def test_DNSVanadiumCorrection_Groups(self):
outputWorkspaceName = "DNSComputeDetCorrCoefsTest_Test1"
dataY = np.linspace(2, 13.5, 24)
sfvana2 = create_fake_dns_workspace('sfvana2',
dataY=dataY,
flipper='ON',
angle=-8.54,
loadinstrument=True)
nsfvana2 = create_fake_dns_workspace('nsfvana2',
dataY=dataY,
flipper='OFF',
angle=-8.54,
loadinstrument=True)
vanagroupsf = GroupWorkspaces([self.sfvanaws, sfvana2])
vanagroupnsf = GroupWorkspaces([self.nsfvanaws, nsfvana2])
dataY.fill(1.5)
sfbg2 = create_fake_dns_workspace('sfbg2',
dataY=dataY,
flipper='ON',
angle=-8.54,
loadinstrument=True)
nsfbg2 = create_fake_dns_workspace('nsfbg2',
dataY=dataY,
flipper='OFF',
angle=-8.54,
loadinstrument=True)
bggroupsf = GroupWorkspaces([self.sfbkgrws, sfbg2])
bggroupnsf = GroupWorkspaces([self.nsfbkgrws, nsfbg2])
alg_test = run_algorithm(
"DNSComputeDetEffCorrCoefs",
VanadiumWorkspaces=[vanagroupsf, vanagroupnsf],
BackgroundWorkspaces=[bggroupsf, bggroupnsf],
OutputWorkspace=outputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
# check whether the data are correct
group = AnalysisDataService.retrieve(outputWorkspaceName)
self.assertTrue(isinstance(group, WorkspaceGroup))
self.assertEqual(2, group.getNumberOfEntries())
res1 = group.getItem(0)
res2 = group.getItem(1)
# dimensions
self.assertEqual(24, res1.getNumberHistograms())
self.assertEqual(24, res2.getNumberHistograms())
self.assertEqual(2, res1.getNumDims())
self.assertEqual(2, res2.getNumDims())
# reference data
refdata = np.linspace(0.08, 1.92, 24)
# data array
for i in range(24):
self.assertAlmostEqual(refdata[i], res1.readY(i)[0])
self.assertAlmostEqual(refdata[i], res2.readY(i)[0])
wslist = [
outputWorkspaceName, 'sfvana2', 'nsfvana2', 'sfbg2', 'nsfbg2'
]
for wsname in wslist:
run_algorithm("DeleteWorkspace", Workspace=wsname)
return
def setUp(self):
dataY = np.zeros(24)
dataY.fill(1.5)
self.sfbkgrws = create_fake_dns_workspace('sfbkgrws', dataY=dataY, flipper='ON', angle=-7.53, loadinstrument=True)
self.nsfbkgrws = create_fake_dns_workspace('nsfbkgrws', dataY=dataY, flipper='OFF', angle=-7.53, loadinstrument=True)
dataY = np.linspace(2, 13.5, 24)
self.sfvanaws = create_fake_dns_workspace('sfvanaws', dataY=dataY, flipper='ON', angle=-7.53, loadinstrument=True)
self.nsfvanaws = create_fake_dns_workspace('nsfvanaws', dataY=dataY, flipper='OFF', angle=-7.53, loadinstrument=True)
def setUp(self):
dataY = np.zeros(24)
dataY.fill(1.5)
self.__bkgrws = create_fake_dns_workspace('__bkgrws', dataY=dataY)
dataY = np.linspace(2, 13.5, 24)
self.__vanaws = create_fake_dns_workspace('__vanaws', dataY=dataY)
dataY = np.arange(1, 25)
self.__dataws = create_fake_dns_workspace('__dataws', dataY=dataY)
def test_DNSFRVanaCorrection(self):
outputWorkspaceName = "DNSFlippingRatioCorrTest_Test6"
# create fake vanadium data workspaces
dataY = np.array([
1811., 2407., 3558., 3658., 3352., 2321., 2240., 2617., 3245.,
3340., 3338., 3310., 2744., 3212., 1998., 2754., 2791., 2509.,
3045., 3429., 3231., 2668., 3373., 2227.
])
__sf_vanaws = create_fake_dns_workspace('__sf_vanaws',
dataY=dataY / 58.0,
flipper='ON')
self.workspaces.append('__sf_vanaws')
dataY = np.array([
2050., 1910., 2295., 2236., 1965., 1393., 1402., 1589., 1902.,
1972., 2091., 1957., 1593., 1952., 1232., 1720., 1689., 1568.,
1906., 2001., 2051., 1687., 1975., 1456.
])
__nsf_vanaws = create_fake_dns_workspace('__nsf_vanaws',
dataY=dataY / 58.0,
flipper='OFF')
self.workspaces.append('__nsf_vanaws')
# consider normalization=1.0 as set in self._create_fake_workspace
dataws_sf = __sf_vanaws - self.__sf_bkgrws
dataws_nsf = __nsf_vanaws - self.__nsf_bkgrws
alg_test = run_algorithm("DNSFlippingRatioCorr",
SFDataWorkspace=dataws_sf,
NSFDataWorkspace=dataws_nsf,
SFNiCrWorkspace=self.__sf_nicrws.getName(),
NSFNiCrWorkspace=self.__nsf_nicrws.getName(),
SFBkgrWorkspace=self.__sf_bkgrws.getName(),
NSFBkgrWorkspace=self.__nsf_bkgrws.getName(),
SFOutputWorkspace=outputWorkspaceName + 'SF',
NSFOutputWorkspace=outputWorkspaceName +
'NSF')
self.assertTrue(alg_test.isExecuted())
# check whether the data are correct
ws_sf = AnalysisDataService.retrieve(outputWorkspaceName + 'SF')
ws_nsf = AnalysisDataService.retrieve(outputWorkspaceName + 'NSF')
# dimensions
self.assertEqual(24, ws_sf.getNumberHistograms())
self.assertEqual(24, ws_nsf.getNumberHistograms())
self.assertEqual(2, ws_sf.getNumDims())
self.assertEqual(2, ws_nsf.getNumDims())
# data array: for vanadium ratio sf/nsf must be around 2
ws = ws_sf / ws_nsf
for i in range(24):
self.assertAlmostEqual(2.0, np.around(ws.readY(i)))
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'SF')
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'NSF')
run_algorithm("DeleteWorkspace", Workspace=dataws_sf)
run_algorithm("DeleteWorkspace", Workspace=dataws_nsf)
run_algorithm("DeleteWorkspace", Workspace=ws)
return
def setUp(self):
self.workspaces = []
for i in range(4):
angle = -7.5 - i*0.5
wsname = "__testws" + str(i)
create_fake_dns_workspace(wsname, angle=angle, loadinstrument=True)
self.workspaces.append(wsname)
# create reference values
angles = np.empty(0)
for j in range(4):
a = 7.5 + j*0.5
angles = np.hstack([angles, np.array([i*5 + a for i in range(24)])])
self.angles = np.sort(angles)
def setUp(self):
self.workspaces = []
for i in range(4):
angle = -7.5 - i*0.5
wsname = "__testws" + str(i)
create_fake_dns_workspace(wsname, angle=angle, loadinstrument=True)
self.workspaces.append(wsname)
# create reference values
angles = np.empty(0)
for j in range(4):
a = 7.5 + j*0.5
angles = np.hstack([angles, np.array([i*5 + a for i in range(24)])])
self.angles = np.sort(angles)
def setUp(self):
dataY = np.array([2997., 2470., 2110., 1818., 840., 1095., 944., 720., 698., 699., 745., 690.,
977., 913., 906., 1007., 1067., 1119., 1467., 1542., 2316., 1536., 1593., 1646.])
self.__sf_bkgrws = create_fake_dns_workspace('__sf_bkgrws', dataY=dataY/620.0, flipper='ON')
self.workspaces.append('__sf_bkgrws')
dataY = np.array([14198., 7839., 4386., 3290., 1334., 1708., 1354., 1026., 958., 953., 888., 847.,
1042., 1049., 1012., 1116., 1294., 1290., 1834., 1841., 2740., 1750., 1965., 1860.])
self.__nsf_bkgrws = create_fake_dns_workspace('__nsf_bkgrws', dataY=dataY/619.0, flipper='OFF')
self.workspaces.append('__nsf_bkgrws')
dataY = np.array([5737., 5761., 5857., 5571., 4722., 5102., 4841., 4768., 5309., 5883., 5181., 4455.,
4341., 4984., 3365., 4885., 4439., 4103., 4794., 14760., 10516., 4445., 5460., 3942.])
self.__nsf_nicrws = create_fake_dns_workspace('__nsf_nicrws', dataY=dataY/58.0, flipper='OFF')
self.workspaces.append('__nsf_nicrws')
dataY = np.array([2343., 2270., 2125., 2254., 1534., 1863., 1844., 1759., 1836., 2030., 1848., 1650.,
1555., 1677., 1302., 1750., 1822., 1663., 2005., 4025., 3187., 1935., 2331., 2125.])
self.__sf_nicrws = create_fake_dns_workspace('__sf_nicrws', dataY=dataY/295.0, flipper='ON')
self.workspaces.append('__sf_nicrws')
def setUp(self):
dataY = np.array([2997., 2470., 2110., 1818., 840., 1095., 944., 720., 698., 699., 745., 690.,
977., 913., 906., 1007., 1067., 1119., 1467., 1542., 2316., 1536., 1593., 1646.])
self.__sf_bkgrws = create_fake_dns_workspace('__sf_bkgrws', dataY=dataY/620.0, flipper='ON')
self.workspaces.append('__sf_bkgrws')
dataY = np.array([14198., 7839., 4386., 3290., 1334., 1708., 1354., 1026., 958., 953., 888., 847.,
1042., 1049., 1012., 1116., 1294., 1290., 1834., 1841., 2740., 1750., 1965., 1860.])
self.__nsf_bkgrws = create_fake_dns_workspace('__nsf_bkgrws', dataY=dataY/619.0, flipper='OFF')
self.workspaces.append('__nsf_bkgrws')
dataY = np.array([5737., 5761., 5857., 5571., 4722., 5102., 4841., 4768., 5309., 5883., 5181., 4455.,
4341., 4984., 3365., 4885., 4439., 4103., 4794., 14760., 10516., 4445., 5460., 3942.])
self.__nsf_nicrws = create_fake_dns_workspace('__nsf_nicrws', dataY=dataY/58.0, flipper='OFF')
self.workspaces.append('__nsf_nicrws')
dataY = np.array([2343., 2270., 2125., 2254., 1534., 1863., 1844., 1759., 1836., 2030., 1848., 1650.,
1555., 1677., 1302., 1750., 1822., 1663., 2005., 4025., 3187., 1935., 2331., 2125.])
self.__sf_nicrws = create_fake_dns_workspace('__sf_nicrws', dataY=dataY/295.0, flipper='ON')
self.workspaces.append('__sf_nicrws')
def test_DNSFRVanaCorrection(self):
outputWorkspaceName = "DNSFlippingRatioCorrTest_Test6"
# create fake vanadium data workspaces
dataY = np.array([1811., 2407., 3558., 3658., 3352., 2321., 2240., 2617., 3245., 3340., 3338., 3310.,
2744., 3212., 1998., 2754., 2791., 2509., 3045., 3429., 3231., 2668., 3373., 2227.])
__sf_vanaws = create_fake_dns_workspace('__sf_vanaws', dataY=dataY/58.0, flipper='ON')
self.workspaces.append('__sf_vanaws')
dataY = np.array([2050., 1910., 2295., 2236., 1965., 1393., 1402., 1589., 1902., 1972., 2091., 1957.,
1593., 1952., 1232., 1720., 1689., 1568., 1906., 2001., 2051., 1687., 1975., 1456.])
__nsf_vanaws = create_fake_dns_workspace('__nsf_vanaws', dataY=dataY/58.0, flipper='OFF')
self.workspaces.append('__nsf_vanaws')
# consider normalization=1.0 as set in self._create_fake_workspace
dataws_sf = __sf_vanaws - self.__sf_bkgrws
dataws_nsf = __nsf_vanaws - self.__nsf_bkgrws
alg_test = run_algorithm("DNSFlippingRatioCorr", SFDataWorkspace=dataws_sf,
NSFDataWorkspace=dataws_nsf, SFNiCrWorkspace=self.__sf_nicrws.getName(),
NSFNiCrWorkspace=self.__nsf_nicrws.getName(), SFBkgrWorkspace=self.__sf_bkgrws.getName(),
NSFBkgrWorkspace=self.__nsf_bkgrws.getName(), SFOutputWorkspace=outputWorkspaceName+'SF',
NSFOutputWorkspace=outputWorkspaceName+'NSF')
self.assertTrue(alg_test.isExecuted())
# check whether the data are correct
ws_sf = AnalysisDataService.retrieve(outputWorkspaceName + 'SF')
ws_nsf = AnalysisDataService.retrieve(outputWorkspaceName + 'NSF')
# dimensions
self.assertEqual(24, ws_sf.getNumberHistograms())
self.assertEqual(24, ws_nsf.getNumberHistograms())
self.assertEqual(2, ws_sf.getNumDims())
self.assertEqual(2, ws_nsf.getNumDims())
# data array: for vanadium ratio sf/nsf must be around 2
ws = ws_sf/ws_nsf
for i in range(24):
self.assertAlmostEqual(2.0, np.around(ws.readY(i)))
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'SF')
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'NSF')
run_algorithm("DeleteWorkspace", Workspace=dataws_sf)
run_algorithm("DeleteWorkspace", Workspace=dataws_nsf)
run_algorithm("DeleteWorkspace", Workspace=ws)
return
def test_DNSVanadiumCorrection_Groups(self):
outputWorkspaceName = "DNSComputeDetCorrCoefsTest_Test1"
dataY = np.linspace(2, 13.5, 24)
sfvana2 = create_fake_dns_workspace('sfvana2', dataY=dataY, flipper='ON', angle=-8.54, loadinstrument=True)
nsfvana2 = create_fake_dns_workspace('nsfvana2', dataY=dataY, flipper='OFF', angle=-8.54, loadinstrument=True)
vanagroupsf = GroupWorkspaces([self.sfvanaws, sfvana2])
vanagroupnsf = GroupWorkspaces([self.nsfvanaws, nsfvana2])
dataY.fill(1.5)
sfbg2 = create_fake_dns_workspace('sfbg2', dataY=dataY, flipper='ON', angle=-8.54, loadinstrument=True)
nsfbg2 = create_fake_dns_workspace('nsfbg2', dataY=dataY, flipper='OFF', angle=-8.54, loadinstrument=True)
bggroupsf = GroupWorkspaces([self.sfbkgrws, sfbg2])
bggroupnsf = GroupWorkspaces([self.nsfbkgrws, nsfbg2])
alg_test = run_algorithm("DNSComputeDetEffCorrCoefs", VanadiumWorkspaces=[vanagroupsf, vanagroupnsf],
BackgroundWorkspaces=[bggroupsf, bggroupnsf], OutputWorkspace=outputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
# check whether the data are correct
group = AnalysisDataService.retrieve(outputWorkspaceName)
self.assertTrue(isinstance(group, WorkspaceGroup))
self.assertEqual(2, group.getNumberOfEntries())
res1 = group.getItem(0)
res2 = group.getItem(1)
# dimensions
self.assertEqual(24, res1.getNumberHistograms())
self.assertEqual(24, res2.getNumberHistograms())
self.assertEqual(2, res1.getNumDims())
self.assertEqual(2, res2.getNumDims())
# reference data
refdata = np.linspace(0.08, 1.92, 24)
# data array
for i in range(24):
self.assertAlmostEqual(refdata[i], res1.readY(i))
self.assertAlmostEqual(refdata[i], res2.readY(i))
wslist = [outputWorkspaceName, 'sfvana2', 'nsfvana2', 'sfbg2', 'nsfbg2']
for wsname in wslist:
run_algorithm("DeleteWorkspace", Workspace=wsname)
return
def test_DNSDoubleSpinFlip(self):
outputWorkspaceName = "DNSFlippingRatioCorrTest_Test7"
f = 0.2
# create fake vanadium data workspaces
dataY = np.array([1811., 2407., 3558., 3658., 3352., 2321., 2240., 2617., 3245., 3340., 3338., 3310.,
2744., 3212., 1998., 2754., 2791., 2509., 3045., 3429., 3231., 2668., 3373., 2227.])
__sf_vanaws = create_fake_dns_workspace('__sf_vanaws', dataY=dataY/58.0, flipper='ON')
self.workspaces.append('__sf_vanaws')
dataY = np.array([2050., 1910., 2295., 2236., 1965., 1393., 1402., 1589., 1902., 1972., 2091., 1957.,
1593., 1952., 1232., 1720., 1689., 1568., 1906., 2001., 2051., 1687., 1975., 1456.])
__nsf_vanaws = create_fake_dns_workspace('__nsf_vanaws', dataY=dataY/58.0, flipper='OFF')
self.workspaces.append('__nsf_vanaws')
# consider normalization=1.0 as set in self._create_fake_workspace
dataws_sf = __sf_vanaws - self.__sf_bkgrws
dataws_nsf = __nsf_vanaws - self.__nsf_bkgrws
alg_test = run_algorithm("DNSFlippingRatioCorr", SFDataWorkspace=dataws_sf,
NSFDataWorkspace=dataws_nsf, SFNiCrWorkspace=self.__sf_nicrws.getName(),
NSFNiCrWorkspace=self.__nsf_nicrws.getName(), SFBkgrWorkspace=self.__sf_bkgrws.getName(),
NSFBkgrWorkspace=self.__nsf_bkgrws.getName(), SFOutputWorkspace=outputWorkspaceName+'SF',
NSFOutputWorkspace=outputWorkspaceName+'NSF', DoubleSpinFlipScatteringProbability=0.0)
self.assertTrue(alg_test.isExecuted())
alg_test = run_algorithm("DNSFlippingRatioCorr", SFDataWorkspace=dataws_sf,
NSFDataWorkspace=dataws_nsf, SFNiCrWorkspace=self.__sf_nicrws.getName(),
NSFNiCrWorkspace=self.__nsf_nicrws.getName(), SFBkgrWorkspace=self.__sf_bkgrws.getName(),
NSFBkgrWorkspace=self.__nsf_bkgrws.getName(), SFOutputWorkspace=outputWorkspaceName+'SF1',
NSFOutputWorkspace=outputWorkspaceName+'NSF1', DoubleSpinFlipScatteringProbability=f)
self.assertTrue(alg_test.isExecuted())
# check whether the data are correct
ws_sf = AnalysisDataService.retrieve(outputWorkspaceName + 'SF')
ws_sf1 = AnalysisDataService.retrieve(outputWorkspaceName + 'SF1')
ws_nsf = AnalysisDataService.retrieve(outputWorkspaceName + 'NSF')
ws_nsf1 = AnalysisDataService.retrieve(outputWorkspaceName + 'NSF1')
# dimensions
self.assertEqual(24, ws_sf.getNumberHistograms())
self.assertEqual(24, ws_sf1.getNumberHistograms())
self.assertEqual(24, ws_nsf.getNumberHistograms())
self.assertEqual(24, ws_nsf1.getNumberHistograms())
self.assertEqual(2, ws_sf.getNumDims())
self.assertEqual(2, ws_sf1.getNumDims())
self.assertEqual(2, ws_nsf.getNumDims())
self.assertEqual(2, ws_nsf1.getNumDims())
# data array: sf must not change
for i in range(24):
self.assertAlmostEqual(ws_sf.readY(i), ws_sf1.readY(i))
# data array: nsf1 = nsf - sf*f
nsf = np.array(ws_nsf.extractY())
sf = np.array(ws_sf.extractY())
refdata = nsf - sf*f
for i in range(24):
self.assertAlmostEqual(refdata[i], ws_nsf1.readY(i))
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'SF')
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'SF1')
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'NSF')
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName + 'NSF1')
run_algorithm("DeleteWorkspace", Workspace=dataws_sf)
run_algorithm("DeleteWorkspace", Workspace=dataws_nsf)
return
