Merge pull request #20730 from mantidproject/20726_python3_doctest_F

Python3 doctest compatibility: algorithms beginning with F

docs/source/algorithms/FFT-v1.rst

@@ -208,11 +208,10 @@ Usage
    #apply the FFT algorithm - note output is point data
    outworkspace = FFT(InputWorkspace = ws, Transform = 'Backward')
 
-   #print statements
-   print "DataX(0)[1] equals DataX(0)[99]? : " + str((round(abs(outworkspace.dataX(0)[1]), 3)) == (round(outworkspace.dataX(0)[99], 3)))
-   print "DataX(0)[10] equals DataX(0)[90]? : " + str((round(abs(outworkspace.dataX(0)[10]), 3)) == (round(outworkspace.dataX(0)[90], 3)))
-   print "DataX((0)[50] equals 0? : " + str((round(abs(outworkspace.dataX(0)[50]), 3)) == 0)
-   print "DataY(0)[40] equals DataY(0)[60]? : " + str((round(abs(outworkspace.dataY(0)[40]), 5)) == (round(outworkspace.dataY(0)[60], 5)))
+   print("DataX(0)[1] equals DataX(0)[99]? : " + str((round(abs(outworkspace.dataX(0)[1]), 3)) == (round(outworkspace.dataX(0)[99], 3))))
+   print("DataX(0)[10] equals DataX(0)[90]? : " + str((round(abs(outworkspace.dataX(0)[10]), 3)) == (round(outworkspace.dataX(0)[90], 3))))
+   print("DataX((0)[50] equals 0? : " + str((round(abs(outworkspace.dataX(0)[50]), 3)) == 0))
+   print("DataY(0)[40] equals DataY(0)[60]? : " + str((round(abs(outworkspace.dataY(0)[40]), 5)) == (round(outworkspace.dataY(0)[60], 5))))
 
 Output:
 

docs/source/algorithms/FFTDerivative-v1.rst

@@ -23,9 +23,9 @@ Usage
     wsOrder2 = FFTDerivative(wsOriginal,Order=2)
     wsOrder3 = FFTDerivative(wsOriginal,Order=3)
 
-    print "bin Orig  1st    2nd   3rd"
+    print("bin Orig  1st    2nd   3rd")
     for i in range (41,67,5):
-        print "%i  %.2f  %.2f  %.2f  %.2f" % (i, wsOriginal.readY(0)[i], wsOrder1.readY(0)[i], wsOrder2.readY(0)[i], wsOrder3.readY(0)[i])
+        print("{}  {:.2f}  {:.2f}  {:.2f}  {:.2f}".format(i, wsOriginal.readY(0)[i], wsOrder1.readY(0)[i], wsOrder2.readY(0)[i], wsOrder3.readY(0)[i]))
 
 .. figure:: /images/FFTDerivativeExample.png
     :align: right
@@ -54,8 +54,8 @@ Output:
 
     wsOrder2Test = FFTDerivative(wsOrder1,Order=1)
 
-    print "The direct 2nd order derivative and the derivative of a derivative should match"
-    print CompareWorkspaces(wsOrder2,wsOrder2Test,CheckAllData=True,Tolerance=1e10)[0]
+    print("The direct 2nd order derivative and the derivative of a derivative should match")
+    print(CompareWorkspaces(wsOrder2,wsOrder2Test,CheckAllData=True,Tolerance=1e10)[0])
 
 Output:
 

docs/source/algorithms/FFTSmooth-v1.rst

@@ -46,9 +46,9 @@ Usage
 
     wsSmooth = FFTSmooth(ws, Params='2', Version=1)
 
-    print "bin Orig  Smoothed"
+    print("bin Orig  Smoothed")
     for i in range (0,100,10):
-        print "%i  %.2f  %.2f" % (i, ws.readY(0)[i], wsSmooth.readY(0)[i])
+        print("{}  {:.2f}  {:.2f}".format(i, ws.readY(0)[i], wsSmooth.readY(0)[i]))
 
 
 .. figure:: /images/FFTSmoothZeroing.png

docs/source/algorithms/FFTSmooth-v2.rst

@@ -67,9 +67,9 @@ Usage
 
     wsSmooth = FFTSmooth(ws, Params='2')
 
-    print "bin Orig  Smoothed"
+    print("bin Orig  Smoothed")
     for i in range (0,100,10):
-        print "%i  %.2f  %.2f" % (i, ws.readY(0)[i], wsSmooth.readY(0)[i])
+        print("{}  {:.2f}  {:.2f}".format(i, ws.readY(0)[i], wsSmooth.readY(0)[i]))
 
 
 .. figure:: /images/FFTSmoothZeroing.png
@@ -114,9 +114,9 @@ Output:
     wsButter5_2 = FFTSmooth(ws, Filter="Butterworth", Params='5,2', AllSpectra=True)
     wsButter20_2 = FFTSmooth(ws, Filter="Butterworth", Params='20,2', AllSpectra=True)
 
-    print "bin Orig  2_2   5_2   20_2"
+    print("bin Orig  2_2   5_2   20_2")
     for i in range (0,100,10):
-        print "%i  %.2f  %.2f  %.2f  %.2f" % (i, ws.readY(0)[i], wsButter2_2.readY(0)[i], wsButter5_2.readY(0)[i], wsButter20_2.readY(0)[i])
+        print("{}  {:.2f}  {:.2f}  {:.2f}  {:.2f}".format(i, ws.readY(0)[i], wsButter2_2.readY(0)[i], wsButter5_2.readY(0)[i], wsButter20_2.readY(0)[i]))
 
 
 .. figure:: /images/FFTSmoothZeroingButter.png

docs/source/algorithms/FakeISISEventDAE-v1.rst

@@ -67,8 +67,8 @@ Usage
 
     try:
         captureLive()
-    except Exception, exc:
-        print "Error occurred starting live data"
+    except:
+        print("Error occurred starting live data")
     finally:
         thread.join() # this must get hit
 
@@ -77,7 +77,7 @@ Usage
 
     #get the ouput workspace
     wsOut = mtd["wsOut"]
-    print "The workspace contains %i events" % wsOut.getNumberEvents()
+    print("The workspace contains %i events" % wsOut.getNumberEvents())
 
 Output:
 

docs/source/algorithms/FakeISISHistoDAE-v1.rst

@@ -61,8 +61,8 @@ Usage
 
     try:
         captureLive()
-    except Exception, exc:
-        print "Error occurred starting live data"
+    except:
+        print("Error occurred starting live data")
     finally:
         thread.join() # this must get hit
 
@@ -71,7 +71,7 @@ Usage
 
     #get the ouput workspace
     wsOut = mtd["wsOut"]
-    print "The workspace contains %i histograms" % wsOut.getNumberHistograms()
+    print("The workspace contains %i histograms" % wsOut.getNumberHistograms())
 
 Output:
 

docs/source/algorithms/FakeMDEventData-v1.rst

@@ -28,7 +28,7 @@ using :ref:`CreateMDWorkspace <algm-CreateMDWorkspace>`.
     ws = CreateMDWorkspace(Dimensions='2', EventType='MDEvent', Extents='-10,10,-10,10',
                            Names='Q_lab_x,Q_lab_y', Units='A,B')
     FakeMDEventData(ws, UniformParams="1000000")
-    print "Number of events =", ws.getNEvents()
+    print("Number of events = {}".format(ws.getNEvents()))
 
 Output:
 
@@ -54,7 +54,7 @@ Creates 3 peaks in (H,K,L) at (0,0,0), (1,1,0) and (1,1,1).
     FakeMDEventData(ws, PeakParams='10000,1,1,1,0.1', RandomSeed='63759', RandomizeSignal='1')
     FakeMDEventData(ws, PeakParams='100000,0,0,0,0.1', RandomSeed='63759', RandomizeSignal='1')
     FakeMDEventData(ws, PeakParams='40000,1,1,0,0.1', RandomSeed='63759', RandomizeSignal='1')
-    print "Number of events =", ws.getNEvents()
+    print("Number of events = {}".format(ws.getNEvents()))
 
 Output:
 
@@ -85,7 +85,7 @@ Creates a peak at (H,K,L) of (0,0,0) around T=5K.
     ws = CreateMDWorkspace(Dimensions='4', Extents='-1,1,-1,1,-1,1,0,10', Names='H,K,L,T', Units='rlu,rlu,rlu,K',
                            SplitInto='2', SplitThreshold='50')
     FakeMDEventData(ws, PeakParams='1e+06,0,0,0,5,0.2', RandomSeed='3873875')
-    print "Number of events =", ws.getNEvents()
+    print("Number of events = {}".format(ws.getNEvents()))
 
 Output:
 

docs/source/algorithms/FilterBadPulses-v1.rst

@@ -33,8 +33,8 @@ Usage
     AddSampleLog(ws,"gd_prtn_chrg", "1e6", "Number")
     wsFiltered = FilterBadPulses(ws)
 
-    print ("The number of events that remain: %i" % wsFiltered.getNumberEvents())
-    print ("compared to the number in the unfiltered workspace: %i" % ws.getNumberEvents())
+    print("The number of events that remain: %i" % wsFiltered.getNumberEvents())
+    print("compared to the number in the unfiltered workspace: %i" % ws.getNumberEvents())
 
 Output:
 

docs/source/algorithms/FilterByLogValue-v1.rst

@@ -97,11 +97,11 @@ Usage
    AddTimeSeriesLog(ws, Name="proton_charge", Time="2010-01-01T00:40:00", Value=15)
    AddTimeSeriesLog(ws, Name="proton_charge", Time="2010-01-01T00:50:00", Value=100)
 
-   print "The unfiltered workspace %s has %i events and a peak value of %.2f" % (ws, ws.getNumberEvents(),ws.readY(0)[50])
+   print("The unfiltered workspace {} has {} events and a peak value of {:.2f}".format(ws, ws.getNumberEvents(),ws.readY(0)[50]))
 
    wsOut = FilterByLogValue(ws,"proton_charge",MinimumValue=75, MaximumValue=150)
 
-   print "The filtered workspace %s has %i events and a peak value of %.2f" % (wsOut, wsOut.getNumberEvents(),wsOut.readY(0)[50])
+   print("The filtered workspace {} has {} events and a peak value of {:.2f}".format(wsOut, wsOut.getNumberEvents(),wsOut.readY(0)[50]))
 
 
 Output:

docs/source/algorithms/FilterByTime-v1.rst

@@ -53,9 +53,9 @@ Usage
         AbsoluteStartTime="2010-01-01T00:10:00",
         AbsoluteStopTime="2010-01-01T00:20:00")
 
-    print ("The number of events within the relative Filter: %i" % wsFiltered.getNumberEvents())
-    print ("The number of events within the Aboslute Filter: %i" % wsFilteredAbs.getNumberEvents())
-    print ("Compared to the number in the unfiltered workspace: %i" % ws.getNumberEvents())
+    print("The number of events within the relative Filter: %i" % wsFiltered.getNumberEvents())
+    print("The number of events within the Aboslute Filter: %i" % wsFilteredAbs.getNumberEvents())
+    print("Compared to the number in the unfiltered workspace: %i" % ws.getNumberEvents())
 
 Output:
 

docs/source/algorithms/FilterByXValue-v1.rst

@@ -26,9 +26,9 @@ Usage
 .. testcode:: ExFilterTofByMax
 
     ws = CreateSampleWorkspace("Event",BankPixelWidth=1)
-    print "%i events before filtering" % ws.getNumberEvents()
+    print("%i events before filtering" % ws.getNumberEvents())
     wsOut = FilterByXValue(ws,XMax=15000)
-    print "%i events after filtering" % wsOut.getNumberEvents()
+    print("%i events after filtering" % wsOut.getNumberEvents())
 
 
 Output:
@@ -44,9 +44,9 @@ Output:
 
     ws = CreateSampleWorkspace("Event",BankPixelWidth=1)
     ws = ConvertUnits(ws,"Wavelength")
-    print "%i events before filtering" % ws.getNumberEvents()
+    print("%i events before filtering" % ws.getNumberEvents())
     wsOut = FilterByXValue(ws,XMin=1,XMax=3)
-    print "%i events after filtering" % wsOut.getNumberEvents()
+    print("%i events after filtering" % wsOut.getNumberEvents())
 
 
 Output:

docs/source/algorithms/FilterEvents-v1.rst

@@ -162,7 +162,7 @@ Usage
     wsnames = wsgroup.getNames()
     for name in sorted(wsnames):
         tmpws = mtd[name]
-        print "workspace %s has %d events" % (name, tmpws.getNumberEvents())
+        print("workspace %s has %d events" % (name, tmpws.getNumberEvents()))
 
 
 Output:
@@ -207,9 +207,9 @@ Output:
     wsnames = wsgroup.getNames()
     for name in sorted(wsnames):
         tmpws = mtd[name]
-        print "workspace %s has %d events" % (name, tmpws.getNumberEvents())
+        print("workspace %s has %d events" % (name, tmpws.getNumberEvents()))
         split_log = tmpws.run().getProperty('splitter')
-        print 'event splitter log: entry 0 and entry 1 are {0} and {1}.'.format(split_log.times[0], split_log.times[1])
+        print('event splitter log: entry 0 and entry 1 are {0} and {1}.'.format(split_log.times[0], split_log.times[1]))
 
 
 Output:
@@ -251,7 +251,7 @@ Output:
     wsnames = wsgroup.getNames()
     for name in sorted(wsnames):
         tmpws = mtd[name]
-        print "workspace %s has %d events" % (name, tmpws.getNumberEvents())
+        print("workspace %s has %d events" % (name, tmpws.getNumberEvents()))
 
 
 Output:
@@ -290,7 +290,7 @@ Output:
     wsnames = wsgroup.getNames()
     for name in sorted(wsnames):
         tmpws = mtd[name]
-        print "workspace %s has %d events" % (name, tmpws.getNumberEvents())
+        print("workspace %s has %d events" % (name, tmpws.getNumberEvents()))
 
 
 Output:

docs/source/algorithms/FilterLogByTime-v1.rst

@@ -40,26 +40,26 @@ Usage
     AddTimeSeriesLog(ws, Name="proton_charge", Time="2010-01-01T00:40:00", Value=15)
     AddTimeSeriesLog(ws, Name="proton_charge", Time="2010-01-01T00:50:00", Value=100)
 
-    print ("Without a StartTime or EndTime all of the values are included")
+    print("Without a StartTime or EndTime all of the values are included")
     (filtered_result,stat_result) = FilterLogByTime(ws,LogName="proton_charge")
-    print ("The default statistic is mean: %i" % stat_result)
-    print ("The filtered result is")
-    print (filtered_result)
+    print("The default statistic is mean: %i" % stat_result)
+    print("The filtered result is")
+    print(filtered_result)
 
     (filtered_result,stat_result) = FilterLogByTime(ws,LogName="proton_charge", Method="max")
-    print ("The max is: %i" % stat_result)
+    print("The max is: %i" % stat_result)
     (filtered_result,stat_result) = FilterLogByTime(ws,LogName="proton_charge", Method="min")
-    print ("The min is: %i" % stat_result)
+    print("The min is: %i" % stat_result)
     (filtered_result,stat_result) = FilterLogByTime(ws,LogName="proton_charge", Method="median")
-    print ("The median is: %i" % stat_result)
-    print 
+    print("The median is: %i" % stat_result)
+    print("") 
 
     print("Adding a start time and optionally an end time allows you to filter the values")
     (filtered_result,stat_result) = FilterLogByTime(ws,LogName="proton_charge",
         StartTime=580,EndTime = 1800)
-    print ("The filtered mean is: %i" % stat_result)
-    print ("The filtered result is")
-    print (filtered_result)
+    print("The filtered mean is: %i" % stat_result)
+    print("The filtered result is")
+    print(filtered_result)
  
 
 Output:

docs/source/algorithms/FindDeadDetectors-v1.rst

@@ -43,17 +43,17 @@ Usage
     str_data=[0.4,5.0,0.001,0.0,0.0,0.0,0.0,0.0,1.0,1.0]
     ws.setY(20,np.array(str_data))
 
-    print "With no range will find very dead"
+    print("With no range will find very dead")
     (wsOut,detList) = FindDeadDetectors(ws)
-    print str(detList)
+    print(detList)
 
-    print "\nwith a lower range will find very dead and drop off"
+    print("\nwith a lower range will find very dead and drop off")
     (wsOut,detList) = FindDeadDetectors(ws,RangeLower=8e3)
-    print str(detList)
+    print(detList)
 
-    print "\nwith a lower range and upper range will find all three"
+    print("\nwith a lower range and upper range will find all three")
     (wsOut,detList) = FindDeadDetectors(ws,RangeLower=8e3, rangeUpper=1.6e4)
-    print str(detList)
+    print(detList)
 
 Output:
 

docs/source/algorithms/FindDetectorsInShape-v1.rst

@@ -53,8 +53,8 @@ Usage
    no_detectors = FindDetectorsInShape(musr_inst_ws, narrow_cylinder)
    all_detectors = FindDetectorsInShape(musr_inst_ws, wide_cylinder)
 
-   print "The narrow cylinder contains %i of the detectors." % len(no_detectors)
-   print "The wide cylinder contains %i of the detectors." % len(all_detectors)
+   print("The narrow cylinder contains %i of the detectors." % len(no_detectors))
+   print("The wide cylinder contains %i of the detectors." % len(all_detectors))
 
 Output:
 

docs/source/algorithms/FindDetectorsOutsideLimits-v1.rst

@@ -41,15 +41,15 @@ Usage
         ws.setY(i,np.array(deadDetArray))
         ws.setY(i+1,np.array(noisyDetArray))
 
-    print "With just the default LowThreshold of 0"
+    print("With just the default LowThreshold of 0")
     (wsOut,NumberOfFailures)=FindDetectorsOutsideLimits(ws)
-    print "%i spectra were outside the limits." % NumberOfFailures
-    print
+    print("{} spectra were outside the limits.".format(NumberOfFailures))
+    print("")
 
-    print "With a High and LowThreshold, as well as restricting the XRange to consider"
+    print("With a High and LowThreshold, as well as restricting the range to consider")
     (wsOut2,NumberOfFailures)=FindDetectorsOutsideLimits(ws, HighThreshold=1000, 
         LowThreshold=0, RangeLower=200, RangeUpper=10000)
-    print "%i spectra were outside the limits." % NumberOfFailures
+    print("{} spectra were outside the limits.".format(NumberOfFailures))
 
     mtd.clear()
 
@@ -61,7 +61,7 @@ Output:
     With just the default LowThreshold of 0
     20 spectra were outside the limits.
 
-    With a High and LowThreshold, as well as restricting the XRange to consider
+    With a High and LowThreshold, as well as restricting the range to consider
     40 spectra were outside the limits.
 
 **Example:**
@@ -70,7 +70,7 @@ Output:
 
     ws = CreateSimulationWorkspace('MARI','0,1,10')
     nh = ws.getNumberHistograms()
-    for ind in xrange(nh):
+    for ind in range(nh):
         y = ws.dataY(ind)    
         if ind>=100 and ind < 300:
             y.fill(100)
@@ -80,15 +80,15 @@ Output:
     mws1,nMasked1 = FindDetectorsOutsideLimits(ws,100)
     mws2,nMasked2 = FindDetectorsOutsideLimits(ws,100,startWorkspaceIndex = 200)
 
-    print "****************************************"
-    print "full mask ws has {0} masked detectors".format(nMasked1)
-    print "part mask ws  has {0} masked detectors".format(nMasked2)
-    print "****************************************"
+    print("****************************************")
+    print("full mask ws has {0} masked detectors".format(nMasked1))
+    print("part mask ws  has {0} masked detectors".format(nMasked2))
+    print("****************************************")
     selected_spec = [99,100,199,200,299,300]
     for spec in selected_spec:
-        print "full mask ws Spec N{0} is masked: {1}".format(spec,mws1.readY(spec)[0]>0.5)
-        print "part mask ws Spec N{0} is masked: {1}".format(spec,mws2.readY(spec)[0]>0.5) 
-    print "****************************************"
+        print("full mask ws Spec N{0} is masked: {1}".format(spec,mws1.readY(spec)[0]>0.5))
+        print("part mask ws Spec N{0} is masked: {1}".format(spec,mws2.readY(spec)[0]>0.5) )
+    print("****************************************")
 
 Output:
 

docs/source/algorithms/FindDetectorsPar-v1.rst

@@ -81,9 +81,9 @@ Usage
     # Output workspace is None if OutputParTable is not used)
     pars = FindDetectorsPar(ws, OutputParTable="pars")
     # pars is a TableWorkspace
-    print "Workspace type =", pars.id()
+    print("Workspace type = {}".format(pars.id()))
     # Show width column headers
-    print "Width headers = (", pars.getColumnNames()[3], ",", pars.getColumnNames()[4], ")"
+    print("Width headers = ( {} , {} )".format(pars.getColumnNames()[3], pars.getColumnNames()[4]))
 
 Output:
 
@@ -100,9 +100,9 @@ Output:
     # Output workspace is None if OutputParTable is not used)
     pars = FindDetectorsPar(ws, ReturnLinearRanges=True, OutputParTable="pars")
     # pars is a TableWorkspace
-    print "Workspace type =", pars.id()
+    print("Workspace type = {}".format(pars.id()))
     # Show width column headers
-    print "Width headers = (", pars.getColumnNames()[3], ",", pars.getColumnNames()[4], ")"
+    print("Width headers = ( {} , {} )".format(pars.getColumnNames()[3], pars.getColumnNames()[4]))
 
 Output:
 

docs/source/algorithms/FindEPP-v1.rst

@@ -31,9 +31,9 @@ Usage
     table = FindEPP(ws, Version=1)
 
     # print some results
-    print "The fit status is", table.row(0)['FitStatus']
-    print "The peak centre is at", round(table.row(0)['PeakCentre'], 2), "microseconds"
-    print "The peak height is", round(table.row(0)['Height'],2)
+    print("The fit status is {}".format(table.row(0)['FitStatus']))
+    print("The peak centre is at {} microseconds".format(round(table.row(0)['PeakCentre'], 2)))
+    print("The peak height is {}".format(round(table.row(0)['Height'],2)))
 
 Output:
 

docs/source/algorithms/FindEPP-v2.rst

@@ -40,9 +40,9 @@ Usage
     table = FindEPP(ws)
 
     # print some results
-    print "The fit status is", table.row(0)['FitStatus']
-    print "The peak centre is at", round(table.row(0)['PeakCentre'], 2), "microseconds"
-    print "The peak height is", round(table.row(0)['Height'],2)
+    print("The fit status is {}".format(table.row(0)['FitStatus']))
+    print("The peak centre is at {} microseconds".format(round(table.row(0)['PeakCentre'], 2)))
+    print("The peak height is {}".format(round(table.row(0)['Height'],2)))
 
 Output:
 

docs/source/algorithms/FindPeaks-v1.rst

@@ -100,8 +100,7 @@ Usage
 
    row = table.row(0)
 
-   #print row
-   print "Peak 1 {Centre: %.3f, width: %.3f, height: %.3f }" % ( row["centre"],  row["width"], row["height"])
+   print("Peak 1 {Centre: %.3f, width: %.3f, height: %.3f }" % ( row["centre"],  row["width"], row["height"]))
 
 
 Output: