def runTest(self, mock_update_slider):
HelperTestingClass.__init__(self)
xmin = 5000
xmax = 10000
ws = CreateSampleWorkspace(NumBanks=2, BankPixelWidth=2, XMin=xmin, XMax=xmax) # two non-monitor spectra
ws.setX(0, hstack([2 * ws.readX(0)[0:-1], inf])) # change x limits of spectrum and put inf in last element
pres = SliceViewer(ws)
pres.view.data_view.plot_matrix(ws)
self.assertEqual(pres.view.data_view.get_axes_limits()[0], (xmin, xmax))
def runTest(self):
HelperTestingClass.__init__(self)
xmin = 5000
xmax = 10000
ws = CreateSampleWorkspace(NumBanks=1, NumMonitors=1, BankPixelWidth=1, XMin=xmin, XMax=xmax)
ws.setX(0, 2 * ws.readX(0)) # change x limits of monitor spectrum
pres = SliceViewer(ws)
pres.view.data_view.plot_matrix(ws)
self.assertEqual(pres.view.data_view.get_axes_limits()[0], (xmin, xmax))
def test_plot_matrix_xlimits_ignores_nans(self, mock_update_slider):
# need to mock update slider as doesn't handle inf when initialising SliceViewer in this manner
xmin = 5000
xmax = 10000
ws = CreateSampleWorkspace(NumBanks=2,
BankPixelWidth=2,
XMin=xmin,
XMax=xmax) # two non-monitor spectra
ws.setX(0, hstack(
[2 * ws.readX(0)[0:-1],
inf])) # change x limits of spectrum and put inf in last element
pres = SliceViewer(ws)
pres.view.data_view.plot_matrix(ws)
self.assertEqual(pres.view.data_view.get_axes_limits()[0],
(xmin, xmax))
class CorrectTOFTest(unittest.TestCase):
def setUp(self):
# create sample workspace
self.xmin = 2123.33867005 + 4005.75
self.xmax = 2123.33867005 + 7995.75
self._input_ws = CreateSampleWorkspace(Function="User Defined", UserDefinedFunction="name=LinearBackground, \
A0=0.3;name=Gaussian, PeakCentre=8190, Height=5, Sigma=75", NumBanks=2,
BankPixelWidth=1, XMin=self.xmin, XMax=self.xmax, BinWidth=10.5,
BankDistanceFromSample=4.0, SourceDistanceFromSample=1.4, OutputWorkspace="ws")
lognames = "wavelength,TOF1"
logvalues = "6.0,2123.33867005"
AddSampleLogMultiple(self._input_ws, lognames, logvalues)
# create EPP table
self._table = CreateEmptyTableWorkspace(OutputWorkspace="epptable")
self._table.addColumn(type="double", name="PeakCentre")
table_row = {'PeakCentre': 8189.5}
for i in range(2):
self._table.addRow(table_row)
def tearDown(self):
for wsname in ['ws', 'epptable']:
if AnalysisDataService.doesExist(wsname):
run_algorithm("DeleteWorkspace", Workspace=wsname)
def testCorrection(self):
# tests that correction is done properly
OutputWorkspaceName = "outputws1"
alg_test = run_algorithm("CorrectTOF", InputWorkspace=self._input_ws, EPPTable=self._table, OutputWorkspace=OutputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
wsoutput = AnalysisDataService.retrieve(OutputWorkspaceName)
velocity = h/(m_n*6.0e-10)
t_el = 4.0e+6/velocity
t_corr = np.arange(self.xmin, self.xmax + 1.0, 10.5) + t_el - (8189.5 - 2123.33867005)
self.assertTrue(np.allclose(t_corr, wsoutput.readX(0))) #sdd = 4
self.assertTrue(np.allclose(t_corr + t_el, wsoutput.readX(1))) #sdd = 8
run_algorithm("DeleteWorkspace", Workspace=wsoutput)
def testGroup(self):
# tests whether the group of workspaces is accepted as an input
ws2 = CloneWorkspace(self._input_ws)
group = GroupWorkspaces([self._input_ws, ws2])
OutputWorkspaceName = "output_wsgroup"
alg_test = run_algorithm("CorrectTOF", InputWorkspace='group', EPPTable=self._table, OutputWorkspace=OutputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
wsoutput = AnalysisDataService.retrieve(OutputWorkspaceName)
self.assertTrue(isinstance(wsoutput, WorkspaceGroup))
self.assertEqual(2, wsoutput.getNumberOfEntries())
run_algorithm("DeleteWorkspace", Workspace=group)
run_algorithm("DeleteWorkspace", Workspace=wsoutput)
def testConvertUnits(self):
# test whether CorrectTof+ConvertUnits+ConvertToDistribution will give the same result as TOFTOFConvertTOFToDeltaE
OutputWorkspaceName = "outputws1"
alg_test = run_algorithm("CorrectTOF", InputWorkspace=self._input_ws, EPPTable=self._table, OutputWorkspace=OutputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
wscorr = AnalysisDataService.retrieve(OutputWorkspaceName)
# convert units, convert to distribution
alg_cu = run_algorithm("ConvertUnits", InputWorkspace=wscorr, Target='DeltaE', EMode='Direct', EFixed=2.27, OutputWorkspace=OutputWorkspaceName+'_dE')
ws_dE = AnalysisDataService.retrieve(OutputWorkspaceName+'_dE')
alg_cd = run_algorithm("ConvertToDistribution", Workspace=ws_dE)
# create reference data for X axis
tof1 = 2123.33867005
dataX = self._input_ws.readX(0) - tof1
tel = 8189.5 - tof1
factor = m_n*1e+15/eV
newX = 0.5*factor*16.0*(1/tel**2 - 1/dataX**2)
# compare
# self.assertEqual(newX[0], ws_dE.readX(0)[0])
self.assertTrue(np.allclose(newX, ws_dE.readX(0), atol=0.01))
# create reference data for Y axis and compare to the output
tof = dataX[:-1] + 5.25
newY = self._input_ws.readY(0)*tof**3/(factor*10.5*16.0)
# compare
self.assertTrue(np.allclose(newY, ws_dE.readY(0), rtol=0.01))
run_algorithm("DeleteWorkspace", Workspace=ws_dE)
run_algorithm("DeleteWorkspace", Workspace=wscorr)
class CorrectTOFTest(unittest.TestCase):
def setUp(self):
# create sample workspace
self.xmin = 2123.33867005 + 4005.75
self.xmax = 2123.33867005 + 7995.75
self._input_ws = CreateSampleWorkspace(Function="User Defined", UserDefinedFunction="name=LinearBackground, \
A0=0.3;name=Gaussian, PeakCentre=8190, Height=5, Sigma=75", NumBanks=2,
BankPixelWidth=1, XMin=self.xmin, XMax=self.xmax, BinWidth=10.5,
BankDistanceFromSample=4.0, SourceDistanceFromSample=1.4, OutputWorkspace="ws")
lognames = "wavelength,TOF1"
logvalues = "6.0,2123.33867005"
AddSampleLogMultiple(self._input_ws, lognames, logvalues)
# create EPP table
self._table = CreateEmptyTableWorkspace(OutputWorkspace="epptable")
self._table.addColumn(type="double", name="PeakCentre")
table_row = {'PeakCentre': 8189.5}
for i in range(2):
self._table.addRow(table_row)
def tearDown(self):
for wsname in ['ws', 'epptable']:
if AnalysisDataService.doesExist(wsname):
run_algorithm("DeleteWorkspace", Workspace=wsname)
def testCorrection(self):
# tests that correction is done properly
OutputWorkspaceName = "outputws1"
alg_test = run_algorithm("CorrectTOF", InputWorkspace=self._input_ws, EPPTable=self._table, OutputWorkspace=OutputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
wsoutput = AnalysisDataService.retrieve(OutputWorkspaceName)
velocity = h/(m_n*6.0e-10)
t_el = 4.0e+6/velocity
t_corr = np.arange(self.xmin, self.xmax + 1.0, 10.5) + t_el - (8189.5 - 2123.33867005)
self.assertTrue(np.allclose(t_corr, wsoutput.readX(0))) #sdd = 4
self.assertTrue(np.allclose(t_corr + t_el, wsoutput.readX(1))) #sdd = 8
run_algorithm("DeleteWorkspace", Workspace=wsoutput)
def testGroup(self):
# tests whether the group of workspaces is accepted as an input
ws2 = CloneWorkspace(self._input_ws)
group = GroupWorkspaces([self._input_ws, ws2])
OutputWorkspaceName = "output_wsgroup"
alg_test = run_algorithm("CorrectTOF", InputWorkspace='group', EPPTable=self._table, OutputWorkspace=OutputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
wsoutput = AnalysisDataService.retrieve(OutputWorkspaceName)
self.assertTrue(isinstance(wsoutput, WorkspaceGroup))
self.assertEqual(2, wsoutput.getNumberOfEntries())
run_algorithm("DeleteWorkspace", Workspace=group)
run_algorithm("DeleteWorkspace", Workspace=wsoutput)
def testConvertUnits(self):
# test whether CorrectTof+ConvertUnits+ConvertToDistribution will give the same result as TOFTOFConvertTOFToDeltaE
OutputWorkspaceName = "outputws1"
alg_test = run_algorithm("CorrectTOF", InputWorkspace=self._input_ws, EPPTable=self._table, OutputWorkspace=OutputWorkspaceName)
self.assertTrue(alg_test.isExecuted())
wscorr = AnalysisDataService.retrieve(OutputWorkspaceName)
# convert units, convert to distribution
alg_cu = run_algorithm("ConvertUnits", InputWorkspace=wscorr, Target='DeltaE', EMode='Direct', EFixed=2.27, OutputWorkspace=OutputWorkspaceName+'_dE')
ws_dE = AnalysisDataService.retrieve(OutputWorkspaceName+'_dE')
alg_cd = run_algorithm("ConvertToDistribution", Workspace=ws_dE)
# create reference data for X axis
tof1 = 2123.33867005
dataX = self._input_ws.readX(0) - tof1
tel = 8189.5 - tof1
factor = m_n*1e+15/eV
newX = 0.5*factor*16.0*(1/tel**2 - 1/dataX**2)
# compare
# self.assertEqual(newX[0], ws_dE.readX(0)[0])
self.assertTrue(np.allclose(newX, ws_dE.readX(0), atol=0.01))
# create reference data for Y axis and compare to the output
tof = dataX[:-1] + 5.25
newY = self._input_ws.readY(0)*tof**3/(factor*10.5*16.0)
# compare
self.assertTrue(np.allclose(newY, ws_dE.readY(0), rtol=0.01))
run_algorithm("DeleteWorkspace", Workspace=ws_dE)
run_algorithm("DeleteWorkspace", Workspace=wscorr)
