def _run_number_changed(self):
""" Handling event if run number is changed... If it is a valid run number,
the load the meta data
"""
from datetime import datetime
# 1. Form the file
newrunnumberstr = self._content.run_number_edit.text()
instrument = self._instrument_name
eventnxsname = "%s_%s_event.nxs" % (instrument, newrunnumberstr)
msg = str("Load event nexus file %s" % (eventnxsname))
self._content.info_text_browser.setText(msg)
# 2. Load file
metawsname = "%s_%s_meta" % (instrument, newrunnumberstr)
try:
metaws = api.Load(Filename=str(eventnxsname),
OutputWorkspace=str(metawsname),
MetaDataOnly=True)
except ValueError:
metaws = None
# 3. Update the log name combo box
if metaws is None:
self._content.info_text_browser.setText(\
str("Error! Failed to load data file %s. Current working directory is %s. " % (eventnxsname, os.getcwd())))
else:
self._metaws = metaws
# a) Clear
self._content.log_name_combo.clear()
# b) Get properties
wsrun = metaws.getRun()
ps = wsrun.getProperties()
properties = []
for p in ps:
if p.__class__.__name__ == "FloatTimeSeriesProperty":
if p.size() > 1:
properties.append(p.name)
print p.name, p.size()
# ENDFOR p
properties = sorted(properties)
# c) Add
for p in properties:
self._content.log_name_combo.addItem(p)
# ENDIFELSE
"""
now = datetime.now()
print "New Run Number = %s. @ %s" % (newrunnumberstr, str(now))
if newrunnumberstr == "":
self._content.log_name_combo.clear()
else:
self._content.log_name_combo.addItem(newrunnumberstr)
"""
return
def load_van_curves_file(curves_van):
"""
load the vanadium curves file passed in
@param curves_van:: the path to the integrated vanadium file
"""
van_curves_ws = simple.Load(curves_van, OutputWorkspace="curves_van")
return van_curves_ws
def load_L2_from_nxs(path):
"load L2 computed using mantid and saved as nxs"
from mantid import simpleapi as msa
L2_calib = msa.Load(path)
L2_calib = msa.SortTableWorkspace(L2_calib, Columns='detid')
L2 = np.array(L2_calib.column('L2'))
L2_detID = np.array(L2_calib.column('detid'))
nodata = np.array(L2_calib.column('nodata'), dtype=bool)
return L2
def load_van_integration_file(ints_van):
"""
load the vanadium integration file passed in
@param ints_van:: the path to the integrated vanadium file
"""
van_integrated_ws = simple.Load(ints_van, OutputWorkspace="int_van")
return van_integrated_ws
def create_calibration_cropped_file(ceria_run, van_run, curve_van, int_van, calibration_directory, calibration_general,
use_spectrum_number, crop_name, spec_nos):
"""
create and save a cropped calibration file
@param ceria_run :: run number for the ceria used
@param van_run :: the run number of the vanadium to use
@param curve_van :: name of the vanadium curves workspace
@param int_van :: name of the integrated vanadium workspace
@param calibration_directory :: the user specific calibration directory to save to
@param calibration_general :: the general calibration dirrecory
@param use_spectrum_number :: whether or not to crop using spectrum numbers or banks
@param crop_name :: name of the output workspace
@param spec_nos :: the value to crop on, either a spectra number, or a bank
"""
van_curves_ws, van_integrated_ws = load_van_files(curve_van, int_van)
ceria_ws = simple.Load(Filename="ENGINX" + ceria_run, OutputWorkspace="eng_calib")
# check which cropping method to use
if use_spectrum_number:
param_tbl_name = crop_name if crop_name is not None else "cropped"
# run the calibration cropping on spectrum number
output = simple.EnggCalibrate(InputWorkspace=ceria_ws, VanIntegrationWorkspace=van_integrated_ws,
VanCurvesWorkspace=van_curves_ws, SpectrumNumbers=str(spec_nos),
FittedPeaks=param_tbl_name,
OutputParametersTableName=param_tbl_name)
# get the values needed for saving out the .prm files
difc = [output.DIFC]
tzero = [output.TZERO]
difa = [output.DIFA]
save_calibration(ceria_run, van_run, calibration_directory, calibration_general, "all_banks", [param_tbl_name],
tzero, difc, difa)
save_calibration(ceria_run, van_run, calibration_directory, calibration_general,
"bank_{}".format(param_tbl_name), [param_tbl_name], tzero, difc, difa)
else:
# work out which bank number to crop on, then calibrate
if spec_nos.lower() == "north":
param_tbl_name = "engg_calibration_bank_1"
bank = 1
else:
param_tbl_name = "engg_calibration_bank_2"
bank = 2
output = simple.EnggCalibrate(InputWorkspace=ceria_ws, VanIntegrationWorkspace=van_integrated_ws,
VanCurvesWorkspace=van_curves_ws, Bank=str(bank), FittedPeaks=param_tbl_name,
OutputParametersTableName=param_tbl_name)
# get the values needed for saving out the .prm files
difc = [output.DIFC]
tzero = [output.TZERO]
difa = [output.DIFA]
save_calibration(ceria_run, van_run, calibration_directory, calibration_general, "all_banks", [spec_nos], tzero,
difc, difa)
save_calibration(ceria_run, van_run, calibration_directory, calibration_general, "bank_{}".format(spec_nos),
[spec_nos], tzero, difc, difa)
# create the table workspace containing the parameters
create_params_table(difc, tzero, difa)
create_difc_zero_workspace(difc, tzero, spec_nos, param_tbl_name)
def _loadFile(self, filename):
""" Load file or run
File will be loaded to a workspace shown in MantidPlot
"""
config = ConfigService
# Check input file name and output workspace name
if filename.isdigit() is True:
# Construct a file name from run number
runnumber = int(filename)
if runnumber <= 0:
error_msg = "Run number cannot be less or equal to zero. User gives %s. " % (
filename)
Logger("Filter_Events").error(error_msg)
return None
else:
ishort = config.getInstrument(self._instrument).shortName()
filename = "%s_%s" % (ishort, filename)
wsname = filename + "_event"
elif filename.count(".") > 0:
# A proper file name
wsname = os.path.splitext(os.path.split(filename)[1])[0]
elif filename.count("_") == 1:
# A short one as instrument_runnumber
iname = filename.split("_")[0]
str_runnumber = filename.split("_")[1]
if str_runnumber.isdigit() is True and int(str_runnumber) > 0:
# Acccepted format
ishort = config.getInstrument(iname).shortName()
wsname = "%s_%s_event" % (ishort, str_runnumber)
else:
# Non-supported
error_msg = "File name / run number in such format %s is not supported. " % (
filename)
Logger("Filter_Events").error(error_msg)
return None
else:
# Unsupported format
error_msg = "File name / run number in such format %s is not supported. " % (
filename)
Logger("Filter_Events").error(error_msg)
return None
# Load
try:
ws = api.Load(Filename=filename, OutputWorkspace=wsname)
except RuntimeError as e:
ws = None
return str(e)
return ws
def _compare_ws(reference_file_name, results):
ref_ws = mantid.Load(Filename=reference_file_name)
is_valid = len(results) > 0
for (ws, ref) in zip(results, ref_ws):
if not mantid.CompareWorkspaces(Workspace1=ws, Workspace2=ref):
is_valid = False
print("{} was not equal to {}".format(ws.getName(), ref.getName()))
return is_valid
def run_vanadium_calibration():
vanadium_run = 98532 # Choose arbitrary run in the cycle 17_1
pdf_inst_obj = setup_inst_object(mode="PDF")
# Run create vanadium twice to ensure we get two different output splines / files
pdf_inst_obj.create_vanadium(first_cycle_run_no=vanadium_run,
do_absorb_corrections=True,
multiple_scattering=False)
# Check the spline looks good and was saved
if not os.path.exists(spline_path):
raise RuntimeError(
"Could not find output spline at the following path: " +
spline_path)
splined_ws = mantid.Load(Filename=spline_path)
unsplined_ws = mantid.Load(Filename=unsplined_van_path)
return splined_ws, unsplined_ws
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 CalibrateWish(RunNumber, PanelNumber):
'''
:param RunNumber: is the run number of the calibration.
:param PanelNumber: is a string of two-digit number of the panel being calibrated
'''
# == Set parameters for calibration ==
previousDefaultInstrument = mantid.config['default.instrument']
mantid.config['default.instrument'] = "WISH"
filename = str(RunNumber)
CalibratedComponent = 'WISH/panel' + PanelNumber
# Get calibration raw file and integrate it
print("Loading", filename)
rawCalibInstWS = mantid.Load(filename) # 'raw' in 'rawCalibInstWS' means unintegrated.
CalibInstWS = mantid.Integration(rawCalibInstWS, RangeLower=1, RangeUpper=20000)
mantid.DeleteWorkspace(rawCalibInstWS)
print("Created workspace (CalibInstWS) with integrated data from run and instrument to calibrate")
# Give y-positions of slit points (gotten for converting first tube's slit point to Y)
# WISH instrument has a particularity. It is composed by a group of upper tubes and lower tubes,
# they are disposed 3 milimiters in difference one among the other
lower_tube = numpy.array([-0.41, -0.31, -0.21, -0.11, -0.02, 0.09, 0.18, 0.28, 0.39])
upper_tube = numpy.array(lower_tube + 0.003)
funcForm = 9 * [1] # 9 gaussian peaks
print("Created objects needed for calibration.")
# Get the calibration and put it into the calibration table
# calibrate the lower tubes
calibrationTable, peakTable = tube.calibrate(CalibInstWS, CalibratedComponent, lower_tube, funcForm,
rangeList=list(range(0, 76)), outputPeak=True)
# calibrate the upper tubes
calibrationTable, peakTable = tube.calibrate(CalibInstWS, CalibratedComponent, upper_tube, funcForm,
rangeList=list(range(76, 152)),
calibTable=calibrationTable,
# give the calibration table to append data
outputPeak=peakTable # give peak table to append data
)
print("Got calibration (new positions of detectors)")
# Apply the calibration
mantid.ApplyCalibration(Workspace=CalibInstWS, PositionTable=calibrationTable)
print("Applied calibration")
# == Save workspace ==
# uncomment these lines to save the workspace
# nexusName = "TubeCalibDemoWish" + PanelNumber + "Result.nxs"
# mantid.SaveNexusProcessed(CalibInstWS, 'TubeCalibDemoWishResult.nxs', "Result of Running TubeCalibWishMerlin_Simple.py")
# print("saved calibrated workspace (CalibInstWS) into Nexus file", nexusName)
# == Reset dafault instrument ==
mantid.config['default.instrument'] = previousDefaultInstrument
def _compare_ws(reference_file_name, results):
ref_ws = mantid.Load(Filename=reference_file_name)
is_valid = True if len(results) > 0 else False
for ws, ref in zip(results, ref_ws):
if not (mantid.CompareWorkspaces(Workspace1=ws, Workspace2=ref)):
is_valid = False
print(ws.getName() + " was not equal to: " + ref.getName())
return is_valid
def load_L2_from_nxs(self, path):
"load L2 computed using mantid and saved as nxs"
L2_calib = msa.Load(path)
L2_calib = msa.SortTableWorkspace(L2_calib, Columns='detid')
L2 = np.array(L2_calib.column('L2'))
L2_detID = np.array(L2_calib.column('detid'))
assert np.all(self.detIDs == L2_detID)
nodata = np.array(L2_calib.column('nodata'), dtype=bool)
self.L2 = L2
self.L2_mask = nodata
return L2, nodata
def get_solid_angle_corrections(self, vanadium, run_details):
if not self._inst_settings.do_solid_angle:
return
name = "sac" + common.generate_splined_name(vanadium, [])
path = run_details.van_paths
try:
solid_angle = mantid.Load(Filename=os.path.join(path,name))
return solid_angle
except ValueError:
raise RuntimeError("Could not find " + os.path.join(path, name)+" please run create_vanadium with "
"\"do_solid_angle_corrections=True\"")
def loadingStep(filename):
filename = str(filename)
rangeLower = 2000 # Integrate counts in each spectra from rangeLower to rangeUpper
rangeUpper = 10000 #
# Get calibration raw file and integrate it
rawCalibInstWS = mantid.Load(filename) # 'raw' in 'rawCalibInstWS' means unintegrated.
print("Integrating Workspace")
CalibInstWS = mantid.Integration(rawCalibInstWS, RangeLower=rangeLower, RangeUpper=rangeUpper)
mantid.DeleteWorkspace(rawCalibInstWS)
print("Created workspace (CalibInstWS) with integrated data from run and instrument to calibrate")
return CalibInstWS
def setUp(self):
mantid.Load(Filename=self.INPUT_FILE_NAME,
OutputWorkspace=self.INPUT_WS_NAME)
run_algorithm(self.ALG_NAME,
InputWorkspace=self.INPUT_WS_NAME,
GSASParamFile=self.GSAS_PARAM_FILE,
OutputFilename=self.OUTPUT_FILE_NAME,
GroupingScheme=[1, 1, 2, 3])
with open(self.OUTPUT_FILE_NAME) as output_file:
self.file_contents = output_file.read().split("\n")
mantid.mtd.remove(self.INPUT_WS_NAME)
os.remove(self.OUTPUT_FILE_NAME)
def _load(self, run_numbers, data_name):
"""
Load data and monitors for run numbers and monitors.
Algorithm 'Load' can aggregate many runs into a single workspace, but it is not able to do so
with the monitor workspaces.
:param run_numbers: run numbers for data event files
:param data_name: output name for data workspace. The name for the workspace holding the
monitor data will be data_name+'_monitors'
:return: None
"""
# Find out the files for each run
load_algorithm = api.AlgorithmManager.createUnmanaged("Load")
load_algorithm.initialize()
load_algorithm.setPropertyValue('Filename', str(run_numbers))
files = (load_algorithm.getProperty('Filename').value)[0]
if not isinstance(files, list):
# run_numbers represents one file only
sapi.Load(Filename=files,
LoadMonitors=True,
OutputWorkspace=data_name)
else:
sapi.Load(Filename=files[0],
LoadMonitors=True,
OutputWorkspace=data_name)
monitor_name = data_name + '_monitors'
for file in files[1:]:
sapi.Load(Filename=file,
LoadMonitors=True,
OutputWorkspace=data_name + '_tmp')
sapi.Plus(LHSWorkspace=data_name,
RHSWorkspace=data_name + '_tmp',
OutputWorkspace=data_name)
sapi.Plus(LHSWorkspace=monitor_name,
RHSWorkspace=data_name + '_tmp_monitors',
OutputWorkspace=monitor_name)
sapi.DeleteWorkspace(data_name + '_tmp')
if sapi.mtd[data_name].getInstrument().getName() not in ('ARCS'):
raise NotImplementedError(
"This algorithm works only for ARCS instrument")
def do_reduction(calibration):
# load data
data = ms.Load("HRP39180.RAW")
# copy parameters from calibration to data
ms.CopyInstrumentParameters(calibration, data)
# Now move component on data workspace using a relative move, where that component was a detector in the calibrated workspace
ms.MoveInstrumentComponent(data,
DetectorID=1100,
X=0.0,
Y=0.0,
Z=5.0,
RelativePosition=True)
return data.getDetector(0).getPos()
def run_vanadium_calibration():
vanadium_run = 66031 # Choose arbitrary run from cycle 16_5
inst_obj = setup_inst_object()
inst_obj.create_vanadium(first_cycle_run_no=vanadium_run,
do_absorb_corrections=True,
multiple_scattering=False,
window="10-110")
# Check the spline looks good and was saved
if not os.path.exists(spline_path):
raise RuntimeError("Could not find output spline at the following path: {}".format(spline_path))
splined_ws = mantid.Load(Filename=spline_path)
return splined_ws
def get_fitting_neutron_data(fname, prob):
"""
Load the X-Y-E data from a file and put the values into a fitting problem
definition object.
@param fname :: file name to load (using mantid loaders)
@param prob :: problem definition to populate with X-Y-E data.
"""
import mantid.simpleapi as msapi
wks = msapi.Load(fname)
prob.data_pattern_in = wks.readX(0)
prob.data_pattern_out = wks.readY(0)
prob.data_pattern_obs_errors = wks.readE(0)
prob.ref_residual_sum_sq = 0
def apply_vanadium_absorb_corrections(van_ws, run_details, absorb_ws=None):
def generate_det_id_list(ws):
det_id_list = []
for i in range(0, ws.getNumberHistograms()):
try:
det_ids = ws.getSpectrum(i).getDetectorIDs()
except RuntimeError:
pass
else:
for det_id in det_ids:
det_id_list.append(det_id)
return det_id_list
if absorb_ws is None:
absorb_ws = mantid.Load(Filename=run_details.vanadium_absorption_path)
van_original_units = van_ws.getAxis(0).getUnit().unitID()
absorb_units = absorb_ws.getAxis(0).getUnit().unitID()
if van_original_units != absorb_units:
van_ws = mantid.ConvertUnits(InputWorkspace=van_ws, Target=absorb_units, OutputWorkspace=van_ws)
# PEARL sometimes do special runs with different detector cards so extract common spectra before doing
# RebinToWorkspace to ensure histogram by histogram by rebin
abs_det_id_list = generate_det_id_list(absorb_ws)
van_det_id_list = generate_det_id_list(van_ws)
common_det_ids = [det_id for det_id in abs_det_id_list if det_id in van_det_id_list]
if not common_det_ids:
raise RuntimeError("No common detectors in Vanadium and sample workspaces")
MSG_STEM = "Vanadium workspace and absorption workspaces have different spectra. "
if common_det_ids != van_det_id_list:
logger.warning(MSG_STEM + "Removing unmatched spectra from the Vanadium workspace")
van_ws = mantid.ExtractSpectra(InputWorkspace=van_ws, DetectorList=common_det_ids)
if common_det_ids != abs_det_id_list:
logger.warning(MSG_STEM + "Removing unmatched spectra from the absorption workspace")
absorb_ws = mantid.ExtractSpectra(InputWorkspace=absorb_ws, DetectorList=common_det_ids)
absorb_ws = mantid.RebinToWorkspace(WorkspaceToRebin=absorb_ws, WorkspaceToMatch=van_ws, OutputWorkspace=absorb_ws)
van_ws = mantid.Divide(LHSWorkspace=van_ws, RHSWorkspace=absorb_ws, OutputWorkspace=van_ws, AllowDifferentNumberSpectra=True)
if van_original_units != absorb_units:
van_ws = mantid.ConvertUnits(InputWorkspace=van_ws, Target=van_original_units, OutputWorkspace=van_ws)
common.remove_intermediate_workspace(absorb_ws)
return van_ws
def _load_run_and_convert_to_dSpacing(filepath, instrument, full_calib):
runno = path_handling.get_run_number_from_path(filepath, instrument)
ws = mantid.Load(Filename=filepath, OutputWorkspace=str(runno))
if ws.getRun().getProtonCharge() > 0:
ws = mantid.NormaliseByCurrent(InputWorkspace=ws,
OutputWorkspace=ws.name())
else:
logger.warning(f"Run {ws.name()} has invalid proton charge.")
mantid.DeleteWorkspace(ws)
return None
mantid.ApplyDiffCal(InstrumentWorkspace=ws,
CalibrationWorkspace=full_calib)
ws = mantid.ConvertUnits(InputWorkspace=ws,
OutputWorkspace=ws.name(),
Target='dSpacing')
return ws
def apply_vanadium_absorb_corrections(van_ws, run_details):
absorb_ws = mantid.Load(Filename=run_details.vanadium_absorption_path)
van_original_units = van_ws.getAxis(0).getUnit().unitID()
absorb_units = absorb_ws.getAxis(0).getUnit().unitID()
if van_original_units != absorb_units:
van_ws = mantid.ConvertUnits(InputWorkspace=van_ws, Target=absorb_units, OutputWorkspace=van_ws)
van_ws = mantid.RebinToWorkspace(WorkspaceToRebin=van_ws, WorkspaceToMatch=absorb_ws, OutputWorkspace=van_ws)
van_ws = mantid.Divide(LHSWorkspace=van_ws, RHSWorkspace=absorb_ws, OutputWorkspace=van_ws)
if van_original_units != absorb_units:
van_ws = mantid.ConvertUnits(InputWorkspace=van_ws, Target=van_original_units, OutputWorkspace=van_ws)
common.remove_intermediate_workspace(absorb_ws)
return van_ws
def create_calibration_files(ceria_run, van_run, curve_van, int_van,
calibration_directory, calibration_general):
"""
create the calibration files for an uncropped run
@param ceria_run :: the run number of the ceria
@param van_run :: the run number of the vanadium
@param curve_van :: the vanadium curves workspace
@param int_van :: the integrated vanadium workspace
@param calibration_directory :: the user specific calibration directory to save to
@param calibration_general :: the general calibration directory
"""
van_curves_ws, van_integrated_ws = load_van_files(curve_van, int_van)
ceria_ws = simple.Load(Filename="ENGINX" + ceria_run,
OutputWorkspace="eng_calib")
difcs = []
tzeros = []
difa = []
banks = 3
bank_names = ["North", "South"]
# loop through the banks, calibrating both
for i in range(1, banks):
param_tbl_name = "engg_calibration_bank_{}".format(i)
output = simple.EnggCalibrate(
InputWorkspace=ceria_ws,
VanIntegrationWorkspace=van_integrated_ws,
VanCurvesWorkspace=van_curves_ws,
Bank=str(i),
FittedPeaks=param_tbl_name,
OutputParametersTableName=param_tbl_name)
# add the needed outputs to a list
difcs.append(output.DIFC)
tzeros.append(output.TZERO)
difa.append(output.DIFA)
# save out the ones needed for this loop
save_calibration(ceria_run, van_run, calibration_directory,
calibration_general,
"bank_{}".format(bank_names[i - 1]),
[bank_names[i - 1]], [tzeros[i - 1]], [difcs[i - 1]])
# save out the total version, then create the table of params
save_calibration(ceria_run, van_run, calibration_directory,
calibration_general, "all_banks", bank_names, tzeros,
difcs)
create_params_table(difcs, tzeros, difa)
create_difc_zero_workspace(difcs, tzeros, "", None)
def __init__(self, data_file, workspace_name=None):
self.errors = []
if HAS_MANTID:
try:
if workspace_name is None:
self.data_ws = "__raw_data_file"
else:
self.data_ws = str(workspace_name)
try:
api.LoadEventNexus(Filename=data_file, OutputWorkspace=workspace_name)
except:
self.errors.append("Error loading data file as Nexus event file:\n%s" % sys.exc_info()[1])
api.Load(Filename=data_file, OutputWorkspace=workspace_name)
self.errors = []
except:
self.data_ws = None
self.errors.append("Error loading data file:\n%s" % sys.exc_info()[1])
def populate_Ei_data(sim_out, nxs):
import ast, os
props = ast.literal_eval(open(os.path.join(sim_out, 'props.json')).read())
Ei, unit = props['average energy'].split(); assert unit=='meV'
t0, unit = props['emission time'].split(); assert unit=='microsecond'
setEnergyRequest(nxs, float(Ei))
from mantid import simpleapi as msa
if sys.version_info<(3,0) and isinstance(nxs, unicode):
nxs = nxs.encode('utf-8')
ws = msa.Load(nxs)
msa.AddSampleLog(ws, LogName='mcvine-Ei', LogText=str(Ei), LogType='Number')
msa.AddSampleLog(ws, LogName='mcvine-t0', LogText=str(t0), LogType='Number')
(fd, filename) = tempfile.mkstemp(); os.close(fd)
msa.SaveNexus(ws, filename)
from ...ARCS.applications.nxs import mv
mv(filename, nxs)
return
def run_vanadium_calibration():
vanadium_run = 98507 # Choose arbitrary run in the cycle 17_1
inst_obj = setup_inst_object(mode="tt70")
# Run create vanadium twice to ensure we get two different output splines / files
inst_obj.create_vanadium(run_in_cycle=vanadium_run,
do_absorb_corrections=True)
# Check the spline looks good and was saved
if not os.path.exists(spline_path):
raise RuntimeError(
"Could not find output spline at the following path: " +
spline_path)
splined_ws = mantid.Load(Filename=spline_path)
return splined_ws
def generate_ts_pdf(run_number, focus_file_path, merge_banks=False, q_lims=None, cal_file_name=None,
sample_details=None, output_binning=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 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)
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)
pdf_output = mantid.RebinToWorkspace(WorkspaceToRebin=pdf_output, WorkspaceToMatch=pdf_output[4],
PreserveEvents=True)
common.remove_intermediate_workspace('self_scattering_correction')
if output_binning is not None:
try:
pdf_output = mantid.Rebin(InputWorkspace=pdf_output, Params=output_binning)
except RuntimeError:
return pdf_output
return pdf_output
def pre_process(focus_run, params, time_period):
"""
pre_process the run passed in, usign the rebin parameters passed in
@param focus_run :: the run to focus
@param params :: the rebin parameters
@param time_period :: the time period for rebin by pulse
@return: pre-processed workspace
"""
# rebin based on pulse if a time period is sent in, otherwise just do a normal rebin
wsname = "engg_preproc_input_ws"
simple.Load(Filename=focus_run, OutputWorkspace=wsname)
if time_period is not None:
return rebin_pulse(params, wsname, time_period)
else:
return rebin_time(params, wsname)
def runTest(self):
import mantid.simpleapi as ms
def do_reduction(calibration):
# load data
data = ms.Load("HRP39180.RAW")
# copy parameters from calibration to data
ms.CopyInstrumentParameters(calibration, data)
# Now move component on data workspace using a relative move, where that component was a detector in the calibrated workspace
ms.MoveInstrumentComponent(data, DetectorID=1100,X=0.0,Y=0.0,Z=5.0,RelativePosition=True)
return data.getDetector(0).getPos()
####
# load calibration
calibration = ms.Load("HRP38094Calib")
self.det_pos_first_run = do_reduction(calibration)
# again not reloading of calibration
self.det_pos_second_run = do_reduction(calibration)
def to_workspace(cls, candidate, ws_prefix="_"):
_workspace = None
if isinstance(candidate, str):
candidate = ConvertToWavelength.get_first_of_coadd_ws(candidate)
if isinstance(candidate, mantid.api.Workspace):
_workspace = candidate
elif isinstance(candidate, str):
if mantid.api.AnalysisDataService.doesExist(candidate.strip()):
_workspace = mantid.api.AnalysisDataService.retrieve(candidate.strip())
elif mantid.api.AnalysisDataService.doesExist(ws_prefix + str(candidate.strip())):
_workspace = mantid.api.AnalysisDataService.retrieve(ws_prefix + str(candidate.strip()))
else:
ws_name = ws_prefix + str(candidate.strip())
msi.Load(Filename=candidate, OutputWorkspace=ws_name)
_workspace = mantid.api.AnalysisDataService.retrieve(ws_name)
else:
raise ValueError("Unknown source item %s" % candidate)
return _workspace
