def test_advanced_geometry(self):
# basic test that positions are approximately equal for detectors for
# CNCS given advanced and basic geometry calculation routes
x = scn.from_mantid(self.base_event_ws, advanced_geometry=False)
y = scn.from_mantid(self.base_event_ws, advanced_geometry=True)
assert np.all(
np.isclose(x.coords['position'].values,
y.coords['position'].values))
def test_extract_energy_inital_when_not_present():
from mantid.simpleapi import CreateSampleWorkspace
from mantid.kernel import DeltaEModeType
ws = CreateSampleWorkspace(StoreInADS=False)
assert ws.getEMode() == DeltaEModeType.Elastic
ds = scn.from_mantid(ws)
assert "incident_energy" not in ds.coords
def test_attrs_with_dims():
from mantid.kernel import FloatArrayProperty
import mantid.simpleapi as sapi
dataX = [1, 2, 3]
dataY = [1, 2, 3]
ws = sapi.CreateWorkspace(DataX=dataX,
DataY=dataY,
NSpec=1,
UnitX="Wavelength")
# Time series property
sapi.AddSampleLog(ws, 'attr0', LogText='1', LogType='Number Series')
# Single value property
sapi.AddSampleLog(ws, 'attr1', LogText='1', LogType='Number')
# Array property (not time series)
p = FloatArrayProperty('attr2', np.arange(10))
run = ws.mutableRun()
run.addProperty('attr2', p, replace=True)
ds = scn.from_mantid(ws)
# Variable (single value) wrapped DataArray
assert isinstance(ds.attrs['attr0'].value, sc.DataArray)
assert 'time' in ds.attrs['attr0'].value.coords
# Variable (single value)
assert isinstance(ds.attrs['attr1'].value, int)
# Variable (single value) wrapped Variable
assert isinstance(ds.attrs['attr2'].value, sc.Variable)
assert ds.attrs['attr2'].shape == [] # outer wrapper
assert ds.attrs['attr2'].value.shape == [10] # inner held
def test_WorkspaceGroup_parsed_correctly(self):
from mantid.simpleapi import (mtd, CreateSampleWorkspace,
GroupWorkspaces)
CreateSampleWorkspace(OutputWorkspace="ws1")
CreateSampleWorkspace(OutputWorkspace="ws2")
CreateSampleWorkspace(OutputWorkspace="ws3")
GroupWorkspaces(InputWorkspaces="ws1,ws2,ws3",
OutputWorkspace="NewGroup")
converted_group = scn.from_mantid(mtd["NewGroup"])
converted_single = scn.from_mantid(mtd["ws1"])
assert len(converted_group) == 3
assert sc.identical(converted_group['ws1'], converted_single)
mtd.clear()
def test_from_mask_workspace():
from mantid.simpleapi import LoadMask
from os import path
dir_path = path.dirname(path.realpath(__file__))
mask = LoadMask('HYS', path.join(dir_path, 'HYS_mask.xml'))
da = scn.from_mantid(mask)
assert da.data.dtype == sc.DType.bool
assert da.dims == ['spectrum']
assert da.variances is None
def test_from_mantid_CreateWorkspace(self):
import mantid.simpleapi as mantid
dataX = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
dataY = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
ws = mantid.CreateWorkspace(DataX=dataX,
DataY=dataY,
NSpec=4,
UnitX="Wavelength")
d = scn.from_mantid(ws)
self.assertEqual(d.data.unit, sc.units.dimensionless)
def test_inelastic_unit_conversion(self):
import mantid.simpleapi as mantid
eventWS = self.base_event_ws
ws_deltaE = mantid.ConvertUnits(eventWS,
Target='DeltaE',
EMode='Direct',
EFixed=3)
ref = scn.from_mantid(ws_deltaE)
da = scn.from_mantid(eventWS)
# Boost and Mantid use CODATA 2006. This test passes if we manually
# change the implementation to use the old constants. Alternatively
# we can correct for this by scaling L1^2 or L2^2, and this was also
# confirmed in C++. Unfortunately only positions are accessible to
# correct for this here, and due to precision issues with
# dot/norm/sqrt this doesn't actually fix the test. We additionally
# exclude low TOF region, and bump relative and absolute accepted
# errors from 1e-8 to 1e-5.
m_n_2006 = 1.674927211
m_n_2018 = 1.67492749804
e_2006 = 1.602176487
e_2018 = 1.602176634
scale = (m_n_2006 / m_n_2018) / (e_2006 / e_2018)
da.coords['source_position'] *= np.sqrt(scale)
da.coords['position'] *= np.sqrt(scale)
low_tof = da.bins.constituents['data'].coords[
'tof'] < 49000.0 * sc.units.us
da.coords['incident_energy'] = 3.0 * sc.units.meV
da = scn.convert(da, 'tof', 'energy_transfer', scatter=True)
assert sc.all(
sc.isnan(da.coords['energy_transfer'])
| sc.isclose(da.coords['energy_transfer'],
ref.coords['energy_transfer'],
atol=1e-8 * sc.units.meV,
rtol=1e-8 * sc.units.one)).value
assert sc.all(
low_tof
| sc.isnan(da.bins.constituents['data'].coords['energy_transfer'])
| sc.isclose(
da.bins.constituents['data'].coords['energy_transfer'],
ref.bins.constituents['data'].coords['energy_transfer'],
atol=1e-5 * sc.units.meV,
rtol=1e-5 * sc.units.one)).value
def absorption_correction(filename,
lambda_binning=(0.7, 10.35, 5615),
**mantid_args):
"""
This method is a straightforward wrapper exposing CylinderAbsorption
through scipp
CylinderAbsorption calculates an approximation of the
attenuation due to absorption and single scattering in a 'cylindrical'
shape.
Requirements:
- The instrument associated with the workspace must be fully defined.
(This being a WISH-centric implementation is done with the predefined
instr file)
Parameters
----------
filename: Path to the file with data
lambda_binning: min, max and number of steps for binning in wavelength
mantid_args: additional arguments to be passed to Mantid's
CylinderAbsorption method.
Returns
-------
Scipp dataset containing absorption correction in Wavelength units.
"""
# Create empty workspace with proper dimensions.
workspace = simpleapi.LoadEventNexus(filename,
MetaDataOnly=True,
LoadMonitors=False,
LoadLogs=False)
workspace.getAxis(0).setUnit('Wavelength')
# Rebin the resulting correction based on default WISH binning
lambda_min, lambda_max, number_bins = lambda_binning
bin_width = (lambda_max - lambda_min) / number_bins
workspace = simpleapi.Rebin(workspace,
params=[lambda_min, bin_width, lambda_max],
FullBinsOnly=True)
correction = simpleapi.CylinderAbsorption(workspace, **mantid_args)
return scn.from_mantid(correction)
def test_extract_energy_final():
# Efinal is often stored in a non-default parameter file
parameters = {
'IN16B': 'IN16B_silicon_311_Parameters.xml',
'IRIS': 'IRIS_mica_002_Parameters.xml',
'OSIRIS': 'OSIRIS_graphite_002_Parameters.xml',
'BASIS': 'BASIS_silicon_311_Parameters.xml'
}
unsupported = [
'ZEEMANS', 'MARS', 'IN10', 'IN13', 'IN16', 'VISION', 'VESUVIO'
]
for instr in _all_indirect(blacklist=unsupported):
out = _load_indirect_instrument(instr, parameters)
ds = scn.from_mantid(out)
efs = ds.coords["final_energy"]
assert not sc.all(sc.isnan(efs)).value
assert efs.unit == sc.Unit("meV")
def test_time_series_log_extraction():
import mantid.simpleapi as sapi
ws = sapi.CreateWorkspace(DataX=[0, 1], DataY=[1])
times = [
np.datetime64(t) for t in
['2021-01-01T00:00:00', '2021-01-01T00:30:00', '2021-01-01T00:50:00']
]
for i, t in enumerate(times):
sapi.AddTimeSeriesLog(ws, Name='time_log', Time=str(t), Value=float(i))
da = scn.from_mantid(ws)
assert da.attrs['time_log'].value.coords[
'time'].dtype == sc.DType.datetime64
# check times
assert sc.identical(
sc.Variable(dims=['time'],
values=np.array(times).astype('datetime64[ns]')),
da.attrs['time_log'].value.coords['time'])
# check values
assert sc.identical(sc.Variable(dims=['time'], values=np.arange(3.)),
da.attrs['time_log'].value.data)
sapi.DeleteWorkspace(ws)
def test_load_mcstas_data():
import mantid.simpleapi as mantid
wsg = mantid.LoadMcStas(scn.data.get_path('mcstas_sans.h5'),
OutputWorkspace="test_mcstas_sans_wsg")
ws = wsg[list(wsg.getNames()).index('EventData_test_mcstas_sans_wsg')]
da = scn.from_mantid(ws)
for i in range(ws.getNumberHistograms()):
np.testing.assert_array_equal(da.coords['tof'].values, ws.readX(i))
spec = ws.getSpectrum(i)
da_spec = da['tof', 0]['spectrum', i]
bin_sizes = da_spec.bins.size()
assert spec.getNumberEvents() == bin_sizes.value
np.testing.assert_array_equal(spec.getTofs(),
da_spec.bins.coords['tof'].values.values)
np.testing.assert_array_equal(
spec.getPulseTimesAsNumpy(),
da_spec.bins.coords['pulse_time'].value.values)
np.testing.assert_array_equal(spec.getWeights(),
da_spec.bins.data.value.values)
from mantid.simpleapi import Load, LoadDiffCal
import scippneutron as scn
ws = Load('PG3_4844_event.nxs')
ws = LoadDiffCal('PG3_golden.cal', InputWorkspace='ws', WorkspaceName='ws')
cal = scn.from_mantid(ws[0]).rename_dims({'row': 'spectrum'})
cal['tzero'].unit = 'us'
cal['difc'].unit = 'us/angstrom'
cal['difa'].unit = 'us/(angstrom*angstrom)'
cal.to_hdf5('PG3_4844_calibration.h5')
def test_from_mantid_LoadEmptyInstrument(self):
import mantid.simpleapi as mantid
ws = mantid.LoadEmptyInstrument(InstrumentName='PG3')
scn.from_mantid(ws)
