def load_files(self, filenames_string):
self._last_added = []
filenames = [name.strip() for name in filenames_string.split(",")]
for filename in filenames:
ws_name = self._generate_workspace_name(filename)
if ws_name not in self._loaded_workspaces:
try:
if not ADS.doesExist(ws_name):
ws = Load(filename, OutputWorkspace=ws_name)
else:
ws = ADS.retrieve(ws_name)
if ws.getNumberHistograms() == 1:
self._loaded_workspaces[ws_name] = ws
if ws_name not in self._bg_sub_workspaces:
self._bg_sub_workspaces[ws_name] = None
if ws_name not in self._bg_params:
self._bg_params[ws_name] = []
self._last_added.append(ws_name)
else:
logger.warning(
f"Invalid number of spectra in workspace {ws_name}. Skipping loading of file.")
except RuntimeError as e:
logger.error(
f"Failed to load file: {filename}. Error: {e}. \n Continuing loading of other files.")
else:
logger.warning(f"File {ws_name} has already been loaded")
self.update_log_workspace_group()
def load_files(self, filenames_string, xunit):
self._last_added = []
filenames = [name.strip() for name in filenames_string.split(",")]
for filename in filenames:
ws_name = self._generate_workspace_name(filename, xunit)
if ws_name not in self._loaded_workspaces:
try:
if not ADS.doesExist(ws_name):
ws = Load(filename, OutputWorkspace=ws_name)
if xunit != "TOF":
ConvertUnits(InputWorkspace=ws, OutputWorkspace=ws_name, Target=xunit)
else:
ws = ADS.retrieve(ws_name)
if ws.getNumberHistograms() == 1:
self._loaded_workspaces[ws_name] = ws
if ws_name not in self._background_workspaces:
self._background_workspaces[ws_name] = None
self._last_added.append(ws_name)
self.add_log_to_table(ws_name, ws)
else:
logger.warning(
f"Invalid number of spectra in workspace {ws_name}. Skipping loading of file.")
except RuntimeError as e:
logger.error(
f"Failed to load file: {filename}. Error: {e}. \n Continuing loading of other files.")
else:
logger.warning(f"File {ws_name} has already been loaded")
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 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 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 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 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)
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)
def load_files(self, filenames_string):
self._last_added = []
filenames = [name.strip() for name in filenames_string.split(",")]
for filename in filenames:
ws_name = self._generate_workspace_name(filename)
try:
ws = Load(filename, OutputWorkspace=ws_name)
if ws.getNumberHistograms() == 1:
self._loaded_workspaces[ws_name] = ws
self._last_added.append(ws_name)
else:
logger.warning(
"Invalid number of spectra in workspace {}. Skipping loading of file."
.format(ws_name))
except RuntimeError as e:
logger.error(
"Failed to load file: {}. Error: {}. \n Continuing loading of other files."
.format(filename, e))
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 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_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_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())
def test_Load_call_with_all_keyword_args_executes_correctly(self):
raw = Load(Filename='IRS21360.raw', SpectrumMax=1)
self.assertEqual(1, raw.getNumberHistograms())
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.assertEqual(116, 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())
