# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
import numpy as np
import math
import mantid.simpleapi as mantid
from mantid.api import WorkspaceGroup
from isis_powder.routines import absorb_corrections, common
from isis_powder.routines.common_enums import WORKSPACE_UNITS
from isis_powder.routines.run_details import create_run_details_object, get_cal_mapping_dict
from isis_powder.polaris_routines import polaris_advanced_config
def calculate_van_absorb_corrections(ws_to_correct, multiple_scattering, is_vanadium):
mantid.MaskDetectors(ws_to_correct, SpectraList=list(range(1, 55)))
absorb_dict = polaris_advanced_config.absorption_correction_params
sample_details_obj = absorb_corrections.create_vanadium_sample_details_obj(config_dict=absorb_dict)
ws_to_correct = absorb_corrections.run_cylinder_absorb_corrections(
ws_to_correct=ws_to_correct, multiple_scattering=multiple_scattering, sample_details_obj=sample_details_obj,
is_vanadium=is_vanadium)
return ws_to_correct
def _get_run_numbers_for_key(current_mode_run_numbers, key):
err_message = "this must be under the relevant Rietveld or PDF mode."
return common.cal_map_dictionary_key_helper(current_mode_run_numbers, key=key,
append_to_error_message=err_message)
def _get_current_mode_dictionary(run_number_string, inst_settings):
mapping_dict = get_cal_mapping_dict(run_number_string, inst_settings.cal_mapping_path)
if inst_settings.mode is None:
ws = mantid.Load('POLARIS'+run_number_string+'.nxs')
mode, cropping_vals = _determine_chopper_mode(ws)
inst_settings.mode = mode
inst_settings.focused_cropping_values = cropping_vals
mantid.DeleteWorkspace(ws)
# Get the current mode "Rietveld" or "PDF" run numbers
return common.cal_map_dictionary_key_helper(mapping_dict, inst_settings.mode)
def get_run_details(run_number_string, inst_settings, is_vanadium_run):
mode_run_numbers = _get_current_mode_dictionary(run_number_string, inst_settings)
# Get empty and vanadium
err_message = "this must be under the relevant Rietveld or PDF mode."
empty_runs = common.cal_map_dictionary_key_helper(mode_run_numbers,
key="empty_run_numbers", append_to_error_message=err_message)
vanadium_runs = common.cal_map_dictionary_key_helper(mode_run_numbers, key="vanadium_run_numbers",
append_to_error_message=err_message)
grouping_file_name = inst_settings.grouping_file_name
return create_run_details_object(run_number_string=run_number_string, inst_settings=inst_settings,
is_vanadium_run=is_vanadium_run, empty_run_number=empty_runs,
vanadium_string=vanadium_runs, grouping_file_name=grouping_file_name)
def save_unsplined_vanadium(vanadium_ws, output_path):
converted_workspaces = []
for ws_index in range(vanadium_ws.getNumberOfEntries()):
ws = vanadium_ws.getItem(ws_index)
previous_units = ws.getAxis(0).getUnit().unitID()
if previous_units != WORKSPACE_UNITS.tof:
ws = mantid.ConvertUnits(InputWorkspace=ws, Target=WORKSPACE_UNITS.tof)
ws = mantid.RenameWorkspace(InputWorkspace=ws, OutputWorkspace="van_bank_{}".format(ws_index + 1))
converted_workspaces.append(ws)
converted_group = mantid.GroupWorkspaces(",".join(ws.name() for ws in converted_workspaces))
mantid.SaveNexus(InputWorkspace=converted_group, Filename=output_path, Append=False)
mantid.DeleteWorkspace(converted_group)
def generate_ts_pdf(run_number, focus_file_path, merge_banks=False, q_lims=None, cal_file_name=None,
sample_details=None, delta_r=None, delta_q=None, pdf_type="G(r)", freq_params=None):
focused_ws = _obtain_focused_run(run_number, focus_file_path)
focused_ws = mantid.ConvertUnits(InputWorkspace=focused_ws, Target="MomentumTransfer", EMode='Elastic')
raw_ws = mantid.Load(Filename='POLARIS'+str(run_number)+'.nxs')
sample_geometry = common.generate_sample_geometry(sample_details)
sample_material = common.generate_sample_material(sample_details)
self_scattering_correction = mantid.TotScatCalculateSelfScattering(InputWorkspace=raw_ws,
CalFileName=cal_file_name,
SampleGeometry=sample_geometry,
SampleMaterial=sample_material)
ws_group_list = []
for i in range(self_scattering_correction.getNumberHistograms()):
ws_name = 'correction_' + str(i)
mantid.ExtractSpectra(InputWorkspace=self_scattering_correction, OutputWorkspace=ws_name,
WorkspaceIndexList=[i])
ws_group_list.append(ws_name)
self_scattering_correction = mantid.GroupWorkspaces(InputWorkspaces=ws_group_list)
self_scattering_correction = mantid.RebinToWorkspace(WorkspaceToRebin=self_scattering_correction,
WorkspaceToMatch=focused_ws)
focused_ws = mantid.Subtract(LHSWorkspace=focused_ws, RHSWorkspace=self_scattering_correction)
if delta_q:
focused_ws = mantid.Rebin(InputWorkspace=focused_ws, Params=delta_q)
if merge_banks:
q_min, q_max = _load_qlims(q_lims)
merged_ws = mantid.MatchAndMergeWorkspaces(InputWorkspaces=focused_ws, XMin=q_min, XMax=q_max,
CalculateScale=False)
fast_fourier_filter(merged_ws, freq_params)
pdf_output = mantid.PDFFourierTransform(Inputworkspace="merged_ws", InputSofQType="S(Q)-1", PDFType=pdf_type,
Filter=True, DeltaR=delta_r)
else:
for ws in focused_ws:
fast_fourier_filter(ws, freq_params)
pdf_output = mantid.PDFFourierTransform(Inputworkspace='focused_ws', InputSofQType="S(Q)-1", PDFType=pdf_type,
Filter=True, DeltaR=delta_r)
pdf_output = mantid.RebinToWorkspace(WorkspaceToRebin=pdf_output, WorkspaceToMatch=pdf_output[4],
PreserveEvents=True)
common.remove_intermediate_workspace('self_scattering_correction')
# Rename output ws
if 'merged_ws' in locals():
mantid.RenameWorkspace(InputWorkspace=merged_ws, OutputWorkspace=run_number + '_merged_Q')
mantid.RenameWorkspace(InputWorkspace='focused_ws', OutputWorkspace=run_number+'_focused_Q')
if isinstance(focused_ws, WorkspaceGroup):
for i in range(len(focused_ws)):
mantid.RenameWorkspace(InputWorkspace=focused_ws[i], OutputWorkspace=run_number+'_focused_Q_'+str(i+1))
mantid.RenameWorkspace(InputWorkspace='pdf_output', OutputWorkspace=run_number+'_pdf_R')
if isinstance(pdf_output, WorkspaceGroup):
for i in range(len(pdf_output)):
mantid.RenameWorkspace(InputWorkspace=pdf_output[i], OutputWorkspace=run_number+'_pdf_R_'+str(i+1))
return pdf_output
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 _load_qlims(q_lims):
if isinstance(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(float(value_list[2]))
q_max.append(float(value_list[3]))
q_min = np.array(q_min)
q_max = np.array(q_max)
except IOError as exc:
raise RuntimeError("q_lims path is not valid: {}".format(exc))
elif isinstance(q_lims, (list, tuple)) or isinstance(q_lims, np.ndarray):
q_min = q_lims[0]
q_max = q_lims[1]
else:
raise RuntimeError("q_lims type is not valid. Expected a string filename or an array.")
return q_min, q_max
def _determine_chopper_mode(ws):
if ws.getRun().hasProperty('Frequency'):
frequency = ws.getRun()['Frequency'].timeAverageValue()
print("Found chopper frequency of {} in log file.".format(frequency))
if math.isclose(frequency, 50, abs_tol=1):
print("Automatically chose Rietveld mode")
return 'Rietveld', polaris_advanced_config.rietveld_focused_cropping_values
if math.isclose(frequency, 0, abs_tol=1):
print("Automatically chose PDF mode")
return 'PDF', polaris_advanced_config.pdf_focused_cropping_values
else:
raise ValueError("Chopper frequency not in log data. Please specify a chopper mode")
def fast_fourier_filter(ws, freq_params=None):
if not freq_params:
return
# This is a simple fourier filter using the FFTSmooth to get a WS with only the low radius components, then
# subtracting that from the merged WS
x_range = ws.dataX(0)
# The param p in FFTSmooth defined such that if the input ws has Nx bins then in the fourier space ws it will cut of
# all frequencies in bins nk=Nk/p and above, calculated by p = pi/(k_c*dQ) when k_c is the cutoff frequency desired.
# The input ws of FFTSmooth has binning [x_min, dx, x_max], with Nx bins.
# FFTSmooth doubles the length of the input ws and preforms an FFT with output ws binning
# [0, dk, k_max]=[0, 1/2*(x_max-x_min), 1/(2*dx)], and Nk=Nx bins.
# k_max/k_c = Nk/nk
# 1/(k_c*2*dx) = p
# because FFT uses sin(2*pi*k*x) while PDFFourierTransform uses sin(Q*r) we need to include a factor of 2*pi
# p = pi/(k_c*dQ)
lower_freq_param = round(np.pi / (freq_params[0] * (x_range[1] - x_range[0])))
# This is giving the FFTSmooth the data in the form of S(Q)-1, later we use PDFFourierTransform with Q(S(Q)-1)
# it does not matter which we use in this case.
tmp = mantid.FFTSmooth(InputWorkspace=ws, Filter="Zeroing", Params=str(lower_freq_param), StoreInADS=False,
IgnoreXBins=True)
mantid.Minus(LHSWorkspace=ws, RHSWorkspace=tmp, OutputWorkspace=ws)
if len(freq_params) > 1:
upper_freq_param = round(np.pi / (freq_params[1] * (x_range[1] - x_range[0])))
mantid.FFTSmooth(InputWorkspace=ws, OutputWorkspace=ws, Filter="Zeroing",
Params=str(upper_freq_param), IgnoreXBins=True)