本文整理汇总了Python中worker.Worker.doTask方法的典型用法代码示例。如果您正苦于以下问题：Python Worker.doTask方法的具体用法？Python Worker.doTask怎么用？Python Worker.doTask使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类worker.Worker的用法示例。
在下文中一共展示了Worker.doTask方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: range
# 需要导入模块: from worker import Worker [as 别名]
# 或者: from worker.Worker import doTask [as 别名]
ys1 = []
ys2 = []
tally = []
for r in range(r_start, r_end + 1):
total = 0
maximum = 0
count = 0
worker = Worker(str(uuid.uuid1()), 0, p, r, 1, 1)
worker.addNoise(0, 0.1)
for i in range(0, runs):
ts = []
cs = []
for j in range(0, horizon):
task = tasks[j]
answer = worker.doTask(task, outcomes)
if answer == task:
count += 1
ts.append(j + 1)
cs.append(count)
learning = learn.learnCurve(cs, ts)
err = learning['e']
#print err
#print learning['r']
if math.isnan(err):
continue
if err < threshold:
total += j + 1
tally.append(j+1)
if j + 1 > maximum:
maximum = j + 1示例2: range
# 需要导入模块: from worker import Worker [as 别名]
# 或者: from worker.Worker import doTask [as 别名]
cqs = [] #cumulative quality
qs = [] #quality
aqs = [] #average quality
ecqs = [] #estimated by linear regression
eqs = [] #estimated by linear regression
fqs = []
###for learning
cs = []
ts = []
errs = []
count = 0
for i in range(0, len(tasks)):
task = tasks[i]
answer = worker.doTask(task)
if answer == task:
count += 1
cqs.append(worker.getCumulativeQuality(i + 1))
qs.append(worker.getQuality())
aqs.append(float(count) / float(i + 1))
#learn
ts.append(i + 1)
cs.append(count)
learning = learn.learnCurve(cs, ts)
fake = Worker(str(uuid.uuid1()), i+1, learning['p'], learning['r'], 1, 1)
ecqs.append(fake.getCumulativeQuality(i+1))
eqs.append(fake.getQuality())
errs.append(learning['e'])
if i == 0:
fqs.append(float(count) / float(i+1))