actual evaluation status

tools/evaluation/PaperEvaluation.py

@@ -900,9 +900,9 @@ def FigureWorkPrecision(which):
         sP='images/'
         L=6
         J=5
-        ydescription='$\\errSI}$'
+        ydescription='$\\errSI$'
         (nameS,minprocS)=plot.workPrecisionInSpace(L,J,j,fL,nL,fSI,eP,point,ydescription)
-        (nameT,minprocT)=plot.workPrecisionInTime(L,J,l,fL,nL,fSI,eP,point,ydescription)
+        (nameT,minprocT)=plot.workPrecisionInTime(L,J,l,fL,nL,fSI,eP,point,ydescription,minprocS)
         print(minprocS,minprocT)
         filename=eP+'tex/'+'WPSIFigP'+str(point)
         caption='\\IESVI, \\LISVI, \\SISVI, ~and \GPDE~with fixed  time step size $j='+str(j)+'$ (left) and $\ell='+str(l)+'$ (right) comparing the CPU time scaled to $\\#$procs$='+str(minprocS)+'$ (left) and $\\#$procs$='+str(minprocT)+'$ (right) to the error $\\errSI('+getPointNamebyNumber(point,True)+')$'
@@ -1148,7 +1148,7 @@ def DurationAndProcs(which):
         tab=Table(lL,tL,sdt,endTime,1,fL[0])
         filename=eP+'tex/'+'CompDurIELISIG'
         caption='CPU time (hours:minutes:seconds) including number of processes for the different time integration schemes in the benchmark configuration'
-        label='\\label{tab:CompDurIELISIG'+'}'
+        label='tab:CompDurIELISIG'
         with open(filename+'.tex', 'w') as output_file:
             output_file.write(tab.writeBeginDurationTabList(caption,label,fL))
             output_file.write(tab.writeDurAProcs(fL,nL))
@@ -1288,8 +1288,8 @@ if __name__=="__main__":
     #PlotSpaceExtrapolates()
     #DifferenceTableSI('SIandLI')
     #PlotRefSolutions()
-    #FigureWorkPrecision('LI') #'SI','LI'
+    FigureWorkPrecision('SI') #'SI','LI'
     #studyFinest()
     #TestTimeIE()
-    Test()
+    #Test()
     

tools/evaluation/utility/computing.py

@@ -24,7 +24,8 @@ def MaxNorm(V,withabs=False):
                 maxI=i
     print(len(V),maxI)
     return max
- def evaluateRightLength(f,dt,T):
+
+def evaluateRightLength(f,dt,T):
     NewF=[]
     numberOfNormSteps = getnumberOfNormSteps(T,dt)
     if len(f)>=numberOfNormSteps:

tools/evaluation/utility/plotting.py

@@ -326,7 +326,7 @@ class Plot:
         plt.close()
         return(plotname,minproc)
         
-    def workPrecisionInTime(self,L,J,l,fL,nL,refPath,eP,p,ydes,timeunit='min'):
+    def workPrecisionInTime(self,L,J,l,fL,nL,refPath,eP,p,ydes,procscale =0,timeunit='min'):
         (t,Ref)=read.getDataFromTXT(refPath,read.createFilename(L,J,self.m),p)
         normRef=comp.L2(Ref,self.sdt,self.T,J,False)
         minproc=1000000000
@@ -354,6 +354,8 @@ class Plot:
             errorA.append(errorL)
             durA.append(durL)
             procA.append(procsL)
+        if procscale!=0:
+            minproc=procscale
         for index in range(len(fL)):
             for k in range(len(procA[index])):
                 factor=procA[index][k]/minproc