspace=pdf_output.getItem(i), OutputWorkspace='pdf_rebined', Params=binning)
- mantid.Rebin(InputWorkspace='focused_correction_ws', OutputWorkspace='focused_correction_ws', Params=binning)
- mantid.Subtract(LHSWorkspace='pdf_rebined', RHSWorkspace='focused_correction_ws', OutputWorkspace=pdf_output.getItem(i))
- binning = [group_bin_min, group_bin_width, group_bin_max]
- pdf_output = mantid.Rebin(InputWorkspace=pdf_output, Params=binning)
- pdf_output_combined = mantid.ConjoinSpectra(InputWorkspaces='pdf_output')
- mantid.MatchSpectra(InputWorkspace=pdf_output_combined, OutputWorkspace=pdf_output_combined, ReferenceSpectrum=1)
- if type(q_lims) == str:
- q_min = []
- q_max = []
- try:
- with open(q_lims, 'r') as f:
- line_list = [line.rstrip('\n') for line in f]
- for line in line_list[:-1]:
- value_list = line.split()
- q_min.append(value_list[2])
- q_max.append(value_list[3])
- except IOError:
- raise RuntimeError("q_lims is not valid")
- elif type(q_lims) == list or type(q_lims) == np.ndarray:
- q_min = q_lims[0, :]
- q_max = q_lims[1, :]
- else:
- raise RuntimeError("q_lims is not valid")
- pdf_x_array = pdf_output_combined.readX(0)
- for i in range(q_min.size):
- q_min[i] = pdf_x_array[np.amin(np.where(pdf_x_array >= q_min[i]))]
- q_max[i] = pdf_x_array[np.amax(np.where(pdf_x_array <= q_max[i]))]
- bin_width = pdf_x_array[1] - pdf_x_array[0]
- pdf_output_combined = mantid.CropWorkspaceRagged(InputWorkspace=pdf_output_combined, XMin=q_min, XMax=q_max)
- pdf_output_combined = mantid.Rebin(InputWorkspace=pdf_output_combined, Params=[min(q_min), bin_width, max(q_max)])
- pdf_output_combined = mantid.SumSpectra(InputWorkspace=pdf_output_combined, WeightedSum=True, MultiplyBySpectra=False)
- pdf_fourier_transform = mantid.PDFFourierTransform(Inputworkspace=pdf_output_combined, InputSofQType="S(Q)",
- PDFType="G(r)", Filter=True)
- return pdf_fourier_transform
-
- pdf_output = mantid.PDFFourierTransform(Inputworkspace=pdf_output, InputSofQType="S(Q)", PDFType="G(r)",
- Filter=True)
- pdf_output = mantid.RebinToWorkspace(WorkspaceToRebin=pdf_output, WorkspaceToMatch=pdf_output[4],
- PreserveEvents=True)
+ pdf_output = _generate_grouped_ts_pdf(focused_ws, q_lims, cal_file_name)
+ else:
+ pdf_output = mantid.PDFFourierTransform(Inputworkspace=focused_ws, InputSofQType="S(Q)", PDFType="G(r)",
+ Filter=True)
+ pdf_output = mantid.RebinToWorkspace(WorkspaceToRebin=pdf_output, WorkspaceToMatch=pdf_output[4],
+ PreserveEvents=True)
+ common.remove_intermediate_workspace(focused_ws)
return pdf_output
-def _generate_grouped_ts_pdf(focused_data, q_lims, cal_file_name):
+def _obtain_focused_run(run_number, focus_file_path):
+ """
+ Searches for the focused workspace to use (based on user specified run number) in the ADS and then the output
+ directory.
+ If unsuccessful, a ValueError exception is thrown.
+ :param run_number: The run number to search for.
+ :param focus_file_path: The expected file path for the focused file.
+ :return: The focused workspace.
+ """
+ # Try the ADS first to avoid undesired loading
+ if mantid.mtd.doesExist('%s-Results-TOF-Grp' % run_number):
+ focused_ws = mantid.mtd['%s-Results-TOF-Grp' % run_number]
+ elif mantid.mtd.doesExist('%s-Results-D-Grp' % run_number):
+ focused_ws = mantid.mtd['%s-Results-D-Grp' % run_number]
+ else:
+ # Check output directory
+ print('No loaded focused files found. Searching in output directory...')
+ try:
+ focused_ws = mantid.LoadNexus(Filename=focus_file_path, OutputWorkspace='focused_ws').OutputWorkspace
+ except ValueError:
+ raise ValueError("Could not find focused file for run number:%s\n"
+ "Please ensure a focused file has been produced and is located in the output directory."
+ % run_number)
+ return focused_ws
+
+
+def _generate_grouped_ts_pdf(focused_ws, q_lims, cal_file_name):
group_bin_min = None
group_bin_max = None
group_bin_width = None
- for i in range(focused_data.getNumberOfEntries()):
- x_array = focused_data.getItem(i).readX(0)
+ for i in range(focused_ws.getNumberOfEntries()):
+ x_array = focused_ws.getItem(i).readX(0)
bin_min = x_array[0]
bin_max = x_array[-1]
bin_width = (x_array[-1] - x_array[0]) / x_array.size
@@ -189,17 +141,16 @@ def _generate_grouped_ts_pdf(focused_data, q_lims, cal_file_name):
group_bin_min = min(group_bin_min, bin_min)
group_bin_max = min(group_bin_max, bin_max)
group_bin_width = min(group_bin_width, bin_width)
- fit_spectra = mantid.FitIncidentSpectrum(InputWorkspace=focused_data.getItem(i),
+ fit_spectra = mantid.FitIncidentSpectrum(InputWorkspace=focused_ws.getItem(i),
BinningForFit=binning,
BinningForCalc=binning,
FitSpectrumWith="GaussConvCubicSpline")
placzek_self_scattering = mantid.CalculatePlaczekSelfScattering(InputWorkspace=fit_spectra)
- cal_workspace = mantid.LoadCalFile(
- InputWorkspace=placzek_self_scattering,
- CalFileName=cal_file_name,
- Workspacename='cal_workspace',
- MakeOffsetsWorkspace=False,
- MakeMaskWorkspace=False)
+ cal_workspace = mantid.LoadCalFile(InputWorkspace=placzek_self_scattering,
+ CalFileName=cal_file_name,
+ Workspacename='cal_workspace',
+ MakeOffsetsWorkspace=False,
+ MakeMaskWorkspace=False)
focused_correction = None
for spec_index in range(placzek_self_scattering.getNumberHistograms()):
if cal_workspace.dataY(spec_index)[0] == i + 1:
@@ -207,19 +158,19 @@ def _generate_grouped_ts_pdf(focused_data, q_lims, cal_file_name):
focused_correction = placzek_self_scattering.dataY(spec_index)
else:
focused_correction = np.add(focused_correction, placzek_self_scattering.dataY(spec_index))
- mantid.CreateWorkspace(DataX=placzek_self_scattering.dataX(0),
- DataY=focused_correction,
- Distribution=True,
- UnitX='MomentumTransfer',
- OutputWorkspace='focused_correction_ws')
- mantid.Rebin(InputWorkspace=focused_data.getItem(i), OutputWorkspace='focused_rebined', Params=binning)
- mantid.Rebin(InputWorkspace='focused_correction_ws', OutputWorkspace='focused_correction_ws', Params=binning)
- mantid.Subtract(LHSWorkspace='focused_rebined', RHSWorkspace='focused_correction_ws',
- OutputWorkspace=focused_data.getItem(i))
+ focused_correction_ws = mantid.CreateWorkspace(DataX=placzek_self_scattering.dataX(0),
+ DataY=focused_correction,
+ Distribution=True,
+ UnitX='MomentumTransfer')
+ mantid.Rebin(InputWorkspace=focused_ws.getItem(i), OutputWorkspace=focused_ws.getItem(i), Params=binning)
+ focused_correction_ws = mantid.Rebin(InputWorkspace=focused_correction_ws, Params=binning)
+ mantid.Subtract(LHSWorkspace=focused_ws.getItem(i),
+ RHSWorkspace=focused_correction_ws,
+ OutputWorkspace=focused_ws.getItem(i))
binning = [group_bin_min, group_bin_width, group_bin_max]
- focused_data = mantid.Rebin(InputWorkspace=focused_data, Params=binning)
- pdf_output_combined = mantid.ConjoinSpectra(InputWorkspaces=focused_data)
- mantid.MatchSpectra(InputWorkspace=pdf_output_combined, OutputWorkspace=pdf_output_combined, ReferenceSpectrum=1)
+ focused_data = mantid.Rebin(InputWorkspace=focused_ws, Params=binning)
+ focused_data_combined = mantid.ConjoinSpectra(InputWorkspaces=focused_data)
+ mantid.MatchSpectra(InputWorkspace=focused_data_combined, OutputWorkspace=focused_data_combined, ReferenceSpectrum=1)
if type(q_lims) == str:
q_min = []
q_max = []
@@ -237,44 +188,28 @@ def _generate_grouped_ts_pdf(focused_data, q_lims, cal_file_name):
q_max = q_lims[1, :]
else:
raise RuntimeError("q_lims is not valid")
- pdf_x_array = pdf_output_combined.readX(0)
+ pdf_x_array = focused_data_combined.readX(0)
for i in range(q_min.size):
q_min[i] = pdf_x_array[np.amin(np.where(pdf_x_array >= q_min[i]))]
q_max[i] = pdf_x_array[np.amax(np.where(pdf_x_array <= q_max[i]))]
bin_width = pdf_x_array[1] - pdf_x_array[0]
- focused_data_combined = mantid.CropWorkspaceRagged(InputWorkspace=pdf_output_combined, XMin=q_min, XMax=q_max)
- focused_data_combined = mantid.Rebin(InputWorkspace=pdf_output_combined, Params=[min(q_min), bin_width, max(q_max)])
- focused_data_combined = mantid.SumSpectra(InputWorkspace=pdf_output_combined, WeightedSum=True,
- MultiplyBySpectra=False)
- pdf_output = mantid.PDFFourierTransform(Inputworkspace=pdf_output_combined, InputSofQType="S(Q)",
- PDFType="G(r)", Filter=True)
- return pdf_output
-
+ focused_data_combined = mantid.CropWorkspaceRagged(InputWorkspace=focused_data_combined, XMin=q_min, XMax=q_max)
+ focused_data_combined = mantid.Rebin(InputWorkspace=focused_data_combined,
+ Params=[min(q_min), bin_width, max(q_max)])
+ focused_data_combined = mantid.SumSpectra(InputWorkspace=focused_data_combined,
+ WeightedSum=True,
+ MultiplyBySpectra=False)
+ pdf_output = mantid.PDFFourierTransform(Inputworkspace=focused_data_combined,
+ InputSofQType="S(Q)",
+ PDFType="G(r)",
+ Filter=True)
-def _obtain_focused_run(run_number, focus_file_path):
- """
- Searches for the focused workspace to use (based on user specified run number) in the ADS and then the output
- directory.
- If unsuccessful, a ValueError exception is thrown.
- :param run_number: The run number to search for.
- :param focus_file_path: The expected file path for the focused file.
- :return: The focused workspace.
- """
- # Try the ADS first to avoid undesired loading
- if mantid.mtd.doesExist('%s-Results-TOF-Grp' % run_number):
- focused_ws = mantid.mtd['%s-Results-TOF-Grp' % run_number]
- elif mantid.mtd.doesExist('%s-Results-D-Grp' % run_number):
- focused_ws = mantid.mtd['%s-Results-D-Grp' % run_number]
- else:
- # Check output directory
- print('No loaded focused files found. Searching in output directory...')
- try:
- focused_ws = mantid.LoadNexus(Filename=focus_file_path, OutputWorkspace='focused_ws').OutputWorkspace
- except ValueError:
- raise ValueError("Could not find focused file for run number:%s\n"
- "Please ensure a focused file has been produced and is located in the output directory."
- % run_number)
- return focused_ws
+ common.remove_intermediate_workspace(cal_workspace)
+ common.remove_intermediate_workspace(fit_spectra)
+ common.remove_intermediate_workspace(focused_correction_ws)
+ common.remove_intermediate_workspace(focused_data)
+ common.remove_intermediate_workspace(placzek_self_scattering)
+ return pdf_output
def _determine_chopper_mode(ws):