def test_minimal_inputs(self):
in_ws = Load('INTER00013460.nxs', OutputWorkspace="13460")
trans1 = Load('INTER00013463.nxs', OutputWorkspace="trans1")
inst = trans1.getInstrument()
out_ws, out_wsl_lam, thetafinal = ReflectometryReductionOneAuto(InputWorkspace=in_ws, AnalysisMode="PointDetectorAnalysis"
,OutputWorkspace="InQ", OutputWorkspaceWavelength="InLam")
history = out_ws.getHistory()
alg = history.lastAlgorithm()
'''
Here we are checking that the applied values (passed to CreateTransmissionWorkspace come from the instrument parameters.
'''
self.assertEqual(inst.getNumberParameter("LambdaMin")[0], alg.getProperty("WavelengthMin").value)
self.assertEqual(inst.getNumberParameter("LambdaMax")[0], alg.getProperty("WavelengthMax").value)
self.assertEqual(inst.getNumberParameter("MonitorBackgroundMin")[0], alg.getProperty("MonitorBackgroundWavelengthMin").value)
self.assertEqual(inst.getNumberParameter("MonitorBackgroundMax")[0], alg.getProperty("MonitorBackgroundWavelengthMax").value)
self.assertEqual(inst.getNumberParameter("MonitorIntegralMin")[0], alg.getProperty("MonitorIntegrationWavelengthMin").value)
self.assertEqual(inst.getNumberParameter("MonitorIntegralMax")[0], alg.getProperty("MonitorIntegrationWavelengthMax").value)
self.assertEqual(inst.getNumberParameter("I0MonitorIndex")[0], alg.getProperty("I0MonitorIndex").value)
self.assertEqual(inst.getNumberParameter("PointDetectorStart")[0], float(alg.getProperty("ProcessingInstructions").value.split(',')[0]))
self.assertEqual(inst.getNumberParameter("PointDetectorStop")[0], float(alg.getProperty("ProcessingInstructions").value.split(',')[1]))
DeleteWorkspace(in_ws)
DeleteWorkspace(trans1)
def test_plus_operator_sums_multiple_set_files_to_give_group(self):
summed_data = Load("TSC15352+15353.raw,TSC15352+15354.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(summed_data, WorkspaceGroup))
self.assertEquals(2, summed_data.getNumberOfEntries())
# First group
data = summed_data[0]
self.assertEquals(149, data.getNumberHistograms())
self.assertEquals(24974, data.blocksize())
self.assertAlmostEqual(9.0, data.readX(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(46352.0, data.readY(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(215.29514625276622, data.readE(2)[1], places=DIFF_PLACES)
# Second group
data = summed_data[1]
self.assertEquals(149, data.getNumberHistograms())
self.assertEquals(24974, data.blocksize())
self.assertAlmostEqual(9.0, data.readX(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(35640.0, data.readY(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(188.78559267062727, data.readE(2)[1], places=DIFF_PLACES)
deleted_names = ["TSC15352", "TSC15353", "TSC15354"]
for name in deleted_names:
self.assertTrue(name not in AnalysisDataService)
def beam_center_gravitational_drop(beam_center_file, sdd=1.13):
'''
This method is used for correcting for gravitational drop
@param beam_center_file :: file where the beam center was found
@param sdd :: sample detector distance to apply the beam center
'''
def calculate_neutron_drop(path_length, wavelength):
'''
Calculate the gravitational drop of the neutrons
path_length in meters
wavelength in Angstrom
'''
wavelength *= 1e-10
neutron_mass = 1.674927211e-27
gravity = 9.80665
h_planck = 6.62606896e-34
l_2 = (gravity * neutron_mass**2 / (2.0 * h_planck**2 )) * path_length**2
return wavelength**2 * l_2
# Get beam center used in the previous reduction
pm = mantid.PropertyManagerDataService[ReductionSingleton().property_manager]
beam_center_x = pm['LatestBeamCenterX'].value
beam_center_y = pm['LatestBeamCenterY'].value
Logger("CommandInterface").information("Beam Center before: [%.2f, %.2f] pixels" % (beam_center_x, beam_center_y))
try:
# check if the workspace still exists
wsname = "__beam_finder_" + os.path.splitext(beam_center_file)[0]
ws = mantid.mtd[wsname]
Logger("CommandInterface").debug("Using Workspace: %s." % (wsname))
except KeyError:
# Let's try loading the file. For some reason the beamcenter ws is not there...
try:
ws = Load(beam_center_file)
Logger("CommandInterface").debug("Using filename %s." % (beam_center_file))
except IOError:
Logger("CommandInterface").error("Cannot read input file %s." % beam_center_file)
return
i = ws.getInstrument()
y_pixel_size_mm = i.getNumberParameter('y-pixel-size')[0]
Logger("CommandInterface").debug("Y Pixel size = %.2f mm" % y_pixel_size_mm)
y_pixel_size = y_pixel_size_mm * 1e-3 # In meters
distance_detector1 = i.getComponentByName("detector1").getPos()[2]
path_length = distance_detector1 - sdd
Logger("CommandInterface").debug("SDD detector1 = %.3f meters. SDD for wing = %.3f meters." % (distance_detector1, sdd))
Logger("CommandInterface").debug("Path length for gravitational drop = %.3f meters." % (path_length))
r = ws.run()
wavelength = r.getProperty("wavelength").value
Logger("CommandInterface").debug("Wavelength = %.2f A." % (wavelength))
drop = calculate_neutron_drop(path_length, wavelength)
Logger("CommandInterface").debug("Gravitational drop = %.6f meters." % (drop))
# 1 pixel -> y_pixel_size
# x pixel -> drop
drop_in_pixels = drop / y_pixel_size
new_beam_center_y = beam_center_y + drop_in_pixels
Logger("CommandInterface").information("Beam Center after: [%.2f, %.2f] pixels" % (beam_center_x, new_beam_center_y))
return beam_center_x, new_beam_center_y
def test_Load_call_with_args_that_do_not_apply_executes_correctly(self):
try:
raw = Load('IRS21360.raw', SpectrumMax=1, Append=True)
except RuntimeError:
self.fail(
"Load with a filename and extra args should not raise an exception"
)
self.assertEquals(1, raw.getNumberHistograms())
def do_reduction(calibration):
# load data
data = Load("HRP39180.RAW")
# copy parameters from calibration to data
CopyInstrumentParameters(calibration, data)
# Now move component on data workspace using a relative move, where that component was a detector in the calibrated workspace
MoveInstrumentComponent(data, DetectorID=1100,X=0.0,Y=0.0,Z=5.0,RelativePosition=True)
return data.getDetector(0).getPos()
def _create_experimental_data_workspace(self):
"""
Loads experimental data into workspaces.
:returns: workspace with experimental data
"""
experimental_wrk = Load(self._experimental_file)
self._set_workspace_units(wrk=experimental_wrk.name())
return experimental_wrk
def test_extra_properties_passed_to_loader_for_multiple_files(self):
data = Load("EQSANS_1466_event.nxs,EQSANS_3293_event.nxs", OutputWorkspace = self.wsname,
BankName = "bank1", SingleBankPixelsOnly = False)
self.assertTrue(isinstance(data, WorkspaceGroup))
self.assertEquals(2, data.getNumberOfEntries())
# Test number of events in each
self.assertEquals(740, data[0].getNumberEvents())
self.assertEquals(105666, data[1].getNumberEvents())
def PyExec(self):
filename = self.getProperty("Filename").value
from mantid.simpleapi import Load
# lifted from script
_tmp = Load(Filename=filename)
_tmp = _tmp.convertUnits(_tmp,Target="Energy")
self.setProperty("OutputWorkspace",_tmp)
_tmp.delete() # Remove temporary reference from MantidPlot view
def test_stepped_range_operator_loads_correct_number_of_files(self):
data = Load("TSC15352:15354:2.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(data, WorkspaceGroup))
self.assertEquals(2, data.getNumberOfEntries())
self.assertTrue(isinstance(data[0], MatrixWorkspace))
self.assertTrue(isinstance(data[1], MatrixWorkspace))
# Cursory check that the correct ones were loaded
self.assertTrue("TO96_2" in data[0].getTitle())
self.assertTrue("TO96_4" in data[1].getTitle())
def load_file_and_apply(self, filename, ws_name):
Load(Filename=filename,
OutputWorkspace=ws_name,
FilterByTofMin=self.getProperty("FilterByTofMin").value,
FilterByTofMax=self.getProperty("FilterByTofMax").value)
if self._load_inst:
LoadInstrument(Workspace=ws_name,
Filename=self.getProperty("LoadInstrument").value,
RewriteSpectraMap=False)
if self._apply_cal:
ApplyCalibration(
Workspace=ws_name,
CalibrationTable=self.getProperty("ApplyCalibration").value)
if self._detcal:
LoadIsawDetCal(InputWorkspace=ws_name,
Filename=self.getProperty("DetCal").value)
if self._copy_params:
CopyInstrumentParameters(OutputWorkspace=ws_name,
InputWorkspace=self.getProperty(
"CopyInstrumentParameters").value)
if self._masking:
if not mtd.doesExist('__mask'):
LoadMask(Instrument=mtd[ws_name].getInstrument().getName(),
InputFile=self.getProperty("MaskFile").value,
OutputWorkspace='__mask')
MaskDetectors(Workspace=ws_name, MaskedWorkspace='__mask')
if self.XMin != Property.EMPTY_DBL and self.XMax != Property.EMPTY_DBL:
ConvertUnits(InputWorkspace=ws_name,
OutputWorkspace=ws_name,
Target='Momentum')
CropWorkspaceForMDNorm(InputWorkspace=ws_name,
OutputWorkspace=ws_name,
XMin=self.XMin,
XMax=self.XMax)
def example_plots():
#create slices and cuts
w = Load(
Filename=
'/SNS/HYS/IPTS-14189/shared/autoreduce/4pixel/HYS_102102_4pixel_spe.nxs'
)
SetUB(w, 4.53, 4.53, 11.2, 90, 90, 90, "1,0,0", "0,0,1")
mde = ConvertToMD(w, QDimensions='Q3D')
sl1d = CutMD(InputWorkspace=mde,
P1Bin='-5,5',
P2Bin='-5,5',
P3Bin='2,4',
P4Bin='-10,0.5,15',
NoPix=True)
sl2d = CutMD(InputWorkspace=mde,
P1Bin='-5,5',
P2Bin='-5,5',
P3Bin='-5,0.1,5',
P4Bin='-10,1,15',
NoPix=True)
#2 subplots per page
fig, ax = plt.subplots(2, 1)
Plot1DMD(ax[0], sl1d, NumEvNorm=True, fmt='ro')
ax[0].set_ylabel("Int(a.u.)")
pcm = Plot2DMD(ax[1], sl2d, NumEvNorm=True)
fig.colorbar(pcm, ax=ax[1])
#save to png
plt.tight_layout(1.08)
fig.savefig('/tmp/test.png')
def test_not_in_deltaE(self):
red_ws_not_deltaE = Load('irs26176_graphite002_red.nxs')
red_ws_not_deltaE = ConvertUnits(InputWorkspace=self._red_ws,
Target='Wavelength',
EMode='Indirect',
EFixed=1.845)
kwargs = {
'ReducedWorkspace': red_ws_not_deltaE,
'SqwWorkspace': self._sqw_ws,
'ChemicalFormula': 'H2-O',
'SampleMassDensity': 1.0,
'NeutronPathsSingle': 50,
'NeutronPathsMultiple': 50,
'Height': 2.0,
'Shape': 'FlatPlate',
'Width': 1.4,
'Thickness': 2.1
}
with self.assertRaises(RuntimeError):
SimpleShapeDiscusInelastic(**kwargs)
DeleteWorkspace(red_ws_not_deltaE)
def main(input_file, output_dir):
validate(input_file, output_dir)
params = web_var.standard_vars
mapping_file = r"/archive/NDXGEM/user/scripts/autoreduction/gem_cycle_mapping.yaml"
calib_dir = r"/archive/NDXGEM/user/scripts/autoreduction/Calibration"
user = "******"
if params['mode'] == '' or params['mode'] == None:
ws = Load(input_file)
mode = determine_mode(ws)
if mode:
print("Using {} mode for reduction.".format(mode))
params['mode'] = mode
else:
raise ValueError(
"No mode supplied and unable to determine from logs please ensure "
"Phase T0, 6m and 9m are expected. "
"Re-run and manually supply mode in the parameters.")
cropping_values = [
(550, 19900), # Bank 1
(550, 19900), # Bank 2
(550, 19900), # Bank 3
(550, 19900), # Bank 4
(550, 18500), # Bank 5
(550, 16750) # Bank 6
]
if params['mode'] == 'Rietveld':
cropping_values = [
(700, 19500), # Bank 1
(1000, 19500), # Bank 2
(1000, 19500), # Bank 3
(1000, 19500), # Bank 4
(1000, 18500), # Bank 5
(1000, 18000) # Bank 6
]
gem = Gem(
user_name=user,
calibration_directory=calib_dir,
output_directory=output_dir,
calibration_mapping_file=mapping_file,
do_absorb_corrections=params['do_absorb_corrections'],
vanadium_normalisation=params['vanadium_normalisation'],
input_mode=params['input_mode'],
mode=params['mode'],
multiple_scattering=params['multiple_scattering'],
focused_cropping_values=cropping_values,
)
# Prior to running this script, you need to have created a vanadium for cycle 17_2 like so:
#gem.create_vanadium(do_absorb_corrections=True,
# mode="PDF",
# first_cycle_run_no=87568)
# Focus run
run_num = get_run_number(input_file)
gem.focus(run_number=run_num, do_absorb_corrections=False)
def GenerateEventsFilterFromFiles(filenames, OutputWorkspace,
InformationWorkspace, **kwargs):
logName = kwargs.get('LogName', None)
minValue = kwargs.get('MinimumLogValue', None)
maxValue = kwargs.get('MaximumLogValue', None)
logInterval = kwargs.get('LogValueInterval', None)
unitOfTime = kwargs.get('UnitOfTime', 'Nanoseconds')
# TODO - handle multi-file filtering. Delete this line once implemented.
if len(filenames) == 1:
error = 'Multi-file filtering is not yet supported. (Stay tuned...)'
raise Exception(error)
for i, filename in enumerate(filenames):
Load(Filename=filename, OutputWorkspace=filename)
splitws, infows = GenerateEventsFilter(InputWorkspace=filename,
UnitOfTime=unitOfTime,
LogName=logName,
MinimumLogValue=minValue,
MaximumLogValue=maxValue,
LogValueInterval=logInterval)
if i == 0:
GroupWorkspaces(splitws, OutputWorkspace=OutputWorkspace)
GroupWorkspaces(infows, OutputWorkspace=InformationWorkspace)
else:
mtd[OutputWorkspace].add(splitws)
mtd[InformationWorkspace].add(infows)
return
def find_reduced_run(run_number, run_rb, current_run_number,
output_workspace_binned):
"""
Contains the logic to find the reduced run.
First checks for a manually pre-reduced run inside RB/single_angles.
If not found, then looks for an autoreduced run.
"""
# try to find the file in a pre-reduced single_angles folder
run_file_path = find_pre_reduced_run(run_number, run_rb)
# did not find a pre-reduced run, try to load an autoreduced one
if not run_file_path:
if run_number == current_run_number:
# if we are looking for the current run number, we have this calculated in a local variable
return output_workspace_binned
else:
# only search for a file if the run is not the current one
run_file_path = find_autoreduced_run(run_number, run_rb)
# found a reduced run at some location, load it into a workspace and return it
if run_file_path:
ws = Load(run_file_path)
return ws
else:
return None
def test_model_with_filtered_data(self):
wsTuple = Load('POLREF00014966.nxs')
#get the first child workspace of the group
ws = wsTuple[0]
model = SampleLogsModel(ws)
log_names = model.get_log_names()
self.assertEqual(len(log_names), 140)
self.assertIn("raw_uah_log", log_names)
self.assertIn("current_period", log_names)
self.assertIn("period", log_names)
values = model.get_log_display_values("raw_uah_log")
self.assertEqual(values[0], "raw_uah_log")
self.assertEqual(values[1], "float series")
self.assertEqual(values[2], "(429 entries)")
self.assertEqual(values[3], "uAh")
self.assertTrue(model.is_log_plottable("raw_uah_log"))
self.assertFalse(model.is_log_plottable("current_period"))
self.assertTrue(model.is_log_plottable("period"))
self.assertTrue(model.get_is_log_filtered("raw_uah_log"))
self.assertFalse(model.get_is_log_filtered("period"))
self.assertFalse(model.get_is_log_filtered("current_period"))
stats = model.get_statistics("raw_uah_log", filtered=True)
self.assertAlmostEqual(stats.maximum, 193.333, 3)
stats = model.get_statistics("raw_uah_log", filtered=False)
self.assertAlmostEqual(stats.maximum, 194.296, 3)
self.assertFalse(model.isMD())
def setUp(self):
config['default.facility'] = 'ILL'
config['default.instrument'] = 'D7'
config.appendDataSearchSubDir('ILL/D7/')
Load('numerical_attenuation.nxs',
OutputWorkspace='numerical_attenuation_ws')
self._sampleProperties = {
'SampleChemicalFormula': 'V',
'SampleMass': 8.54,
'FormulaUnitMass': 50.94,
'SampleInnerRadius': 2,
'SampleOuterRadius': 2.5,
'SampleRadius': 2.5,
'Height': 2,
'SampleThickness': 0.5,
'SampleDensity': 0.1,
'SampleAngle': 0,
'SampleWidth': 2.5,
'BeamWidth': 3.0,
'BeamHeight': 3.0,
'ContainerRadius': 2.7,
'ContainerInnerRadius': 1.99,
'ContainerOuterRadius': 2.7,
'ContainerFrontThickness': 0.2,
'ContainerBackThickness': 0.2,
'ContainerChemicalFormula': 'Al',
'ContainerDensity': 0.01,
'EventsPerPoint': 100,
'ElementSize': 1.0,
'IncoherentCrossSection': 0.1,
'SampleSpin': 1.5
}
def runTest(self):
UseCompatibilityMode()
config['default.instrument'] = 'SANS2D'
SANS2DTUBES()
Set1D()
Detector("rear-detector")
# This contains two MASKFILE commands, each resulting in a separate call to MaskDetectors.
MaskFile('SANS2DTube_ZerroErrorFreeTest.txt')
# Saves a file which produces an output file which does not contain any zero errors
csv_file = FileFinder.getFullPath(
"SANS2DTUBES_ZeroErrorFree_batch.csv")
save_alg = {"SaveNexus": "nxs"}
BatchReduce(csv_file,
'nxs',
saveAlgs=save_alg,
plotresults=False,
save_as_zero_error_free=True)
DeleteWorkspace('zero_free_out_rear_1D_1.75_12.5')
# The zero correction only occurs for the saved files. Stephen King mentioned that the
# original workspaces should not be tampered with
self._final_output = os.path.join(
config['defaultsave.directory'],
'zero_free_out_rear_1D_1.75_12.5.nxs')
self._final_workspace = 'ws'
Load(Filename=self._final_output,
OutputWorkspace=self._final_workspace)
def runTest(self):
flood = CreateFloodWorkspace('OFFSPEC00035946.nxs', StartSpectrum=250, EndSpectrum=600,
ExcludeSpectra=[260, 261, 262, 516, 517, 518], OutputWorkspace='flood')
data = Load('OFFSPEC00044998.nxs')
data = Rebin(data, [0,1000,100000], PreserveEvents=False)
data = ConvertUnits(data, 'Wavelength')
ApplyFloodWorkspace(InputWorkspace=data, FloodWorkspace=flood, OutputWorkspace=self.out_ws_name)
def setUp(self):
red_ws = Load('irs26176_graphite002_red.nxs')
red_ws = ConvertUnits(InputWorkspace=red_ws,
Target='Wavelength',
EMode='Indirect',
EFixed=1.845)
self._arguments = {
'ChemicalFormula': 'H2-O',
'DensityType': 'Mass Density',
'Density': 1.0,
'EventsPerPoint': 200,
'BeamHeight': 3.5,
'BeamWidth': 4.0,
'Height': 2.0
}
self._red_ws = red_ws
corrected = SimpleShapeMonteCarloAbsorption(
InputWorkspace=self._red_ws,
Shape='FlatPlate',
Width=2.0,
Thickness=2.0,
**self._arguments)
# store the basic flat plate workspace so it can be compared with others
self._corrected_flat_plate = corrected
def test_ILL_reduced(self):
ill_red_ws = Load('ILL/IN16B/091515_red.nxs')
ill_red_ws = ConvertUnits(ill_red_ws,
Target='Wavelength',
EMode='Indirect',
EFixed=1.845)
kwargs = self._arguments
corrected = SimpleShapeMonteCarloAbsorption(InputWorkspace=ill_red_ws,
Shape='FlatPlate',
Width=2.0,
Thickness=2.0,
**kwargs)
x_unit = corrected.getAxis(0).getUnit().unitID()
self.assertEquals(x_unit, 'Wavelength')
y_unit = corrected.YUnitLabel()
self.assertEquals(y_unit, 'Attenuation factor')
num_hists = corrected.getNumberHistograms()
self.assertEquals(num_hists, 18)
blocksize = corrected.blocksize()
self.assertEquals(blocksize, 1024)
DeleteWorkspace(ill_red_ws)
def validateWorkspaceToNeXus(self):
'''
Assumes the second item from self.validate() is a nexus file and loads it
to compare to the supplied workspace.
'''
valNames = list(self.validate())
from mantid.simpleapi import Load
numRezToCheck=len(valNames)
mismatchName=None;
validationResult =True;
for ik in range(0,numRezToCheck,2): # check All results
workspace2 = valNames[ik+1]
if workspace2.endswith('.nxs'):
Load(Filename=workspace2,OutputWorkspace="RefFile")
workspace2 = "RefFile"
else:
raise RuntimeError("Should supply a NeXus file: %s" % workspace2)
valPair=(valNames[ik],"RefFile");
if numRezToCheck>2:
mismatchName = valNames[ik];
if not(self.validateWorkspaces(valPair,mismatchName)):
validationResult = False;
print 'Workspace {0} not equal to its reference file'.format(valNames[ik]);
#end check All results
return validationResult;
def runTest(self):
"""
Override parent method, does the work of running the test
"""
try:
# Load files and create workspace group
names = ('BASIS_63652_sqw', 'BASIS_63700_sqw')
[
Load(Filename=name + '.nxs', OutputWorkspace=name)
for name in names
]
GroupWorkspaces(InputWorkspaces=names,
OutputWorkspace='elwin_input')
ElasticWindowMultiple(InputWorkspaces='elwin_input',
IntegrationRangeStart=-0.0035,
IntegrationRangeEnd=0.0035,
BackgroundRangeStart=-0.1,
BackgroundRangeEnd=-0.05,
SampleEnvironmentLogName='SensorA',
SampleEnvironmentLogValue='average',
OutputInQ='outQ',
OutputInQSquared='outQ2',
OutputELF='ELF',
OutputELT='ELT')
finally:
self.preptear()
def setUp(self):
Load(Filename='irs26176_graphite002_red.nxs', OutputWorkspace='sample')
SetSample(InputWorkspace='sample',
Geometry={
'Shape': 'FlatPlate',
'Height': 2.0,
'Width': 2.0,
'Thick': 0.1,
'Center': [0., 0., 0.]
},
Material={
'ChemicalFormula': 'H2-O',
'MassDensity': 1.0
},
ContainerGeometry={
'Shape': 'FlatPlateHolder',
'Height': 2.0,
'Width': 2.0,
'Thick': 0.1,
'FrontThick': 0.02,
'BackThick': 0.02,
'Center': [0., 0., 0.]
},
ContainerMaterial={
'ChemicalFormula': 'V',
'MassDensity': 6.0
})
def Untest_exportVulcanFile(self):
""" Test to export logs without header file
File 2: VULCAN_41739_event
"""
from mantid.simpleapi import Load
# Generate the matrix workspace with some logs
Load(
Filename=
"/home/wzz/Projects/MantidProjects/Mantid2/Code/debug/VULCAN_41703_event.nxs",
OutputWorkspace="VULCAN_41703",
MetaDataOnly=True,
LoadLog=True)
# Test algorithm
alg_test = run_algorithm(
"ExportSampleLogsToCSVFile",
InputWorkspace="VULCAN_41703",
OutputFilename="/tmp/furnace41703.txt",
SampleLogNames=["furnace.temp1", "furnace.temp2", "furnace.power"],
WriteHeaderFile=False)
# Validate
self.assertTrue(alg_test.isExecuted())
return
class TableWorkspaceDisplayDecoderTest(unittest.TestCase):
def setUp(self):
self.ws = Load("SavedTableWorkspace.nxs", OutputWorkspace="ws")
self.decoder = TableWorkspaceDisplayDecoder()
def test_decoder_returns_view(self):
self.assertEqual(
self.decoder.decode(TABLEWORKSPACEDISPLAY_DICT).__class__,
StatusBarView)
def test_decoder_returns_custom_features(self):
view = self.decoder.decode(TABLEWORKSPACEDISPLAY_DICT)
self.assertEqual(self.ws.name(), view.presenter.model.ws.name())
self.assertEqual(TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y"],
view.presenter.model.marked_columns.as_y)
self.assertEqual(TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_x"],
view.presenter.model.marked_columns.as_x)
self.assertEqual(
TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y_err"][0]
["column"], view.presenter.model.marked_columns.as_y_err[0].column)
self.assertEqual(
TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y_err"][0]
["relatedY"],
view.presenter.model.marked_columns.as_y_err[0].related_y_column)
self.assertEqual(1, len(view.presenter.model.marked_columns.as_y_err))
def do_load(file_specifier, output_ws_name, ipf_filename, load_logs,
load_opts):
"""
Loads the files, passing the given file specifier in the load command.
:param file_specifier: The file specifier (single file, range or sum)
:param output_ws_name: The name of the output workspace to create
:param ipf_filename: The instrument parameter file to load with
:param load_opts: Additional loading options
:param load_logs: If True, load logs
"""
from mantid.simpleapi import LoadVesuvio, LoadParameterFile
if 'VESUVIO' in ipf_filename:
# Load all spectra. They are cropped later
LoadVesuvio(Filename=str(file_specifier),
OutputWorkspace=output_ws_name,
SpectrumList='1-198',
**load_opts)
else:
Load(Filename=file_specifier,
OutputWorkspace=output_ws_name,
LoadLogFiles=load_logs,
**load_opts)
# Load the instrument parameters
LoadParameterFile(Workspace=output_ws_name, Filename=ipf_filename)
def test_exp(self):
"""
Tests if experimental data is loaded correctly.
@return:
"""
Abins(AbInitioProgram=self._ab_initio_program,
VibrationalOrPhononFile="benzene_Abins.phonon",
ExperimentalFile="benzene_Abins.dat",
TemperatureInKelvin=self._temperature,
SampleForm=self._sample_form,
Instrument=self._instrument_name,
Atoms=self._atoms,
Scale=self._scale,
SumContributions=self._sum_contributions,
QuantumOrderEventsNumber=self._quantum_order_events_number,
ScaleByCrossSection=self._cross_section_factor,
OutputWorkspace="benzene_exp")
# load experimental data
Load(Filename="benzene.dat", OutputWorkspace="benzene_only_exp")
(result,
messages) = CompareWorkspaces(Workspace1=mtd["experimental_wrk"],
Workspace2=mtd["benzene_only_exp"],
CheckAxes=False,
Tolerance=self._tolerance)
self.assertEqual(result, True)
def validateWorkspaceToNeXus(self):
'''
Assumes the second item from self.validate() is a nexus file and loads it
to compare to the supplied workspace.
'''
valNames = list(self.validate())
numRezToCheck = len(valNames)
mismatchName = None
validationResult = True
# results are in pairs
for valname, refname in zip(valNames[::2], valNames[1::2]):
if refname.endswith('.nxs'):
Load(Filename=refname, OutputWorkspace="RefFile")
refname = "RefFile"
else:
raise RuntimeError("Should supply a NeXus file: %s" % refname)
valPair = (valname, "RefFile")
if numRezToCheck > 2:
mismatchName = valname
if not(self.validateWorkspaces(valPair, mismatchName)):
validationResult = False
print('Workspace {0} not equal to its reference file'.format(valname))
return validationResult
def test_csv_list_with_same_instrument_produces_single_group(self):
data = Load("OFFSPEC10791,10792,10793.raw", OutputWorkspace = self.wsname)
self.assertTrue(isinstance(data, WorkspaceGroup))
self.assertEquals(6, data.getNumberOfEntries())
ads_names = ["OFFSPEC00010791_1", "OFFSPEC00010791_2",
"OFFSPEC00010792_1", "OFFSPEC00010792_2",
"OFFSPEC00010793_1", "OFFSPEC00010793_2"]
for name in ads_names:
self.assertTrue(name in AnalysisDataService)
deleted_names = ["OFFSPEC10791", "OFFSPEC10792", "OFFSPEC10793"]
for name in deleted_names:
self.assertTrue(name not in AnalysisDataService)
self.cleanup_names = ads_names
def __determineCharacterizations(self, filename, wkspname, loadFile):
useCharac = bool(self.charac is not None)
# input workspace is only needed to find a row in the characterizations table
tempname = None
if loadFile:
if useCharac:
tempname = '__%s_temp' % wkspname
Load(Filename=filename, OutputWorkspace=tempname,
MetaDataOnly=True)
else:
tempname = wkspname # assume it is already loaded
# put together argument list
args = dict(ReductionProperties=self.getProperty('ReductionProperties').valueAsStr)
for name in PROPS_FOR_PD_CHARACTER:
prop = self.getProperty(name)
if not prop.isDefault:
args[name] = prop.value
if tempname is not None:
args['InputWorkspace']=tempname
if useCharac:
args['Characterizations'] = self.charac
PDDetermineCharacterizations(**args)
if loadFile and useCharac:
DeleteWorkspace(Workspace=tempname)
def test_csv_list_with_same_instrument_produces_single_group(self):
data = Load("OFFSPEC10791,10792,10793.raw", OutputWorkspace = self.wsname)
self.assertTrue(isinstance(data, WorkspaceGroup))
self.assertEquals(6, data.getNumberOfEntries())
ads_names = ["OFFSPEC00010791_1", "OFFSPEC00010791_2",
"OFFSPEC00010792_1", "OFFSPEC00010792_2",
"OFFSPEC00010793_1", "OFFSPEC00010793_2"]
for name in ads_names:
self.assertTrue(name in AnalysisDataService)
deleted_names = ["OFFSPEC10791", "OFFSPEC10792", "OFFSPEC10793"]
for name in deleted_names:
self.assertTrue(name not in AnalysisDataService)
self.cleanup_names = ads_names
def setUpClass(cls):
ConfigService.Instance().setString("default.facility", "ISIS")
# A small workspace for general tests
test_workspace = LoadNexusProcessed(Filename="LOQ48127")
cls.immutable_test_workspace = test_workspace
# A full workspace on which we can test region of interest selection
region_of_interest_workspace = Load(Filename="LOQ74044")
cls.region_of_interest_workspace = region_of_interest_workspace
# A region of interest xml file
roi_content = ("<?xml version=\"1.0\"?>\n"
"\t<detector-masking>\n"
"\t\t<group>\n"
"\t\t\t<detids>6990-6996</detids>\n"
"\t\t</group>\n"
"\t</detector-masking>\n")
cls.roi_file_path = cls._get_path(cls.roi_file)
cls._save_file(cls.roi_file_path, roi_content)
# A mask file
mask_content = ("<?xml version=\"1.0\"?>\n"
"\t<detector-masking>\n"
"\t\t<group>\n"
"\t\t\t<detids>6991</detids>\n"
"\t\t</group>\n"
"\t</detector-masking>\n")
cls.mask_file_path = cls._get_path(cls.mask_file)
cls._save_file(cls.mask_file_path, mask_content)
ConfigService.Instance().setString("default.facility", " ")
def test_history(self):
ws_name = "GEM38370_Focussed_Legacy"
file_name = FileFinder.getFullPath(ws_name + ".nxs")
Load(file_name, OutputWorkspace=ws_name)
ws = mtd[ws_name]
history = ws.getHistory()
self.assertEqual(history.empty(), False)
self.assertEqual(history.size(), 4)
alg_hists = history.getAlgorithmHistories()
self.assertEqual(len(alg_hists), 4)
self.assertEqual(alg_hists[0].name(), "LoadRaw")
self.assertEqual(alg_hists[1].name(), "AlignDetectors")
self.assertEqual(alg_hists[2].name(), "DiffractionFocussing")
self.assertEqual(alg_hists[3].name(), "Load")
self.assertEqual(history.getAlgorithmHistory(0).name(), "LoadRaw")
self.assertEqual(
history.getAlgorithmHistory(1).name(), "AlignDetectors")
self.assertEqual(
history.getAlgorithmHistory(2).name(), "DiffractionFocussing")
self.assertEqual(history.getAlgorithmHistory(3).name(), "Load")
alg = history.lastAlgorithm()
self.assertEqual(alg.name(), "Load")
alg = history.getAlgorithm(history.size() - 1)
self.assertEqual(alg.name(), "Load")
def main(input_file, output_dir):
standard_params = web_var.standard_vars
advanced_params = web_var.advanced_vars
config['defaultsave.directory'] = output_dir
print("Input file", input_file, "output dir", output_dir)
input_workspace, datafile_name = load_workspace(input_file)
flood_workspace = Load(advanced_params["flood_workspace"])
matplotlib_figure, (det_image_ax, spec_pixel_ax) = plt.subplots(
figsize=(13, 4.8), ncols=2, subplot_kw={'projection': 'mantid'})
matplotlib_figure.suptitle(input_workspace.getTitle())
plot_detector_image(input_workspace, matplotlib_figure, det_image_ax)
plotly_fig = plot_specular_pixel_check(input_workspace, flood_workspace,
spec_pixel_ax)
save_plotly_figure(plotly_fig, datafile_name, "peak", output_dir)
matplotlib_figure.savefig(os.path.join(output_dir, f"{datafile_name}.png"))
full_run_title = input_workspace.getTitle()
run_rb = str(input_workspace.getRun().getLogData("rb_proposal").value)
run_number = str(input_workspace.getRun().getLogData("run_number").value)
print("Run title:", full_run_title, "RB:", run_rb)
# only reduce if not a transmission run
if "trans" in full_run_title.lower():
print(
"Skipping reduction due to having 'trans' in the title: {full_run_title}"
)
else:
sample_name = get_sample_name(full_run_title)
settings_file = find_settings_json(
sample_name, standard_params['JSON Settings File'],
f"/instrument/INTER/RBNumber/RB{run_rb}")
output_workspace_binned = None
if settings_file:
output_workspace_binned = run_reduction(input_workspace,
datafile_name,
settings_file, output_dir)
else:
print("Skipping reduction due to missing settings file")
group_run_numbers = find_group_runs(sample_name, run_rb, input_file)
print("Found group_run_numbers:", group_run_numbers)
if group_run_numbers:
try:
group_plot_fig = plot_group_runs(group_run_numbers,
sample_name, run_rb,
run_number,
output_workspace_binned)
if group_plot_fig:
with open(
os.path.join(output_dir,
f"{datafile_name}_group.json"),
'w') as figfile:
figfile.write(group_plot_fig)
except Exception as err:
print("Encountered error while trying to plot group:", err)
def __loadAndTest__(self, filename):
"""Do all of the real work of loading and testing the file"""
print("----------------------------------------")
print("Loading '%s'" % filename)
from mantid.api import Workspace
# Output can be a tuple if the Load algorithm has extra output properties
# but the output workspace should always be the first argument
outputs = Load(filename)
if isinstance(outputs, tuple):
wksp = outputs[0]
else:
wksp = outputs
if not isinstance(wksp, Workspace):
print("Unexpected output type from Load algorithm: Type found=%s" %
str(type(outputs)))
return False
if wksp is None:
print('Load returned None')
return False
# generic checks
if wksp.name() is None or len(wksp.name()) <= 0:
print("Workspace does not have a name")
del wksp
return False
wid = wksp.id()
if wid is None or len(wid) <= 0:
print("Workspace does not have an id")
del wksp
return False
# checks based on workspace type
if hasattr(wksp, "getNumberHistograms"):
if wksp.getNumberHistograms() <= 0:
print("Workspace has zero histograms")
del wksp
return False
if "managed" not in wid.lower() and wksp.getMemorySize() <= 0:
print("Workspace takes no memory: Memory used=" +
str(wksp.getMemorySize()))
del wksp
return False
# checks for EventWorkspace
if hasattr(wksp, "getNumberEvents"):
if wksp.getNumberEvents() <= 0:
print("EventWorkspace does not have events")
del wksp
return False
# do the extra checks
result = self.__runExtraTests__(wksp, filename)
# cleanup
del wksp
return result
def fetch_correction_workspaces(vanadium_path, instrument, rb_num=""):
"""
Fetch workspaces from the file system or create new ones.
:param vanadium_path: The path to the requested vanadium run raw data.
:param instrument: The instrument the data came from.
:param rb_num: A user identifier, usually an experiment number.
:return: The resultant integration and curves workspaces.
"""
vanadium_number = path_handling.get_run_number_from_path(
vanadium_path, instrument)
integ_path, curves_path = _generate_saved_workspace_file_paths(
vanadium_number)
force_recalc = get_setting(path_handling.INTERFACES_SETTINGS_GROUP,
path_handling.ENGINEERING_PREFIX,
"recalc_vanadium",
return_type=bool)
if path.exists(curves_path) and path.exists(
integ_path
) and not force_recalc: # Check if the cached files exist.
try:
integ_workspace = Load(Filename=integ_path,
OutputWorkspace=INTEGRATED_WORKSPACE_NAME)
curves_workspace = Load(Filename=curves_path,
OutputWorkspace=CURVES_WORKSPACE_NAME)
if rb_num:
user_integ, user_curves = _generate_saved_workspace_file_paths(
vanadium_number, rb_num=rb_num)
if not path.exists(user_integ) and not path.exists(
user_curves):
_save_correction_files(integ_workspace, user_integ,
curves_workspace, user_curves)
return integ_workspace, curves_workspace
except RuntimeError as e:
logger.error(
"Problem loading existing vanadium calculations. Creating new files. Description: "
+ str(e))
integ_workspace, curves_workspace = _calculate_vanadium_correction(
vanadium_path)
_save_correction_files(integ_workspace, integ_path, curves_workspace,
curves_path)
if rb_num:
user_integ, user_curves = _generate_saved_workspace_file_paths(
vanadium_number, rb_num=rb_num)
_save_correction_files(integ_workspace, user_integ, curves_workspace,
user_curves)
return integ_workspace, curves_workspace
def test_get_history_chained_calls(self):
ws_name = "GEM38370_Focussed_Legacy"
file_name = FileFinder.getFullPath(ws_name + ".nxs")
Load(file_name, OutputWorkspace=ws_name)
ws = mtd[ws_name]
load_filename = ws.getHistory().lastAlgorithm().getProperty(
"Filename").value
self.assertEqual(file_name, load_filename[0])
def test_TotScatCalculateSelfScattering_executes(self):
raw_ws = Load(Filename='POLARIS98533.nxs')
correction_ws = TotScatCalculateSelfScattering(
InputWorkspace=raw_ws,
CalFileName=self.cal_file_path,
SampleGeometry=self.geometry,
SampleMaterial=self.material)
self.assertEqual(correction_ws.getNumberHistograms(), 5)
def test_Load_returns_correct_args_when_extra_output_props_are_added_at_execute_time(
self):
try:
data, monitors = Load('IRS21360.raw', LoadMonitors='Separate')
except Exception, exc:
self.fail(
"An error occurred when returning outputs declared at algorithm execution: '%s'"
% str(exc))
def test_csv_list_with_different_instrument_produces_single_group(self):
# Combine test of different instruments with giving the output name
# the same name as one of the members of the group
self.wsname = "LOQ99631"
data = Load("LOQ99631.RAW, CSP85423.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(data, WorkspaceGroup))
self.assertEquals(3, data.getNumberOfEntries())
ads_names = ["LOQ99631", "CSP85423_1", "CSP85423_2"]
for name in ads_names:
self.assertTrue(name in AnalysisDataService)
deleted_names = ["CSP85423"]
for name in deleted_names:
self.assertTrue(name not in AnalysisDataService)
self.cleanup_names = ads_names
self.wsname = "__LoadTest"
def _run_number_changed(self):
""" Handling event if run number is changed... If it is a valid run number,
the load the meta data
"""
# 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 = 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)
Logger('FilterSetupWidget').information('{}[{}]'.format(p.name, p.size()))
# ENDFOR p
properties = sorted(properties)
# c) Add
for p in properties:
self._content.log_name_combo.addItem(p)
def test_plus_operator_for_input_groups(self):
summed_data = Load("OFFSPEC10791+10792.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(summed_data, WorkspaceGroup))
self.assertEquals(2, summed_data.getNumberOfEntries())
# First group
data = summed_data[0]
self.assertEquals(245, data.getNumberHistograms())
self.assertEquals(5000, data.blocksize())
self.assertAlmostEqual(25.0, data.readX(1)[1], places=DIFF_PLACES)
self.assertAlmostEqual(4.0, data.readY(1)[1], places=DIFF_PLACES)
self.assertAlmostEqual(2.0, data.readE(1)[1], places=DIFF_PLACES)
# Second group
data = summed_data[1]
self.assertEquals(245, data.getNumberHistograms())
self.assertEquals(5000, data.blocksize())
self.assertAlmostEqual(25.0, data.readX(1)[1], places=DIFF_PLACES)
self.assertAlmostEqual(1.0, data.readY(1)[1], places=DIFF_PLACES)
self.assertAlmostEqual(1.0, data.readE(1)[1], places=DIFF_PLACES)
def test_sum_range_operator_with_step_sums_to_single_workspace(self):
data = Load("TSC15352-15354:2.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(data, MatrixWorkspace))
self.assertEquals(149, data.getNumberHistograms())
self.assertEquals(24974, data.blocksize())
self.assertAlmostEqual(9.0, data.readX(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(35640.0, data.readY(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(188.78559267062727, data.readE(2)[1], places=DIFF_PLACES)
def test_sum_range_operator_sums_to_single_workspace(self):
data = Load("TSC15352-15353.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(data, MatrixWorkspace))
self.assertEquals(149, data.getNumberHistograms())
self.assertEquals(24974, data.blocksize())
self.assertAlmostEqual(9.0, data.readX(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(46352.0, data.readY(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(215.29514625276622, data.readE(2)[1], places=DIFF_PLACES)
def runTest(self):
self.input_ws = Load(Filename=self.input_ws_path(), OutputWorkspace="input_ws")
gsas_path = self.path_to_gsas()
if not gsas_path:
self.fail("Could not find GSAS-II installation")
self.fitted_peaks_ws, self.lattice_params_table, self.rwp, self.sigma, self.gamma = \
GSASIIRefineFitPeaks(RefinementMethod=self._get_refinement_method(),
InputWorkspace=self.input_ws,
PhaseInfoFiles=self.phase_file_paths(),
InstrumentFile=self.inst_param_file_path(),
PathToGSASII=gsas_path,
SaveGSASIIProjectFile=self._get_gsas_proj_filename(),
MuteGSASII=True,
XMin=10000, XMax=40000,
LatticeParameters=self._LATTICE_PARAM_TBL_NAME,
RefineSigma=True, RefineGamma=True)
def test_plus_operator_sums_single_set_files(self):
data = Load("TSC15352+15353.raw", OutputWorkspace=self.wsname)
self.assertTrue(isinstance(data, MatrixWorkspace))
self.assertEquals(149, data.getNumberHistograms())
self.assertEquals(24974, data.blocksize())
self.assertAlmostEqual(9.0, data.readX(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(46352.0, data.readY(2)[1], places=DIFF_PLACES)
self.assertAlmostEqual(215.29514625276622, data.readE(2)[1], places=DIFF_PLACES)
deleted_names = ["TSC15352", "TSC15353"]
for name in deleted_names:
self.assertTrue(name not in AnalysisDataService)
class TableWorkspaceDisplayDecoderTest(GuiTest):
def setUp(self):
self.ws = Load("SavedTableWorkspace.nxs", OutputWorkspace="ws")
self.decoder = TableWorkspaceDisplayDecoder()
def test_decoder_returns_view(self):
self.assertEqual(self.decoder.decode(TABLEWORKSPACEDISPLAY_DICT).__class__, StatusBarView)
def test_decoder_returns_custom_features(self):
view = self.decoder.decode(TABLEWORKSPACEDISPLAY_DICT)
self.assertEqual(self.ws.name(), view.presenter.model.ws.name())
self.assertEqual(TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y"], view.presenter.model.marked_columns.as_y)
self.assertEqual(TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_x"], view.presenter.model.marked_columns.as_x)
self.assertEqual(
TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y_err"][0]["column"],
view.presenter.model.marked_columns.as_y_err[0].column)
self.assertEqual(
TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y_err"][0]["relatedY"],
view.presenter.model.marked_columns.as_y_err[0].related_y_column)
self.assertEqual(
TABLEWORKSPACEDISPLAY_DICT["markedColumns"]["as_y_err"][0]["labelIndex"],
view.presenter.model.marked_columns.as_y_err[0].label_index)
self.assertEqual(1, len(view.presenter.model.marked_columns.as_y_err))
def PyExec(self):
from mantid.simpleapi import Load, ConvertUnits, Rebin, DeleteWorkspace
# Load file to workspace
_tmpws = Load(Filename=self.getPropertyValue("Filename"))
# Convert to units to DeltaE
ei = self.getProperty("Ei").value
_tmpws = ConvertUnits(InputWorkspace=_tmpws, Target="DeltaE", EMode="Direct", EFixed=ei)
# Rebin to requested units
bins = self.getProperty("BinParams").value
_tmpws = Rebin(InputWorkspace=_tmpws, Params=bins)
# Create the new output workspace
_summed = WorkspaceFactory.create(_tmpws, NVectors=1)
# Set the X values for the new workspace
_summed.setX(0, _tmpws.readX(0))
# Sum the rows to a single row. Two methods demonstrated:
# ----- 1: Direct workspace access -----
# Uses less memory as it avoids a copy of the data
# readY returns read only array. dataY returns an array we can modify on the new workspace
# note _summed at this point has all its y-values = 0
sumy = _summed.dataY(0) # initialise sumy with zeros
for i in range(_tmpws.getNumberHistograms()):
sumy += _tmpws.readY(i)
# ----- 2: Extract to numpy and sum ----
# Uses more memory as extract copies to data (uncomment to see working)
# yin = __tmpsws.extractY()
# npsum = numpy.sum(yin,axis=0) # Axis 0 = summing down the columns
# and put the data to the workspace
# _summed.setY(0, npsum)
# Store reference outside of algorithm
self.setProperty("OutputWorkspace", _summed)
DeleteWorkspace(_tmpws)
def test_extra_properties_passed_to_loader(self):
data = Load("CNCS_7860_event.nxs", OutputWorkspace=self.wsname, BankName="bank1", SingleBankPixelsOnly=False)
self.assertTrue(isinstance(data, IEventWorkspace))
self.assertEquals(1740, data.getNumberEvents())
def test_Load_call_with_all_keyword_args_executes_correctly(self):
raw = Load(Filename='IRS21360.raw', SpectrumMax=1)
self.assertEquals(1, raw.getNumberHistograms())
def test_Load_call_with_other_args_executes_correctly(self):
try:
raw = Load("IRS21360.raw", SpectrumMax=1)
except RuntimeError:
self.fail("Load with a filename and extra args should not raise an exception")
self.assertEquals(1, raw.getNumberHistograms())
def setUp(self):
self.ws = Load("SavedTableWorkspace.nxs", OutputWorkspace="ws")
self.decoder = TableWorkspaceDisplayDecoder()
def test_Load_call_with_just_filename_executes_correctly(self):
try:
raw = Load('IRS21360.raw')
except RuntimeError:
self.fail("Load with a filename should not raise an exception")
self.assertEquals(116, raw.getNumberHistograms())
print "t0={}, t(-1)={}".format(running_times[0], running_times[-1])
if ts < running_times[0] or ts > running_times[-1]:
return False
running = True
for i in range(len(running_times) - 1):
print "ts={}, rt(i)={}, rt(i+1)={}".format(ts, running_times[i], running_times[i+1])
if (ts >= running_times[i]) and (ts < running_times[i+1]):
running = running_values[i]
print "found ",i, running
break
return running
# ----------------------------------------------------------------------------------------------------------------------
w = Load('/mnt/data1/source/github/mantidproject/mantid/builds/debug/ExternalData/Testing/Data/SystemTest/LARMOR/LARMOR00000063.nxs')
r = w.run()
run_start = dt.datetime.strptime(str(r.startTime()).strip(), ISO_TIMESTAMP_FORMAT)
dae_beam_current = r.getLogData('dae_beam_current')
# running log is series of boolean values indicating run status
running_log = w.run().getLogData('running')
running_times = []
for t in running_log.times:
running_times.append(to_datetime_iso(t))
# create times as offset from run_start
uamps_times, uamps_values = dae_beam_current.times, dae_beam_current.value
delta_t, uamps_datetime = [], []
for t in uamps_times:
t1, t2 = run_start, to_datetime_iso(t)
def reduceOneKeepingEvents(nxsfile, angle, eiguess, eaxis, outfile, t0guess=0.):
"""reduce nxs from one angle of a single crystal scan, keeping events
(only do tof->E conversion)
nxsfile: input path
angle: psi in degrees
eiguess: Ei in meV
eaxis: Emin, Emax, dE
outfile: output path
"""
from mantid.simpleapi import DgsReduction, SofQW3, SaveNexus, SaveNXSPE, LoadInstrument, Load, MoveInstrumentComponent, AddSampleLog
outfile = os.path.abspath(outfile)
print "* working on reducing %s to %s" % (nxsfile, outfile)
# load workspace from input nexus file
workspace = Load(nxsfile)
# workspace name have to be unique
unique_name = os.path.dirname(nxsfile).split('/')[-1]
wsname = 'reduced-%s' % unique_name
# Ei
if eiguess == 0.:
# If user does not supply Ei, we try to get it from the samplelog,
# because mcvine-generated SEQUOIA data files are mantid-processed nexus file
# with sample logs of Ei and t0.
# If we don't have them from sample logs, we just set Ei and T0 to None
run = workspace.getRun()
UseIncidentEnergyGuess = False
try:
Ei = run.getLogData('mcvine-Ei').value
UseIncidentEnergyGuess = True
except:
Ei = None
try:
T0 = run.getLogData('mcvine-t0').value
except:
T0 = None
else:
# user specified Ei, just use that
Ei = eiguess
T0 = t0guess
UseIncidentEnergyGuess = True
# keep events (need to then run RebinToWorkspace and ConvertToDistribution)
Emin, Emax, dE = eaxis
eaxis = '%s,%s,%s' % (Emin,dE, Emax)
DgsReduction(
SampleInputWorkspace = workspace,
IncidentEnergyGuess = Ei,
TimeZeroGuess = T0,
UseIncidentEnergyGuess=UseIncidentEnergyGuess,
OutputWorkspace=wsname,
SofPhiEIsDistribution='0',
EnergyTransferRange = eaxis,
)
AddSampleLog(Workspace=wsname,LogName="psi",LogText=str(angle),LogType="Number")
SaveNexus(
InputWorkspace=wsname,
Filename = outfile,
Title = 'reduced',
)
return
class _AbstractGSASIIRefineFitPeaksTest(stresstesting.MantidStressTest):
__metaclass__ = ABCMeta
fitted_peaks_ws = None
gamma = None
input_ws = None
rwp = None
sigma = None
lattice_params_table = None
_LATTICE_PARAM_TBL_NAME = "LatticeParameters"
_INPUT_WORKSPACE_FILENAME = "focused_bank1_ENGINX00256663.nxs"
_PHASE_FILENAME_1 = "Fe-gamma.cif"
_PHASE_FILENAME_2 = "Fe-alpha.cif"
_INST_PARAM_FILENAME = "template_ENGINX_241391_236516_North_bank.prm"
_TEMP_DIR = tempfile.gettempdir()
_path_to_gsas = None
@abstractmethod
def _get_expected_rwp(self):
pass
@abstractmethod
def _get_fit_params_reference_filename(self):
pass
@abstractmethod
def _get_gsas_proj_filename(self):
pass
@abstractmethod
def _get_refinement_method(self):
pass
def cleanup(self):
mantid.mtd.clear()
self.remove_all_gsas_files(gsas_filename_without_extension=self._get_gsas_proj_filename().split(".")[0])
def excludeInPullRequests(self):
return True
def input_ws_path(self):
return mantid.FileFinder.getFullPath(self._INPUT_WORKSPACE_FILENAME)
def inst_param_file_path(self):
return mantid.FileFinder.getFullPath(self._INST_PARAM_FILENAME)
def path_to_gsas(self):
if self._path_to_gsas is None:
gsas_location = os.path.join(site.USER_SITE, "g2conda", "GSASII")
if os.path.isdir(gsas_location):
self._path_to_gsas = os.path.join(site.USER_SITE, "g2conda", "GSASII")
else:
self._path_to_gsas = ""
return self._path_to_gsas
def phase_file_paths(self):
return mantid.FileFinder.getFullPath(self._PHASE_FILENAME_1) + "," + \
mantid.FileFinder.getFullPath(self._PHASE_FILENAME_2)
def remove_all_gsas_files(self, gsas_filename_without_extension):
for filename in os.listdir(self._TEMP_DIR):
if re.search(gsas_filename_without_extension, filename):
os.remove(os.path.join(self._TEMP_DIR, filename))
def runTest(self):
self.input_ws = Load(Filename=self.input_ws_path(), OutputWorkspace="input_ws")
gsas_path = self.path_to_gsas()
if not gsas_path:
self.fail("Could not find GSAS-II installation")
self.fitted_peaks_ws, self.lattice_params_table, self.rwp, self.sigma, self.gamma = \
GSASIIRefineFitPeaks(RefinementMethod=self._get_refinement_method(),
InputWorkspace=self.input_ws,
PhaseInfoFiles=self.phase_file_paths(),
InstrumentFile=self.inst_param_file_path(),
PathToGSASII=gsas_path,
SaveGSASIIProjectFile=self._get_gsas_proj_filename(),
MuteGSASII=True,
XMin=10000, XMax=40000,
LatticeParameters=self._LATTICE_PARAM_TBL_NAME,
RefineSigma=True, RefineGamma=True)
def skipTests(self):
# Skip this test, as it's just a wrapper for the Rietveld and Pawley tests
return True
def validate(self):
# TODO: Check fitted_peaks_ws has correct values once we have some data we're sure of
self.assertEqual(self.input_ws.getNumberBins(), self.fitted_peaks_ws.getNumberBins())
self.assertAlmostEqual(self.rwp, self._get_expected_rwp(), delta=1e-6)
return self._LATTICE_PARAM_TBL_NAME, mantid.FileFinder.getFullPath(self._get_fit_params_reference_filename())