def setUp(self):
self._facility = config['default.facility']
self._data_search_dirs = config.getDataSearchDirs()
config.appendDataSearchSubDir('ILL/D11/')
config.appendDataSearchSubDir('ILL/D33/')
config.setFacility("ILL")
SANSILLReduction(Run='010569', ProcessAs='Sample', OutputWorkspace='sample')
def tearDown(self):
config.setFacility(self._facility)
config.setDataSearchDirs(self._data_search_dirs)
mtd.clear()
def runTest(self):
""" This is the old way to do MDNorm to sample, background and finally clean background from sample
Now it serves as a benchmark to generate expected result for enhanced MDNorm
Current status: To task 88 no accumulation
Next status: To task 89 no accumulation
To task 88 with accumulation
To task 89 with accumulation
"""
# Set facility that load data
config.setFacility('SNS')
Load(Filename='HYS_13656', OutputWorkspace='sum')
SetGoniometer(Workspace='sum', Axis0='s1,0,1,0,1')
# prepare sample MD: in test must between 10 and 12 to match the gold data
dgs_red_group_name1 = self.prepare_md(input_ws_name='sum',
merged_md_name='merged1',
min_log_value=10,
max_log_value=12,
log_step=LOG_VALUE_STEP,
prefix='step1')
# 1-1 Existing method (but to keep)
benchmark = self.run_old_solution('merged1',
f'{dgs_red_group_name1}_1',
'oldstep1')
self._old_clean = str(benchmark.cleaned)
# Prepare background workspace
self.prepare_single_exp_info_background(
input_md_name=f'{dgs_red_group_name1}_1',
output_md_name='bkgd_md1',
target_qframe='Q_lab')
# Test new solutions
r = MDNorm(InputWorkspace='merged1',
BackgroundWorkspace='bkgd_md1',
Dimension0Name='QDimension1',
Dimension0Binning='-5,0.05,5',
Dimension1Name='QDimension2',
Dimension1Binning='-5,0.05,5',
Dimension2Name='DeltaE',
Dimension2Binning='-2,2',
Dimension3Name='QDimension0',
Dimension3Binning='-0.5,0.5',
SymmetryOperations=SYMMETRY_OPERATION,
OutputWorkspace='clean_data',
OutputDataWorkspace='dataMD',
OutputNormalizationWorkspace='normMD',
OutputBackgroundDataWorkspace='background_dataMD',
OutputBackgroundNormalizationWorkspace='background_normMD')
# Test solution
assert hasattr(r, 'OutputBackgroundNormalizationWorkspace'
), 'MDNorm does not execute.'
# Compare workspaces: binned background data workspace
rc = CompareMDWorkspaces(Workspace1=benchmark.bkgd_data,
Workspace2='background_dataMD')
assert rc.Equals, f'Error message: {rc.Result}'
# Compare workspaces: background normalization workspace
r89 = CompareMDWorkspaces(Workspace1=benchmark.bkgd_norm,
Workspace2='background_normMD',
Tolerance=1E-9)
assert r89.Equals, f'Incompatible background normalization workspaces: {r89.Result}'
# Compare the cleaned MD
r_out = CompareMDWorkspaces(Workspace1=benchmark.cleaned,
Workspace2='clean_data',
Tolerance=1E-16)
if not r_out.Equals:
raise ValueError(
f'Sample output data does not match: {r_out.Result}')
# Round 2: Test accumulation mode
dgs_red_group_name1 = self.prepare_md(input_ws_name='sum',
merged_md_name='merged2',
min_log_value=13,
max_log_value=15,
log_step=LOG_VALUE_STEP,
prefix='step2')
# Old solution
benchmark2 = self.run_old_solution('merged2',
f'{dgs_red_group_name1}_2',
'oldstep2', benchmark)
# 1-2 Test new solutions
self.prepare_single_exp_info_background(
input_md_name=f'{dgs_red_group_name1}_2',
output_md_name='bkgd_md2',
target_qframe='Q_lab')
r = MDNorm(
InputWorkspace='merged2',
BackgroundWorkspace='bkgd_md2',
TemporaryDataWorkspace='dataMD',
TemporaryNormalizationWorkspace='normMD',
TemporaryBackgroundDataWorkspace='background_dataMD',
TemporaryBackgroundNormalizationWorkspace='background_normMD',
Dimension0Name='QDimension1',
Dimension0Binning='-5,0.05,5',
Dimension1Name='QDimension2',
Dimension1Binning='-5,0.05,5',
Dimension2Name='DeltaE',
Dimension2Binning='-2,2',
Dimension3Name='QDimension0',
Dimension3Binning='-0.5,0.5',
SymmetryOperations=SYMMETRY_OPERATION,
OutputWorkspace='clean_data_2',
OutputDataWorkspace='dataMD2',
OutputNormalizationWorkspace='normMD2',
OutputBackgroundDataWorkspace='background_dataMD2',
OutputBackgroundNormalizationWorkspace='background_normMD2')
# Compare data workspace
r_sd = CompareMDWorkspaces(Workspace1=benchmark2.sample_data,
Workspace2='dataMD',
Tolerance=1E-7)
assert r_sd.Equals, f'Sample binned data MD not equal: {r_sd.Result}'
# Compare gold (old solution) and new: passed test in #88
r = CompareMDWorkspaces(Workspace1=benchmark2.bkgd_data,
Workspace2='background_dataMD2')
if not r.Equals:
raise ValueError(
f'Accumulation mode: Background binned data MD: {r.Result}')
# Compare gold (old solution) and new: passed test in #88
r_bn = CompareMDWorkspaces(Workspace1=benchmark2.bkgd_norm,
Workspace2='background_normMD2',
Tolerance=1E-9)
if not r_bn.Equals:
raise ValueError(
f'Accumulation mode: Background normalization MD: {r_bn.Result}'
)
# Test MDNorm's checking on inputs
# Note that this test must be put after all the tests because
# it will modify some workspaces and thus mess some experimental data set up to verify
self.test_property_setup('merged1', f'{dgs_red_group_name1}_1')
def __init__(self, *args):
# set previous
config.setFacility('SNS')
unittest.TestCase.__init__(self, *args)