def modifyfile(filename):
f = open(filename, 'rU')
lines = f.readlines()
f.close()
data = []
processes=[]
for line in lines:
if line.startswith("imax"):
data.append(line.strip().split())
imax = int(line.strip().split()[1])
elif line.startswith("rate"):
rateList = ['rate','']
nprocess = len(line.strip().split()[1:])/imax
#ColumnsToModify = linspace(2,(imax-1)*nprocess+2,imax)
ColumnsToModify=[]
for i in range(len(processes)):
if process in processes[i]: ColumnsToModify.append(i+1)
i=1
for item in line.strip().split()[1:]:
if i in ColumnsToModify:
itemtemp = float(mu)*float(item)
rateList.append(str(itemtemp))
else:
rateList.append(item)
i+=1
data.append(rateList)
elif line.startswith("----"): data.append(['break'])
elif (line.startswith("Observation") or line.startswith("shapes")): data.append([line.strip().split()[0],'','','']+line.strip().split()[1:])
elif (line.startswith("bin") or line.startswith("process")):
data.append([line.strip().split()[0],'']+line.strip().split()[1:])
if line.startswith("process") and not processes:
processes=line.strip().split()[1:]
else: data.append(line.strip().split())
out=open(output,'w')
printTable(data,out)
def modifyfile(filename):
f = open(filename, 'rU')
lines = f.readlines()
f.close()
data = []
for line in lines:
if line.startswith("imax"):
data.append(line.strip().split())
imax = int(line.strip().split()[1])
elif line.startswith("rate"):
rateList = ['rate', '']
nprocess = len(line.strip().split()[1:]) / imax
ColumnsToModify = linspace(2, (imax - 1) * nprocess + 2, imax)
i = 1
for item in line.strip().split()[1:]:
if i in ColumnsToModify:
itemtemp = float(mu) * float(item)
rateList.append(str(itemtemp))
else:
rateList.append(item)
i += 1
data.append(rateList)
elif line.startswith("----"):
data.append(['break'])
elif (line.startswith("Observation") or line.startswith("shapes")):
data.append([line.strip().split()[0], '', '', ''] +
line.strip().split()[1:])
elif (line.startswith("bin") or line.startswith("process")):
data.append([line.strip().split()[0], ''] +
line.strip().split()[1:])
else:
data.append(line.strip().split())
out = open('dataCard.txt', 'w')
printTable(data, out)
def show():
print u"\n\n\n +++++++++++++你已经进入流水相关服务 ： +++++++++++++"
cardNo = sql.readLoginCardNo()
if not cardNo:
print u"请先登录..."
login.loginStart()
cardNo = sql.readLoginCardNo()
while True:
utils.printTable(flowService)
num = raw_input(u"请选择对应服务 或者 输入q退出 ：")
if num == 'q': break
regex = re.compile(r"\d+")
if (not regex.match(num)) or ( int(num) >= len(flowService)):
print u"请输入正确服务号码"
continue
num = int(num)
break
result = flowService[num].values().pop()()
if not result :
print u"无任何记录"
return True
for t in result:
tmpDict = {'type':t.get('type'),'money':t.get('money')}
tmpDict['time'] = time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(t.get('time')))
print tmpDict
return True
def main(inputRfilename, outputRfilename, inputDCfilename, outputDCfilename, threshold, thresholdBG):
input = ROOT.TFile(inputRfilename, 'READ')
output = ROOT.TFile(outputRfilename, 'RECREATE')
data = []
olddata, binList, processList = readOldDataCard(inputDCfilename)
data += olddata
newdata = walk_and_copy(input, output, threshold, thresholdBG, binList, processList)
data += newdata
out=open(outputDCfilename,'w')
printTable(data,out)
def main(inputRfilename, outputRfilename, inputDCfilename, outputDCfilename):
input = ROOT.TFile(inputRfilename, 'READ')
output = ROOT.TFile(outputRfilename, 'RECREATE')
if not os.path.exists(inputDCfilename[:-4] + '_original.txt'):
os.system('mv ' + inputDCfilename + ' ' + inputDCfilename[:-4] +
'_original.txt')
data = readDataCard(inputDCfilename[:-4] + '_original.txt')
out = open(inputDCfilename, 'w')
printTable(data, out)
walk_and_copy(input, output)
def main(inputDCfile, inputDCfile0P, outputDCfile0P, inputDCfile0M, outputDCfile0M): data0P = [] dataOld0P, dictOld0P = readDataCard(inputDCfile0P) data0P += dataOld0P dataNew0P = addStatShapes(inputDCfile, dictOld0P, dataOld0P[-1]) data0P += dataNew0P out0P=open(outputDCfile0P,'w') printTable(data0P,out0P) data0M = [] dataOld0M, dictOld0M = readDataCard(inputDCfile0M) data0M += dataOld0M dataNew0M = addStatShapes(inputDCfile, dictOld0M, dataOld0M[-1]) data0M += dataNew0M out0M=open(outputDCfile0M,'w') printTable(data0M,out0M)
def main(inputRfilename, input2dRfilename, outputRfilename, inputDCfilename,
outputDCfilename, threshold, thresholdBG, thresholdSignal, p0m, p1m,
p0h, p1h):
input = ROOT.TFile(inputRfilename, 'READ')
input2d = ROOT.TFile(input2dRfilename, 'READ')
output = ROOT.TFile(outputRfilename, 'RECREATE')
data = []
olddata, binList, processLists = readOldDataCard(inputDCfilename)
data += olddata
newdataS, newdataT = walk_and_copy(input, input2d, output, threshold,
thresholdBG, thresholdSignal, binList,
processLists, p0m, p1m, p0h, p1h)
data += newdataT
data += newdataS
out = open(outputDCfilename, 'w')
printTable(data, out)
from utils import readFilePairs, printTable
from calculateMakespan import calculateMakespan
from plotResult import plotResult
sequence = [
11, 10, 9, 2, 1, 13, 8, 0, 2, 4, 13, 0, 4, 4, 5, 0, 7, 4, 5, 11, 12, 12, 4,
10, 5, 2, 11, 6, 6, 3, 12, 6, 0, 9, 9, 14, 1, 12, 7, 9, 13, 2, 6, 14, 2, 8,
5, 3, 6, 5, 12, 9, 8, 1, 4, 6, 7, 1, 10, 14, 3, 7, 6, 11, 14, 14, 8, 0, 1,
7, 9, 5, 9, 10, 2, 4, 3, 13, 5, 4, 3, 12, 6, 0, 7, 12, 6, 11, 2, 0, 8, 12,
13, 2, 2, 6, 12, 0, 8, 6, 13, 13, 11, 10, 10, 3, 10, 1, 13, 12, 9, 1, 1, 1,
14, 2, 7, 10, 14, 0, 11, 14, 11, 9, 4, 11, 3, 9, 6, 12, 11, 10, 13, 10, 4,
9, 7, 7, 5, 10, 8, 13, 3, 0, 12, 6, 2, 7, 14, 2, 1, 2, 8, 11, 14, 9, 8, 0,
8, 4, 2, 1, 7, 1, 10, 3, 7, 5, 7, 1, 8, 14, 11, 8, 3, 11, 3, 0, 13, 13, 10,
3, 5, 1, 6, 9, 4, 12, 4, 7, 3, 0, 14, 14, 5, 4, 14, 7, 0, 13, 12, 11, 14,
3, 13, 6, 1, 8, 9, 4, 3, 10, 9, 2, 12, 10, 5, 5, 11, 13, 5, 8, 5, 0, 8
]
times, machines, n = readFilePairs("cases/15_15_1")
result, table = calculateMakespan(times, machines, sequence, n)
print("RESULT: %s" % result)
print("Sequence: ")
print(sequence)
printTable(table)
plotResult(table, result)
def genetic(times, machines, n, population_number, iterations, rate, target):
machine_number = len(machines[0])
start_time = time.time()
def sortAndGetBestIndividual(population):
best_individual = None
best_result = None
for individual in population:
result = None
if not individual[1]:
result, table = calculateMakespan(times, machines, individual[0], n)
individual[1] = result
else:
result = individual[1]
if not best_result or result < best_result:
best_result = result
best_individual = individual
population.sort(key=lambda x: x[1])
return best_individual, best_result
population = generate_population(population_number, n, machine_number)
global_best_ind, global_best = sortAndGetBestIndividual(population)
##if we don't define a target we set the number of iterations we want
if not target:
for i in range(iterations):
population = evolve(population, rate)
best_ind, best_result = sortAndGetBestIndividual(population)
total_fitness, diffPercentage = getFitness(population)
if(not global_best or best_result < global_best):
global_best = best_result
global_best_ind = copy.deepcopy(best_ind)
printProgress(best_result, i, time.time() - start_time)
checkDiversity(population, diffPercentage, n, machine_number)
else:
#If we define a target we iterate until the best result reach that target
i = 0
while(target < global_best):
i += 1
#in every iteration:
#We evolve the population
population = evolve(population, rate)
#We find the best individual
best_ind, best_result = sortAndGetBestIndividual(population)
#We calculate the diversity % between the population and the total_fitness(sum of all the results)
total_fitness, diffPercentage = getFitness(population)
#if the result found is better than the global found we update the global
if(not global_best or best_result < global_best):
global_best = best_result
global_best_ind = copy.deepcopy(best_ind)
#We print the progress so far and the time elapsed
printProgress(best_result, i, time.time() - start_time)
#We check the diversity, in case the diversity percentage is very low we delete a number of the population and we add randome members
checkDiversity(population, diffPercentage, n, machine_number)
best_result, best_table = calculateMakespan(times, machines, global_best_ind[0], n)
print("\nOVERALL RESULT")
print("RESULT: %s" %best_result)
print('the elapsed time:%ss'% (int(time.time() - start_time)))
print("Permutation: ")
print(fromPermutation(global_best_ind[0], n))
printTable(best_table)
plotResult(best_table, best_result)
def toTxt(self, fileName):
out = open(fileName, 'w')
printTable(self.data, out)
def toTxt(self, fileName):
out=open(fileName,'w')
printTable(self.data,out)
def main():
""" Main function to run Paper Trail program. """
# Load database. If none exists, create one.
papersDir = os.path.dirname(DB_PATH)
if not os.path.isdir(papersDir):
os.makedirs(papersDir)
if os.path.isfile(DB_PATH):
with open(DB_PATH, 'rb') as f:
database = pickle.load(f)
else:
database = Database()
# Action loop
while True:
print_action_prompt()
action = input()
print("")
if action == '1':
# Get table name to print.
print("Enter table name. Should be either 'papers', 'authors', or"\
" 'topics': ", end="")
tableName = input()
while tableName not in ['papers', 'authors', 'topics']:
print("Invalid table name! Try again: ", end="")
tableName = input()
# Call utils to print table
printTable(database, tableName)
elif action == '2':
# Collect paper information from link.
print("Enter link to paper: ", end="")
link = input()
paperArgs = getBibInfo(link)
# Check for error opening paper.
if 'err' in paperArgs:
print("%s\n" % paperArgs['err'])
continue
# Get labels from user
print("Enter topic names separated by commas: ", end="")
paperArgs['topicNames'] = [
label.strip() for label in input().split(",")
]
# Get parents from user
print("Enter name of parent papers. "\
"If no parents, just press enter: ", end="")
parents = input().split()
while not all([parent in database.papers for parent in parents]):
print("Unrecognized parent name! Try again:")
parents = input().split()
paperArgs['parents'] = parents
# Get children from user
print("Enter name of child papers. "\
"If no children, just press enter: ", end="")
children = input().split()
while not all([child in database.papers for child in children]):
print("Unrecognized child name! Try again:")
children = input().split()
paperArgs['children'] = children
# Add misc info
paperArgs['dateAdded'] = datetime.datetime.now().strftime(
"%m/%d/%Y")
paperArgs['dateRead'] = ""
paperArgs['link'] = link
paperArgs['read'] = False
paperArgs['notes'] = ""
# Create paper object and add it to database
database.addPaper(Paper(**paperArgs))
print("Paper added!\n")
elif action == '3':
# Get name of paper to delete
print("Name of paper: ", end="")
paperName = input()
# Create and execute SQL command
if paperName in database.papers:
del database.papers[paperName]
print("Paper '%s' removed!\n" % paperName)
else:
print("Paper '%s' not in database!\n" % paperName)
else:
print("Goodbye!\n")
break
# Save database
with open(DB_PATH, 'wb') as f:
pickle.dump(database, f)
