diff --git a/Framework/PythonInterface/plugins/algorithms/MergeCalFiles.py b/Framework/PythonInterface/plugins/algorithms/MergeCalFiles.py
index ec1b438be28726065d6a90610d0e817c391e3a04..8c2b116f84f9e6f4cb2583603a41ad3191c259a4 100644
--- a/Framework/PythonInterface/plugins/algorithms/MergeCalFiles.py
+++ b/Framework/PythonInterface/plugins/algorithms/MergeCalFiles.py
@@ -96,7 +96,7 @@ class MergeCalFiles(PythonAlgorithm):
#add any lines at the end
for UDET in updateDict.keys():
- (offset,select,group)=updateDict.pop(UDET)
+ (offset,select,group)=updateDict[UDET]
lastNumber += 1
outputFile.write(self.FormatLine(lastNumber,UDET,offset,select,group))
linesAdded += 1
diff --git a/docs/source/algorithms/MaskWorkspaceToCalFile-v1.rst b/docs/source/algorithms/MaskWorkspaceToCalFile-v1.rst
index 9fc0667507484719143819aa0b1c831b19e650b8..11682c79abf521c4259af2e7dbe58c24efa3af55 100644
--- a/docs/source/algorithms/MaskWorkspaceToCalFile-v1.rst
+++ b/docs/source/algorithms/MaskWorkspaceToCalFile-v1.rst
@@ -40,7 +40,7 @@ Usage
# Print out first 10 lines of the file
for line in calFile[:10]:
- print line
+ print(line)
Output
######
diff --git a/docs/source/algorithms/MatchPeaks-v1.rst b/docs/source/algorithms/MatchPeaks-v1.rst
index c2466b914084c918086eeeb9314eb81967795db2..d245e56808a2ec73e8a70150585a6f12fd854249 100644
--- a/docs/source/algorithms/MatchPeaks-v1.rst
+++ b/docs/source/algorithms/MatchPeaks-v1.rst
@@ -39,7 +39,7 @@ Usage
output_ws = MatchPeaks(InputWorkspace=ws)
- print('Peak height at center: {}').format(output_ws.readY(0)[ws.blocksize() / 2])
+ print('Peak height at center: {:.11f}'.format(output_ws.readY(0)[ws.blocksize() // 2]))
Output
######
diff --git a/docs/source/algorithms/Max-v1.rst b/docs/source/algorithms/Max-v1.rst
index 5528c0cc9acff2406ff17dd21aac1bfa3e255517..e0b69bbb7ef3c54122b7b8222d36a1b05454e3c6 100644
--- a/docs/source/algorithms/Max-v1.rst
+++ b/docs/source/algorithms/Max-v1.rst
@@ -23,17 +23,17 @@ Usage
max_ws = Max(ws)
# Check the returned values
- print 'Maximum found at bin [',max_ws.readX(0)[0],',',max_ws.readX(0)[1],'], value',max_ws.readY(0)[0]
- print 'In original workspace'
- print 'Bounds of bin 30 [',ws.readX(0)[30],',',ws.readX(0)[31],'], value',ws.readY(0)[30]
+ print('Maximum found at bin [ {} , {} ], value {}'.format(max_ws.readX(0)[0], max_ws.readX(0)[1], max_ws.readY(0)[0]))
+ print('In original workspace')
+ print('Bounds of bin 30 [ {} , {} ], value {}'.format(ws.readX(0)[30], ws.readX(0)[31], ws.readY(0)[30]))
# Find another peak
max_ws = Max(ws,RangeLower = 7000)
# Check the returned values
- print 'Maximum found at bin [',max_ws.readX(0)[0],',',max_ws.readX(0)[1],'], value',max_ws.readY(0)[0]
- print 'In original workspace'
- print 'Bounds of bin 60 [',ws.readX(0)[60],',',ws.readX(0)[61],'], value',ws.readY(0)[60]
+ print('Maximum found at bin [ {} , {} ], value {}'.format(max_ws.readX(0)[0], max_ws.readX(0)[1], max_ws.readY(0)[0]))
+ print('In original workspace')
+ print('Bounds of bin 60 [ {} , {} ], value {}'.format(ws.readX(0)[60], ws.readX(0)[61], ws.readY(0)[60]))
Output
######
diff --git a/docs/source/algorithms/MaxEnt-v1.rst b/docs/source/algorithms/MaxEnt-v1.rst
index 43760f435720693c6001507aae0171f77ef31546..b1356dd121b6dc46a4e85eb9cabb488875850479 100644
--- a/docs/source/algorithms/MaxEnt-v1.rst
+++ b/docs/source/algorithms/MaxEnt-v1.rst
@@ -157,11 +157,11 @@ and the reconstructed image, i.e. Fourier transform (right).
CreateWorkspace(OutputWorkspace='inputws',DataX=X,DataY=Y,DataE=E,NSpec=1)
evolChi, evolAngle, image, data = MaxEnt(InputWorkspace='inputws', chiTarget=N, A=0.0001)
- print "First reconstructed coefficient: %.3f" % data.readY(0)[5]
- print "Second reconstructed coefficient: %.3f" % data.readY(0)[10]
- print "Third reconstructed coefficient: %.3f" % data.readY(0)[20]
- print "Fourth reconstructed coefficient: %.3f" % data.readY(0)[12]
- print "Fifth reconstructed coefficient: %.3f" % data.readY(0)[14]
+ print("First reconstructed coefficient: {:.3f}".format(data.readY(0)[5]))
+ print("Second reconstructed coefficient: {:.3f}".format(data.readY(0)[10]))
+ print("Third reconstructed coefficient: {:.3f}".format(data.readY(0)[20]))
+ print("Fourth reconstructed coefficient: {:.3f}".format(data.readY(0)[12]))
+ print("Fifth reconstructed coefficient: {:.3f}".format(data.readY(0)[14]))
Output:
@@ -193,9 +193,9 @@ and :ref:`algm-FFT` (right).
# Compare MaxEnt to FFT
imageFFT = FFT(InputWorkspace='MUSR00022725')
- print "Image at %.3f: %.3f" % (image.readX(0)[44], image.readY(0)[44])
- print "Image at %.3f: %.3f" % (image.readX(0)[46], image.readY(0)[46])
- print "Image at %.3f: %.3f" % (image.readX(0)[48], image.readY(0)[48])
+ print("Image at {:.3f}: {:.3f}".format(image.readX(0)[44], image.readY(0)[44]))
+ print("Image at {:.3f}: {:.3f}".format(image.readX(0)[46], image.readY(0)[46]))
+ print("Image at {:.3f}: {:.3f}".format(image.readX(0)[48], image.readY(0)[48]))
Output:
@@ -222,12 +222,12 @@ and its imaginary part (right).
# Compare MaxEnt to FFT
imageFFT = FFT(InputWorkspace='EMU00020884')
- print "Image (real part) at %.3f: %.3f" % (image.readX(0)[129], image.readY(0)[129])
- print "Image (real part) at %.3f: %.3f" % (image.readX(0)[135], image.readY(0)[135])
- print "Image (real part) at %.3f: %.3f" % (image.readX(0)[141], image.readY(0)[141])
- print "Image (imaginary part) at %.3f: %.3f" % (image.readX(0)[129], image.readY(0)[129])
- print "Image (imaginary part) at %.3f: %.3f" % (image.readX(0)[135], image.readY(0)[135])
- print "Image (imaginary part) at %.3f: %.3f" % (image.readX(0)[141], image.readY(0)[141])
+ print("Image (real part) at {:.3f}: {:.3f}".format(image.readX(0)[129], image.readY(0)[129]))
+ print("Image (real part) at {:.3f}: {:.3f}".format(image.readX(0)[135], image.readY(0)[135]))
+ print("Image (real part) at {:.3f}: {:.3f}".format(image.readX(0)[141], image.readY(0)[141]))
+ print("Image (imaginary part) at {:.3f}: {:.3f}".format(image.readX(0)[129], image.readY(0)[129]))
+ print("Image (imaginary part) at {:.3f}: {:.3f}".format(image.readX(0)[135], image.readY(0)[135]))
+ print("Image (imaginary part) at {:.3f}: {:.3f}".format(image.readX(0)[141], image.readY(0)[141]))
Output:
@@ -268,9 +268,9 @@ the original and reconstructed data (left), and the reconstructed image (right).
CreateWorkspace(OutputWorkspace='ws',DataX=X+X,DataY=YRe+YIm,DataE=E+E,NSpec=2)
evolChi, evolAngle, image, data = MaxEnt(InputWorkspace='ws', ComplexData=True, chiTarget=2*N, A=0.001)
- print "Image (real part) at %.3f: %.3f" % (image.readX(0)[102], image.readY(0)[102])
- print "Image (real part) at %.3f: %.3f" % (image.readX(0)[103], image.readY(0)[103])
- print "Image (real part) at %.3f: %.3f" % (image.readX(0)[104], image.readY(0)[104])
+ print("Image (real part) at {:.3f}: {:.3f}".format(image.readX(0)[102], image.readY(0)[102]))
+ print("Image (real part) at {:.3f}: {:.3f}".format(image.readX(0)[103], image.readY(0)[103]))
+ print("Image (real part) at {:.3f}: {:.3f}".format(image.readX(0)[104], image.readY(0)[104]))
Output:
@@ -320,9 +320,9 @@ image in order to obtain smooth results).
evolChi, evolAngle, image, data = MaxEnt(InputWorkspace='ws', ComplexData=True, chiTarget=2*N, A=0.001, PositiveImage=False)
evolChiP, evolAngleP, imageP, dataP = MaxEnt(InputWorkspace='ws', ComplexData=True, chiTarget=2*N, A=0.001, PositiveImage=True)
- print "Image at %.3f: %.3f (PositiveImage=False), %.3f (PositiveImage=True)" % (image.readX(0)[102], image.readY(0)[102], imageP.readY(0)[102])
- print "Image at %.3f: %.3f (PositiveImage=False), %.3f (PositiveImage=True)" % (image.readX(0)[103], image.readY(0)[103], imageP.readY(0)[103])
- print "Image at %.3f: %.3f (PositiveImage=False), %.3f (PositiveImage=True)" % (image.readX(0)[104], image.readY(0)[104], imageP.readY(0)[102])
+ print("Image at {:.3f}: {:.3f} (PositiveImage=False), {:.3f} (PositiveImage=True)".format(image.readX(0)[102], image.readY(0)[102], imageP.readY(0)[102]))
+ print("Image at {:.3f}: {:.3f} (PositiveImage=False), {:.3f} (PositiveImage=True)".format(image.readX(0)[103], image.readY(0)[103], imageP.readY(0)[103]))
+ print("Image at {:.3f}: {:.3f} (PositiveImage=False), {:.3f} (PositiveImage=True)".format(image.readX(0)[104], image.readY(0)[104], imageP.readY(0)[102]))
Output:
@@ -367,8 +367,8 @@ the reconstructed data is twice the size of the original (experimental) data.
evolChi1, evolAngle1, image1, data1 = MaxEnt(InputWorkspace='ws', A=0.0001, ChiTarget=300, MaxIterations=2500, ResolutionFactor=1)
evolChi2, evolAngle2, image2, data2 = MaxEnt(InputWorkspace='ws', A=0.0001, ChiTarget=300, MaxIterations=5000, ResolutionFactor=2)
- print "Image at %.3f: %.3f (ResolutionFactor=1)" % (image1.readX(0)[135], image1.readY(0)[135])
- print "Image at %.3f: %.3f (ResolutionFactor=2)" % (image2.readX(0)[270], image2.readY(0)[270])
+ print("Image at {:.3f}: {:.3f} (ResolutionFactor=1)".format(image1.readX(0)[135], image1.readY(0)[135]))
+ print("Image at {:.3f}: {:.3f} (ResolutionFactor=2)".format(image2.readX(0)[270], image2.readY(0)[270]))
Output:
diff --git a/docs/source/algorithms/MaxMin-v1.rst b/docs/source/algorithms/MaxMin-v1.rst
index de8329a15ceeea04738181d155a95a28ba241761..39961f5687b66d27a5ebd42b149f35befe94a8f1 100644
--- a/docs/source/algorithms/MaxMin-v1.rst
+++ b/docs/source/algorithms/MaxMin-v1.rst
@@ -30,9 +30,9 @@ Usage
# Run algorithm
wsMax = MaxMin (ws)
- print "Maximum of each spectrum"
+ print("Maximum of each spectrum")
for i in range(9):
- print wsMax.readY(i)
+ print(wsMax.readY(i))
Output:
@@ -60,9 +60,9 @@ Output:
# Run algorithm
wsMax = MaxMin (ws, ShowMin=True)
- print "Minimum of each spectrum"
+ print("Minimum of each spectrum")
for i in range(9):
- print wsMax.readY(i)
+ print(wsMax.readY(i))
Output:
diff --git a/docs/source/algorithms/MayersSampleCorrection-v1.rst b/docs/source/algorithms/MayersSampleCorrection-v1.rst
index 1e9e1a32080d6c7ea6fd4ebf8c1c2c2fc1614527..7a1c489f2931f95fae92b4cbf00401bafa2a1f81 100644
--- a/docs/source/algorithms/MayersSampleCorrection-v1.rst
+++ b/docs/source/algorithms/MayersSampleCorrection-v1.rst
@@ -81,8 +81,8 @@ Usage
MultipleScattering=True)
# Print a bin
- print "Uncorrected signal: {0:.4f}".format(sample_ws.readY(0)[25])
- print "Corrected signal: {0:.4f}".format(corrected_sample.readY(0)[25])
+ print("Uncorrected signal: {0:.4f}".format(sample_ws.readY(0)[25]))
+ print("Corrected signal: {0:.4f}".format(corrected_sample.readY(0)[25]))
Output:
diff --git a/docs/source/algorithms/Mean-v1.rst b/docs/source/algorithms/Mean-v1.rst
index feb5e3398a26b97c3560c43bef436618138fbfa4..b73567b1784a9e52869896cf12e379842c96e573 100644
--- a/docs/source/algorithms/Mean-v1.rst
+++ b/docs/source/algorithms/Mean-v1.rst
@@ -41,8 +41,8 @@ Usage:
ws_2 = CreateWorkspace(dataX, dataY, NSpec=2)
result = Mean("ws_1, ws_2") # note the comma-separate strings
- print "Mean of y values in first spectrum:", result.readY(0)
- print "Mean of y values in second spectrum:", result.readY(1)
+ print("Mean of y values in first spectrum: {}".format(result.readY(0)))
+ print("Mean of y values in second spectrum: {}".format(result.readY(1)))
Output:
diff --git a/docs/source/algorithms/MergeCalFiles-v1.rst b/docs/source/algorithms/MergeCalFiles-v1.rst
index a3fa528eff8a6f8219edd3fdb42097d10f16cc2b..9a41a8f9224aecaae0a590e2173d1d7017d6084a 100644
--- a/docs/source/algorithms/MergeCalFiles-v1.rst
+++ b/docs/source/algorithms/MergeCalFiles-v1.rst
@@ -57,9 +57,9 @@ Usage
MergeGroups = True)
#Load and print the resulting file
- print "The result file has been updated with 0 for group, select and offset\nwhere the detector id's match"
+ print("The result file has been updated with 0 for group, select and offset\nwhere the detector id's match")
with open(output_file, "r") as file:
- print file.read().rstrip()
+ print(file.read().rstrip())
#cleanup
os.remove(calFile_master)
@@ -119,9 +119,9 @@ Output:
MergeGroups = False)
#Load and print the resulting file
- print "Any additional rows in the update file will be added,\nset the Merge options to False if you don't want to affect existing values"
+ print("Any additional rows in the update file will be added,\nset the Merge options to False if you don't want to affect existing values")
with open(output_file, "r") as file:
- print file.read().rstrip()
+ print(file.read().rstrip())
#cleanup
os.remove(calFile_master)
diff --git a/docs/source/algorithms/MergeLogs-v1.rst b/docs/source/algorithms/MergeLogs-v1.rst
index efb18ddc4cb7183db13823154cbf10dc794c84d0..e4b257a2df5fbcfb861a121ff6ba0eb95fce38f5 100644
--- a/docs/source/algorithms/MergeLogs-v1.rst
+++ b/docs/source/algorithms/MergeLogs-v1.rst
@@ -32,13 +32,13 @@ Usage
prop1 = ws.run().getProperty("Phase1")
prop2 = ws.run().getProperty("Phase2")
- print "Phase 1's size = %d, Phase 2's size = %d, Merged size = %d." % (prop1.size(), prop2.size(), newprop.size())
- for i in xrange(5):
- print "Phase1 Time[%d] = %s." % (i, prop1.nthTime(i))
- for i in xrange(5):
- print "Phase2 Time[%d] = %s." % (i, prop2.nthTime(i))
- for i in xrange(5):
- print "Mixed Phase 1 and 2 Time[%d] = %s." % (i, newprop.nthTime(i))
+ print("Phase 1's size = {}, Phase 2's size = {}, Merged size = {}.".format(prop1.size(), prop2.size(), newprop.size()))
+ for i in range(5):
+ print("Phase1 Time[{}] = {}.".format(i, prop1.nthTime(i)))
+ for i in range(5):
+ print("Phase2 Time[{}] = {}.".format(i, prop2.nthTime(i)))
+ for i in range(5):
+ print("Mixed Phase 1 and 2 Time[{}] = {}.".format(i, newprop.nthTime(i)))
.. testcleanup:: ExMerge2Logs
diff --git a/docs/source/algorithms/MergeMD-v1.rst b/docs/source/algorithms/MergeMD-v1.rst
index f9f4aaecdda0b5feb35485c813c2115119f9b5d5..dc48a4a11169ae34b8dc7fd07f23ad8d34b1f41b 100644
--- a/docs/source/algorithms/MergeMD-v1.rst
+++ b/docs/source/algorithms/MergeMD-v1.rst
@@ -47,21 +47,21 @@ Usage
SumWS=MergeMD(InputWorkspaces='mdWs1,mdWs2',SplitInto='100,100')
# check it looks like the one we wanted
- print 'merged workspace of type: {0}\n'.format(SumWS.id()),
+ print('merged workspace of type: {0}'.format(SumWS.id()))
# this is how you would check whether it is a general MDEventWorkspace
- print 'it is a type of MDEventWorkspace: {0}\n'.format(isinstance(SumWS, IMDEventWorkspace)),
- print '****************************************************************'
- print 'workspace 1 has {0} dimensions with {1} points and {2} events'.format(mdWs1.getNumDims(),mdWs1.getNPoints(),mdWs1.getNEvents());
+ print('it is a type of MDEventWorkspace: {0}'.format(isinstance(SumWS, IMDEventWorkspace)))
+ print('****************************************************************')
+ print('workspace 1 has {0} dimensions with {1} points and {2} events'.format(mdWs1.getNumDims(),mdWs1.getNPoints(),mdWs1.getNEvents()))
d1=mdWs1.getDimension(0);d2=mdWs1.getDimension(1)
- print 'with d1 min_max={0}:{1}, d2 min_max={2}:{3}'.format(d1.getMinimum(),d1.getMaximum(),d2.getMinimum(),d2.getMaximum())
- print 'workspace 2 has {0} dimensions with {1} points and {2} events'.format(mdWs2.getNumDims(),mdWs2.getNPoints(),mdWs2.getNEvents());
+ print('with d1 min_max={0}:{1}, d2 min_max={2}:{3}'.format(d1.getMinimum(),d1.getMaximum(),d2.getMinimum(),d2.getMaximum()))
+ print('workspace 2 has {0} dimensions with {1} points and {2} events'.format(mdWs2.getNumDims(),mdWs2.getNPoints(),mdWs2.getNEvents()))
d1=mdWs2.getDimension(0);d2=mdWs2.getDimension(1)
- print 'with d1 min_max={0}:{1}, d2 min_max={2}:{3}'.format(d1.getMinimum(),d1.getMaximum(),d2.getMinimum(),d2.getMaximum())
- print '****************************************************************'
- print 'Merged WS has {0} dimensions with {1} points and {2} events'.format(SumWS.getNumDims(),SumWS.getNPoints(),SumWS.getNEvents());
+ print('with d1 min_max={0}:{1}, d2 min_max={2}:{3}'.format(d1.getMinimum(),d1.getMaximum(),d2.getMinimum(),d2.getMaximum()))
+ print('****************************************************************')
+ print('Merged WS has {0} dimensions with {1} points and {2} events'.format(SumWS.getNumDims(),SumWS.getNPoints(),SumWS.getNEvents()))
d1=SumWS.getDimension(0);d2=SumWS.getDimension(1)
- print 'with d1 min_max={0}:{1}, d2 min_max={2}:{3}'.format(d1.getMinimum(),d1.getMaximum(),d2.getMinimum(),d2.getMaximum())
- print '****************************************************************'
+ print('with d1 min_max={0}:{1}, d2 min_max={2}:{3}'.format(d1.getMinimum(),d1.getMaximum(),d2.getMinimum(),d2.getMaximum()))
+ print('****************************************************************')
**Output:**
diff --git a/docs/source/algorithms/MergeRuns-v1.rst b/docs/source/algorithms/MergeRuns-v1.rst
index 0dc8a4786c767205ca91cf502d25de20c1e9cb21..1ff0fbaf6a39249cd8bf972cf52eb01827488a87 100644
--- a/docs/source/algorithms/MergeRuns-v1.rst
+++ b/docs/source/algorithms/MergeRuns-v1.rst
@@ -147,9 +147,9 @@ Usage
merged = MergeRuns(InputWorkspaces="a, b")
- print "a = " + str(a.readY(0))
- print "b = " + str(b.readY(0))
- print "merged = " + str(merged.readY(0))
+ print("a = {}".format(a.readY(0)))
+ print("b = {}".format(b.readY(0)))
+ print("merged = {}".format(merged.readY(0)))
Output:
@@ -176,13 +176,13 @@ Output:
merged = MergeRuns(InputWorkspaces="group_1, group_2")
- print "group_1 = [" + str(group_1[0].readY(0)) + ","
- print " " + str(group_1[1].readY(0)) + "]"
+ print("group_1 = [{},".format(group_1[0].readY(0)))
+ print(" {}]".format(group_1[1].readY(0)))
+
+ print("group_2 = [{},".format(group_2[0].readY(0)))
+ print(" {}]".format(group_2[1].readY(0)))
- print "group_2 = [" + str(group_2[0].readY(0)) + ","
- print " " + str(group_2[1].readY(0)) + "]"
-
- print "merged = " + str(merged.readY(0))
+ print("merged = {}".format(merged.readY(0)))
Output:
diff --git a/docs/source/algorithms/Min-v1.rst b/docs/source/algorithms/Min-v1.rst
index dfe615e660cbf21a87318bf8775c7d0ab98d4054..04328af539f7771ec46934f099f71bd55f42876a 100644
--- a/docs/source/algorithms/Min-v1.rst
+++ b/docs/source/algorithms/Min-v1.rst
@@ -20,12 +20,16 @@ Usage
#Find minima
minim=Min(InputWorkspace='w2')
- print "Minima for spectrum 0 is Y = ",minim.dataY(0)[0]," and it occurs at X between ", minim.dataX(0)[0], " and ", minim.dataX(0)[1]
- print "Minima for spectrum 1 is Y = ",minim.dataY(1)[0]," and it occurs at X between ", minim.dataX(1)[0], " and ", minim.dataX(1)[1]
+ print("Minima for spectrum 0 is Y = {} and it occurs at X between {} and {}".
+ format(minim.dataY(0)[0], minim.dataX(0)[0], minim.dataX(0)[1]))
+ print("Minima for spectrum 1 is Y = {} and it occurs at X between {} and {}".
+ format(minim.dataY(1)[0], minim.dataX(1)[0], minim.dataX(1)[1]))
#Find minima with extra parameters
minim=Min(InputWorkspace='w2',RangeLower=0,RangeUpper=3,StartWorkspaceIndex =1,EndWorkspaceIndex=1)
- print "The new output workspace has ",minim.getNumberHistograms()," histogram, with the minimum Y = ",minim.dataY(0)[0]," and it occurs at X between ", minim.dataX(0)[0], " and ", minim.dataX(0)[1]
+ print("The new output workspace has {} histogram, with the minimum Y = {} " \
+ "and it occurs at X between {} and {}".
+ format(minim.getNumberHistograms(), minim.dataY(0)[0], minim.dataX(0)[0], minim.dataX(0)[1]))
.. testcleanup:: Min
diff --git a/docs/source/algorithms/Minus-v1.rst b/docs/source/algorithms/Minus-v1.rst
index 915fd3e465fd4c62a1ca6c8914a29b213731570b..27d3ff7dc7fd72ff1c10e599c70f6c80e628e4ab 100644
--- a/docs/source/algorithms/Minus-v1.rst
+++ b/docs/source/algorithms/Minus-v1.rst
@@ -41,9 +41,9 @@ Usage
# perform the algorithm
ws = Minus(ws1, ws2)
- print "The X values are: " + str(ws.readX(0))
- print "The Y values are: " + str(ws.readY(0))
- print "The updated Error values are: " + str(ws.readE(0))
+ print("The X values are: {}".format(ws.readX(0)))
+ print("The Y values are: {}".format(ws.readY(0)))
+ print("The updated Error values are: {}".format(ws.readE(0)))
Output:
@@ -71,9 +71,9 @@ Output:
# perform the algorithm
ws = ws1 - ws2
- print "The X values are: " + str(ws.readX(0))
- print "The Y values are: " + str(ws.readY(0))
- print "The updated Error values are: " + str(ws.readE(0))
+ print("The X values are: {}".format(ws.readX(0)))
+ print("The Y values are: {}".format(ws.readY(0)))
+ print("The updated Error values are: {}".format(ws.readE(0)))
Output:
@@ -101,9 +101,9 @@ Output:
# perform the algorithm
ws -= ws1
- print "The X values are: " + str(ws.readX(0))
- print "The Y values are: " + str(ws.readY(0))
- print "The updated Error values are: " + str(ws.readE(0))
+ print("The X values are: {}".format(ws.readX(0)))
+ print("The Y values are: {}".format(ws.readY(0)))
+ print("The updated Error values are: {}".format(ws.readE(0)))
Output:
@@ -127,9 +127,9 @@ Output:
# perform the algorithm
ws = ws1 - 2.5
- print "The X values are: " + str(ws.readX(0))
- print "The Y values are: " + str(ws.readY(0))
- print "The updated Error values are: " + str(ws.readE(0))
+ print("The X values are: {}".format(ws.readX(0)))
+ print("The Y values are: {}".format(ws.readY(0)))
+ print("The updated Error values are: {}".format(ws.readE(0)))
Output: