Ported aerialvision to use python3 instead of python2

1 files changed, 18 insertions, 17 deletions

diff --git a/aerialvision/organizedata.py b/aerialvision/organizedata.py
index 090b90f..f5d5312 100644
--- a/aerialvision/organizedata.py
+++ b/aerialvision/organizedata.py
@@ -99,7 +99,7 @@ def organizedata(fileVars):
     }
     data_type_char = {int:'I', float:'f'}
 
-    print "Organizing data into internal format..."
+    print("Organizing data into internal format...")
 
     # Organize globalCycle in advance because it is used as a reference
     if ('globalCycle' in fileVars):
@@ -107,28 +107,28 @@ def organizedata(fileVars):
         fileVars['globalCycle'].data = organizeFunction[statData.organize](statData.data, data_type_char[statData.datatype])
 
     # Organize other stat data into internal format
-    for statName, statData in fileVars.iteritems():
+    for statName, statData in fileVars.items():
         if (statName != 'CFLOG' and statName != 'globalCycle' and statData.organize != 'custom'):
             fileVars[statName].data = organizeFunction[statData.organize](statData.data, data_type_char[statData.datatype])
   
     # Custom routines to organize stat data into internal format
-    if fileVars.has_key('averagemflatency'):
+    if 'averagemflatency' in fileVars:
         zeros = []
         for count in range(len(fileVars['averagemflatency'].data),len(fileVars['globalCycle'].data)):
             zeros.append(0)
         fileVars['averagemflatency'].data = zeros + fileVars['averagemflatency'].data
 
-    if (skipCFLog == 0) and fileVars.has_key('CFLOG'):
+    if (skipCFLog == 0) and 'CFLOG' in fileVars:
         ptxFile = CFLOGptxFile
         statFile = CFLOGInsnInfoFile
         
-        print "PC Histogram to CUDA Src = %d" % convertCFLog2CUDAsrc
+        print("PC Histogram to CUDA Src = %d" % convertCFLog2CUDAsrc)
         parseCFLOGCUDA = convertCFLog2CUDAsrc
 
         if parseCFLOGCUDA == 1:
-            print "Obtaining PTX-to-CUDA Mapping from %s..." % ptxFile
+            print("Obtaining PTX-to-CUDA Mapping from %s..." % ptxFile)
             map = lexyacctexteditor.ptxToCudaMapping(ptxFile.rstrip())
-            print "Obtaining Program Range from %s..." % statFile
+            print("Obtaining Program Range from %s..." % statFile)
             maxStats = max(lexyacctexteditor.textEditorParseMe(statFile.rstrip()).keys())
 
         if parseCFLOGCUDA == 1:
@@ -136,7 +136,7 @@ def organizedata(fileVars):
             for lines in map:
                 for ptxLines in map[lines]:
                     newMap[ptxLines] = lines
-            print "    Total number of CUDA src lines = %s..." % len(newMap)
+            print("    Total number of CUDA src lines = %s..." % len(newMap))
             
             markForDel = []
             for ptxLines in newMap:
@@ -144,7 +144,7 @@ def organizedata(fileVars):
                     markForDel.append(ptxLines)
             for lines in markForDel:
                 del newMap[lines]
-            print "    Number of touched CUDA src lines = %s..." % len(newMap)
+            print("    Number of touched CUDA src lines = %s..." % len(newMap))
     
         fileVars['CFLOGglobalPTX'] = vc.variable('',2,0)
         fileVars['CFLOGglobalCUDA'] = vc.variable('',2,0)
@@ -152,7 +152,7 @@ def organizedata(fileVars):
         count = 0
         for iter in fileVars['CFLOG']:
 
-            print "Organizing data for %s" % iter
+            print("Organizing data for %s" % iter)
 
             fileVars[iter + 'PTX'] = fileVars['CFLOG'][iter]
             fileVars[iter + 'PTX'].data = CFLOGOrganizePTX(fileVars['CFLOG'][iter].data, fileVars['CFLOG'][iter].maxPC)
@@ -174,7 +174,7 @@ def organizedata(fileVars):
                             for columns in range(0, len(fileVars[iter + 'CUDA'].data[rows])): 
                                 fileVars['CFLOGglobalCUDA'].data[rows][columns] += fileVars[iter + 'CUDA'].data[rows][columns]
             except:
-                print "Error in generating globalCFLog data"
+                print("Error in generating globalCFLog data")
 
             count += 1
         del fileVars['CFLOG']
@@ -231,10 +231,10 @@ def nullOrganizedStackedBar(nullVar, datatype_c):
         for row in range (0,len(organized)):
             newy = array.array(datatype_c, [0 for col in range(newLen)])
             for col in range(0, len(organized[row])):
-                newcol = col / n_data
+                newcol = int(col / n_data)
                 newy[newcol] += organized[row][col]
             for col in range(0, len(newy)):
-                newy[col] /= n_data 
+                newy[col] = int(newy[col]/n_data) 
             organized[row] = newy
 
     return organized
@@ -320,15 +320,15 @@ def CFLOGOrganizeCuda(list, ptx2cudamap):
     nSamples = len(list[0])
 
     # create a dictionary of empty data array (one array per cuda source line)
-    for ptxline, cudaline in ptx2cudamap.iteritems():
-        if tmp.has_key(cudaline):
+    for ptxline, cudaline in ptx2cudamap.items():
+        if cudaline in tmp:
             pass
         else:
             tmp[cudaline] = [0 for lengthData in range(nSamples)]
 
 
     for cudaline in tmp:
-        for ptxLines, mapped_cudaline in ptx2cudamap.iteritems():
+        for ptxLines, mapped_cudaline in ptx2cudamap.items():
             if mapped_cudaline == cudaline:
                 for lengthData in range(nSamples):
                     tmp[cudaline][lengthData] += list[ptxLines][lengthData]
@@ -336,7 +336,7 @@ def CFLOGOrganizeCuda(list, ptx2cudamap):
     
     final = []           
     for iter in range(min(tmp.keys()),max(tmp.keys())):
-        if tmp.has_key(iter):
+        if iter in tmp:
             final.append(tmp[iter])            
         else:
             final.append([0 for lengthData in range(nSamples)])
@@ -356,3 +356,4 @@ def CFLOGOrganizeCuda(list, ptx2cudamap):
 #    return organized
 
 
+