import argparse
import sys
import os
-
+import plot as pl
class AutoTunerArgParser:
def __init__(self):
self.parser = argparse.ArgumentParser(description='Parsing the output log of the CSolver auto tuner ...')
self.parser.add_argument('--folder', '-f', metavar='bin', type=str, nargs=1,help='output log of running the autotuner ...')
- self.parser.add_argument('--number', '-n', metavar='122', type=int, nargs=1,help='Number of runs ...')
self.args = self.parser.parse_args()
def getFolder(self):
return self.args.folder[0]
- def getRunNumber(self):
- return self.args.number[0]
+PROBLEMS = []
TUNABLEHEADER = ["DECOMPOSEORDER", "MUSTREACHGLOBAL", "MUSTREACHLOCAL", "MUSTREACHPRUNE", "OPTIMIZEORDERSTRUCTURE",
"ORDERINTEGERENCODING", "PREPROCESS", "NODEENCODING", "EDGEENCODING", "MUSTEDGEPRUNE", "ELEMENTOPT",
mystr=""
for header in TUNABLEHEADER:
mystr+=str(header)+","
- print >>file, mystr
+ file.write(mystr)
+ file.write("\n")
def dump(file, row):
global TUNABLEHEADER
mystr=""
+ data = []
for i in range(len(TUNABLEHEADER)):
mystr += row[TUNABLEHEADER[i]]+ ","
- print "mystr is:"+ mystr
- print >>file, mystr
+ data.append(row[TUNABLEHEADER[i]])
+ print ("mystr is:"+ mystr)
+ file.write(mystr)
+ file.write("\n")
+ return data
def loadTunerInfo(row, filename):
with open(filename) as f:
for line in f:
numbers = re.findall('\d+',line)
- numbers = map(int,numbers)
+ numbers = list(map(int,numbers))
row[TUNABLEHEADER[numbers[3]]] = row[TUNABLEHEADER[numbers[3]]] + str(numbers[7])
def loadSolverTime(row, filename):
row["EXECTIME"] = configs["EXECTIME"]
def loadProblemName(row,filename):
+ global PROBLEMS
with open(filename) as f:
- row["PROBLEM"] = f.readline().replace("\n","")
+ problem = f.readline().replace("\n","")
+ probNumber = int(f.readline())
+ if probNumber >= len(PROBLEMS):
+ PROBLEMS.insert(probNumber,problem)
+ elif PROBLEMS[probNumber] != problem:
+ PROBLEMS[probNumber] = problem
+ row["PROBLEM"] = problem
+
def loadTunerNumber(row, filename):
with open(filename) as f:
row["TUNERNUMBER"] = f.readline().replace("\n","")
argprocess = AutoTunerArgParser()
printHeader(file)
rows = []
- for i in range(argprocess.getRunNumber()):
+ data = []
+ i = 0
+ while True :
row = {"DECOMPOSEORDER" : "",
"MUSTREACHGLOBAL" : "",
"MUSTREACHLOCAL" : "",
"EXECTIME": "",
"TUNERNUMBER":""
}
- loadTunerNumber(row, argprocess.getFolder() + "/tunernum" + str(i))
- loadTunerInfo(row, argprocess.getFolder()+"/tuner"+str(i)+"used")
- loadSolverTime(row, argprocess.getFolder()+"/log"+str(i))
- loadProblemName(row, argprocess.getFolder()+"/problem"+str(i))
- dump(file, row)
- rows.append(row)
- return rows
-
-def tunerNumberAnalysis(file, rows):
+ try:
+ loadTunerNumber(row, argprocess.getFolder() + "/tunernum" + str(i))
+ loadTunerInfo(row, argprocess.getFolder()+"/tuner"+str(i)+"used")
+ loadSolverTime(row, argprocess.getFolder()+"/log"+str(i))
+ loadProblemName(row, argprocess.getFolder()+"/problem"+str(i))
+ data.append(dump(file, row))
+ rows.append(row)
+ except IOError:
+ break
+ i += 1
+ return rows, data
+
+def tunerCountAnalysis(file, rows):
global TUNABLEHEADER
+ global PROBLEMS
tunercount = {}
tunernumber = {}
for row in rows:
mystr=""
for i in range(18):
- mystr+=row[TUNABLEHEADER[i]]
+ if not row[TUNABLEHEADER[i]]:
+ mystr += "."
+ else:
+ mystr+=row[TUNABLEHEADER[i]]
if mystr not in tunercount:
tunercount.update({mystr : 1})
tunernumber.update({mystr : str(row["TUNERNUMBER"])})
tunernumber[mystr] += "-" + str(row["TUNERNUMBER"])
problems = set(map(lambda x: x["PROBLEM"], rows))
- print "Number of repititive tuners"
+ print ("Number of repititive tuners")
for key in tunercount:
if tunercount[key] > 1:
- print key + "(ids:" + tunernumber[key] + ") = #" + str(tunercount[key])
+ print( key + "(ids:" + tunernumber[key] + ") = #" + str(tunercount[key]) )
+
+def combineRowForEachTuner(rows):
+ global PROBLEMS
+ newRows = []
+ combined = None
+ for row in rows:
+ if row["PROBLEM"] == PROBLEMS[0]:
+ combined = row
+ for key in row:
+ if row[key]:
+ combined[key] = row[key]
+ if row["PROBLEM"] == PROBLEMS[len(PROBLEMS)-1]:
+ newRows.append(combined)
+ return newRows
+
+def transformDataset(rows):
+ print(rows)
def main():
+ global TUNABLEHEADER
file = open("tuner.csv", "w")
- rows = analyzeLogs(file)
- tunerNumberAnalysis(file, rows)
+ rows, data = analyzeLogs(file)
+ tunerCountAnalysis(file, combineRowForEachTuner(rows) )
file.close()
- return
+ #transformDataset(data)
+ pl.plot(data, TUNABLEHEADER)
+
if __name__ == "__main__":
main()