Fix unit tests. Refs #11824

Code/Mantid/Framework/PythonInterface/plugins/algorithms/LRScalingFactors.py

@@ -107,7 +107,7 @@ def PyExec(self):
                 peak_range[2*i] = x_min
                 peak_range[2*i+1] = x_max
         elif len(peak_range) < 2:
-            raise RuntimeError, "SignalPeakPixelRange should have a length of at least 2."
+            raise RuntimeError("SignalPeakPixelRange should have a length of at least 2.")
 
         if len(background_range)==2:
             x_min = int(background_range[0])
@@ -117,12 +117,12 @@ def PyExec(self):
                 background_range[2*i] = x_min
                 background_range[2*i+1] = x_max
         elif len(background_range) < 2:
-            raise RuntimeError, "SignalBackgroundPixelRange should have a length of at least 2."
+            raise RuntimeError("SignalBackgroundPixelRange should have a length of at least 2.")
 
         # Check that the peak range arrays are of the proper length
         if not (len(peak_range) == 2*len(data_runs) \
                 and len(background_range) == 2*len(data_runs)):
-            raise RuntimeError, "Supplied peak/background arrays should be of the same length as the run array."
+            raise RuntimeError("Supplied peak/background arrays should be of the same length as the run array.")
 
         # Slit information for the previous run (see loop below)
         previous_slits = None
@@ -166,7 +166,7 @@ def PyExec(self):
             if wavelength is None:
                 wavelength = wl
             elif abs(wl-wavelength) > 0.2:
-                raise RuntimeError, "Supplied runs don't have matching wavelengths."
+                raise RuntimeError("Supplied runs don't have matching wavelengths.")
 
             peak = [int(peak_range[2*i]), int(peak_range[2*i+1])]
             background = [int(background_range[2*i]), int(background_range[2*i+1])]
@@ -179,7 +179,7 @@ def PyExec(self):
             # attenuator.
             if have_attenuator_info is True:
                 if attenuators[i] < n_attenuator:
-                    raise RuntimeError, "Runs were not supplied in increasing number of attenuators."
+                    raise RuntimeError("Runs were not supplied in increasing number of attenuators.")
                 n_attenuator = attenuators[i]
 
             is_reference = False
@@ -203,7 +203,7 @@ def PyExec(self):
             # If the number of attenuators is zero, skip.
             if n_attenuator == 0:
                 if references.has_key(0):
-                    raise RuntimeError, "More than one run with zero attenuator was supplied."
+                    raise RuntimeError("More than one run with zero attenuator was supplied.")
                 references[0] = {'index': i,
                                  'run': run,
                                  'ref_ws': workspace_name,
@@ -235,7 +235,7 @@ def PyExec(self):
                 # Divide by the reference for this number of attenuators
                 # and multiply by the reference ratio
                 if not references.has_key(n_attenuator):
-                    raise RuntimeError, "No reference for %s attenuators: check run ordering." % n_attenuator
+                    raise RuntimeError("No reference for %s attenuators: check run ordering." % n_attenuator)
                 f_ws = "F_%s_%s" % (run, n_attenuator)
                 Divide(LHSWorkspace=workspace_name,
                        RHSWorkspace=references[n_attenuator]['ref_ws'],

Code/Mantid/Framework/PythonInterface/plugins/algorithms/LiquidsReflectometryReduction.py

@@ -291,7 +291,7 @@ def PyExec(self):
 
         # Sanity check
         if sum(data_y) == 0:
-            raise RuntimeError, "The reflectivity is all zeros: check your peak selection"
+            raise RuntimeError("The reflectivity is all zeros: check your peak selection")
 
         # Avoid leaving trash behind
         for ws in ['ws_event_data', 'normalized_data', 'q_workspace']:
@@ -342,7 +342,7 @@ def process_data(self, workspace, tof_range, crop_low_res, low_res_range,
             error_msg = "Requested TOF range does not match data for %s: " % str(workspace)
             error_msg += "[%g, %g] found [%g, %g]" % (tof_range[0], tof_range[1],
                                                       tof_min, tof_max)
-            raise RuntimeError, error_msg
+            raise RuntimeError(error_msg)
 
         tof_step = self.getProperty("TOFSteps").value
         workspace = Rebin(InputWorkspace=workspace, Params=[0, tof_step, tof_max],

Code/Mantid/Framework/PythonInterface/plugins/algorithms/LoadLogPropertyTable.py

@@ -55,10 +55,9 @@ def getGeneralLogValue(self,ws,name,begin):
                 v=v.unfiltered()
             for tt in v.times:
                 times2.append((datetime.datetime(*(time.strptime(str(tt),"%Y-%m-%dT%H:%M:%S")[0:6]))-begin).total_seconds())
-        except AttributeError:
+        except:
             #print "probably not a time series"
             pass
-
         if name[0:8]=="Beamlog_" and (name.find("Counts")>0 or name.find("Frames")>0):
             i=bisect.bisect_right(times2,2) # allowance for "slow" clearing of DAE
             #print "returning max beam log, list cut 0:",i,":",len(times2)

Code/Mantid/Framework/PythonInterface/plugins/algorithms/RetrieveRunInfo.py

@@ -116,7 +116,7 @@ def __init__(self, filenames):
         # Validate.
         if not isinstance(filenames, list):
             raise TypeError("Expected a list.")
-        if not all([s._is_string for s in filenames]):
+        if not all([self._is_string(s) for s in filenames]):
             raise TypeError("Expected a list of strings.")
         if len(filenames) < 1:
             raise ValueError("Expected at least one filename.")

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/EQSANSAzimuthalAverage1D.py

@@ -154,7 +154,7 @@ def _with_frame_skipping(self, source_aperture_radius):
         if workspace.getRun().hasProperty("wavelength_max"):
             wl_max_f1 = workspace.getRun().getProperty("wavelength_max").value
         if wl_min_f1 is None and wl_max_f1 is None:
-            raise RuntimeError, "Could not get the wavelength band for frame 1"
+            raise RuntimeError("Could not get the wavelength band for frame 1")
 
         # Second frame
         wl_min_f2 = None
@@ -164,7 +164,7 @@ def _with_frame_skipping(self, source_aperture_radius):
         if workspace.getRun().hasProperty("wavelength_max_frame2"):
             wl_max_f2 = workspace.getRun().getProperty("wavelength_max_frame2").value
         if wl_min_f2 is None and wl_max_f2 is None:
-            raise RuntimeError, "Could not get the wavelength band for frame 2"
+            raise RuntimeError("Could not get the wavelength band for frame 2")
 
         # Compute binning
         if independent_binning:
@@ -369,7 +369,7 @@ def _get_binning(self, workspace, wavelength_min, wavelength_max):
                 beam_ctr_x = property_manager.getProperty("LatestBeamCenterX").value
                 beam_ctr_y = property_manager.getProperty("LatestBeamCenterY").value
             else:
-                raise RuntimeError, "No beam center information can be found on the data set"
+                raise RuntimeError("No beam center information can be found on the data set")
 
         # Q min is one pixel from the center, unless we have the beam trap size
         if workspace.getRun().hasProperty("beam-trap-diameter"):

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/EQSANSDirectBeamTransmission.py

@@ -164,12 +164,12 @@ def _crop_and_compute(wl_min_prop, wl_max_prop, suffix):
                 if workspace.getRun().hasProperty(wl_min_prop):
                     wl_min = workspace.getRun().getProperty(wl_min_prop).value
                 else:
-                    raise RuntimeError, "DirectBeamTransmission could not retrieve the %s property" % wl_min_prop
+                    raise RuntimeError("DirectBeamTransmission could not retrieve the %s property" % wl_min_prop)
 
                 if workspace.getRun().hasProperty(wl_max_prop):
                     wl_max = workspace.getRun().getProperty(wl_max_prop).value
                 else:
-                    raise RuntimeError, "DirectBeamTransmission could not retrieve the %s property" % wl_max_prop
+                    raise RuntimeError("DirectBeamTransmission could not retrieve the %s property" % wl_max_prop)
 
                 rebin_params = "%4.1f,%4.1f,%4.1f" % (wl_min, 0.1, wl_max)
                 alg = TransmissionUtils.simple_algorithm("Rebin",\

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/HFIRSANSReduction.py

@@ -31,7 +31,7 @@ def _multiple_load(self, data_file, workspace,
         #   Make sure we process a list of files written as a string
         def _load_data(filename, output_ws):
             if not property_manager.existsProperty("LoadAlgorithm"):
-                raise RuntimeError, "SANS reduction not set up properly: missing load algorithm"
+                raise RuntimeError("SANS reduction not set up properly: missing load algorithm")
             p=property_manager.getProperty("LoadAlgorithm")
             alg=Algorithm.fromString(p.valueAsStr)
             alg.setProperty("Filename", filename)

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/OSIRISDiffractionReduction.py

@@ -18,9 +18,9 @@
     17.09e4: tuple([10.4, 11.6]),\
     18.86e4: tuple([11.0, 12.5])}\
 
-""" A "wrapper" class for a map, which maps workspaces from their corresponding
-time regimes.
-"""
+# A "wrapper" class for a map, which maps workspaces from their corresponding
+#time regimes.
+
 class DRangeToWsMap(object):
 
     def __init__(self):

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/ReactorSANSResolution.py

@@ -72,7 +72,7 @@ def PyExec(self):
             for i in range(len(input_ws.readX(0))):
                 input_ws.dataDx(0)[i] = math.sqrt(res_factor+math.pow((input_ws.readX(0)[i]*d_wvl), 2)/6.0)
         else:
-            raise RuntimeError, "ReactorSANSResolution could not find all the run parameters needed to compute the resolution."
+            raise RuntimeError("ReactorSANSResolution could not find all the run parameters needed to compute the resolution.")
 
 
 AlgorithmFactory.subscribe(ReactorSANSResolution)

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/SANSAbsoluteScale.py

@@ -86,7 +86,7 @@ def PyExec(self):
             self.setProperty("OutputMessage", msg)
             return
 
-    #pylint: disable=too-many-locals
+    #pylint: disable=too-many-locals,too-many-branches
     def _hfir_scaling(self, property_manager):
         property_manager_name = self.getProperty("ReductionProperties").value
         input_ws = self.getProperty("InputWorkspace").value
@@ -103,7 +103,7 @@ def _hfir_scaling(self, property_manager):
         def _load_data(filename, output_ws):
             if not property_manager.existsProperty("LoadAlgorithm"):
                 Logger("SANSDirectBeamTransmission").error("SANS reduction not set up properly: missing load algorithm")
-                raise RuntimeError, "SANS reduction not set up properly: missing load algorithm"
+                raise RuntimeError("SANS reduction not set up properly: missing load algorithm")
             p=property_manager.getProperty("LoadAlgorithm")
             alg=Algorithm.fromString(p.valueAsStr)
             alg.setChild(True)
@@ -145,7 +145,7 @@ def _load_data(filename, output_ws):
                 beam_diameter = ref_ws.getRun().getProperty("beam-diameter").value
                 Logger("SANSAbsoluteScale").debug("Found beamstop diameter: %g" % beam_diameter)
             else:
-                raise RuntimeError, "AbsoluteScale could not read the beam radius and none was provided"
+                raise RuntimeError("AbsoluteScale could not read the beam radius and none was provided")
 
         # Apply sensitivity correction
         apply_sensitivity = self.getProperty("ApplySensitivity").value
@@ -199,7 +199,7 @@ def _load_data(filename, output_ws):
         if pixel_size_param is not None:
             pixel_size = pixel_size_param[0]
         else:
-            raise RuntimeError, "AbsoluteScale could not read the pixel size"
+            raise RuntimeError("AbsoluteScale could not read the pixel size")
 
         attenuator_trans = self.getProperty("AttenuatorTransmission").value
         # (detector count rate)/(attenuator transmission)/(monitor rate)*(pixel size/SDD)**2

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/SANSAzimuthalAverage1D.py

@@ -78,11 +78,11 @@ def PyExec(self):
             x = workspace.dataX(1)
             x_length = len(x)
             if x_length < 2:
-                raise RuntimeError, "Azimuthal averaging expects at least one wavelength bin"
+                raise RuntimeError("Azimuthal averaging expects at least one wavelength bin")
             wavelength_max = (x[x_length-2]+x[x_length-1])/2.0
             wavelength_min = (x[0]+x[1])/2.0
             if wavelength_min==0 or wavelength_max==0:
-                raise RuntimeError, "Azimuthal averaging needs positive wavelengths"
+                raise RuntimeError("Azimuthal averaging needs positive wavelengths")
             qmin, qstep, qmax = self._get_binning(workspace, wavelength_min, wavelength_max)
             align = self.getProperty("AlignWithDecades").value
             log_binning = self.getProperty("LogBinning").value
@@ -210,7 +210,7 @@ def _get_binning(self, workspace, wavelength_min, wavelength_max):
                     beam_ctr_x = property_manager.getProperty("LatestBeamCenterX").value
                     beam_ctr_y = property_manager.getProperty("LatestBeamCenterY").value
                 else:
-                    raise RuntimeError, "No beam center information can be found on the data set"
+                    raise RuntimeError("No beam center information can be found on the data set")
 
             # Q min is one pixel from the center, unless we have the beam trap size
             if workspace.getRun().hasProperty("beam-trap-diameter"):

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/SANSBeamSpreaderTransmission.py

@@ -86,7 +86,7 @@ def PyExec(self):
         def _load_data(filename, output_ws):
             if not property_manager.existsProperty("LoadAlgorithm"):
                 Logger("SANSBeamSpreaderTransmission").error("SANS reduction not set up properly: missing load algorithm")
-                raise RuntimeError, "SANS reduction not set up properly: missing load algorithm"
+                raise RuntimeError("SANS reduction not set up properly: missing load algorithm")
             p=property_manager.getProperty("LoadAlgorithm")
             alg=Algorithm.fromString(p.valueAsStr)
             alg.setProperty("Filename", filename)

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/SANSReduction.py

@@ -30,7 +30,7 @@ def _py_init(self):
     def _load_data(self, filename, output_ws, property_manager, property_manager_name):
         if not property_manager.existsProperty('LoadAlgorithm'):
             property_manager.existsProperty('LoadAlgorithm')
-            raise RuntimeError, 'SANS reduction not set up properly: missing load algorithm'
+            raise RuntimeError('SANS reduction not set up properly: missing load algorithm')
         else:
             property_manager.existsProperty('LoadAlgorithm')
         p = property_manager.getProperty('LoadAlgorithm')

Code/Mantid/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/TransmissionUtils.py

@@ -55,7 +55,7 @@ def load_monitors(self, property_manager):
     def _load_data(filename, output_ws):
         if not property_manager.existsProperty("LoadAlgorithm"):
             Logger("SANSDirectBeamTransmission").error("SANS reduction not set up properly: missing load algorithm")
-            raise RuntimeError, "SANS reduction not set up properly: missing load algorithm"
+            raise RuntimeError("SANS reduction not set up properly: missing load algorithm")
         p=property_manager.getProperty("LoadAlgorithm")
 
         alg_props = {"Filename": filename,