def main():
import profile
import pstats
if len(sys.argv[1:]):
profile_it = 0
reps_flag = 0
profile_reps = 100
for arg in sys.argv[1:]:
if reps_flag:
profile_reps = int(arg)
reps_flag = 0
elif arg == "-p" or arg == "--profile":
profile_it = 1
elif arg == "-r" or arg == "--reps":
reps_flag = 1
elif profile_it > 0:
print "Profiling, " + str(profile_reps) + " repetitions..."
page = page_factory.page(arg)
profile.run('benchmark("' + arg + '", ' + str(profile_reps) + ")", "profile_stats")
p = pstats.Stats("profile_stats")
p.sort_stats("time").print_stats()
else:
print page_factory.page(URI(arg))
else:
profile()
def main():
import profile
import pstats
if len(sys.argv[1:]):
profile_it = 0
reps_flag = 0
profile_reps = 100
for arg in sys.argv[1:]:
if reps_flag:
profile_reps = int(arg)
reps_flag = 0
elif arg == '-p' or arg == '--profile':
profile_it = 1
elif arg == '-r' or arg == '--reps':
reps_flag = 1
elif profile_it > 0:
print 'Profiling, ' + str(profile_reps) + ' repetitions...'
page = page_factory.page(arg)
profile.run(
'benchmark("' + arg + '", ' + str(profile_reps) + ')',
'profile_stats')
p = pstats.Stats('profile_stats')
p.sort_stats('time').print_stats()
else:
print page_factory.page(URI(arg))
else:
profile()
def serve(app, **kw):
_server = kw.pop("_server", create_server) # test shim
_quiet = kw.pop("_quiet", False) # test shim
_profile = kw.pop("_profile", False) # test shim
if not _quiet: # pragma: no cover
# idempotent if logging has already been set up
logging.basicConfig()
server = _server(app, **kw)
if not _quiet: # pragma: no cover
server.print_listen("Serving on http://{}:{}")
if _profile: # pragma: no cover
profile("server.run()", globals(), locals(), (), False)
else:
server.run()
def serve(app, **kw):
_server = kw.pop("_server", create_server) # test shim
_quiet = kw.pop("_quiet", False) # test shim
_profile = kw.pop("_profile", False) # test shim
if not _quiet: # pragma: no cover
# idempotent if logging has already been set up
logging.basicConfig()
server = _server(app, **kw)
if not _quiet: # pragma: no cover
print("serving on http://%s:%s" % (server.effective_host, server.effective_port))
if _profile: # pragma: no cover
profile("server.run()", globals(), locals(), (), False)
else:
server.run()
def serve(app, **kw):
_server = kw.pop('_server', create_server) # test shim
_quiet = kw.pop('_quiet', False) # test shim
_profile = kw.pop('_profile', False) # test shim
if not _quiet: # pragma: no cover
# idempotent if logging has already been set up
logging.basicConfig()
server = _server(app, **kw)
if not _quiet: # pragma: no cover
server.print_listen('Serving on http://{}:{}')
if _profile: # pragma: no cover
profile('server.run()', globals(), locals(), (), False)
else:
server.run()
def serve(app, **kw):
_server = kw.pop('_server', create_server) # test shim
_quiet = kw.pop('_quiet', False) # test shim
_profile = kw.pop('_profile', False) # test shim
if not _quiet: # pragma: no cover
# idempotent if logging has already been set up
logging.basicConfig()
server = _server(app, **kw)
if not _quiet: # pragma: no cover
print('serving on http://%s:%s' %
(server.effective_host, server.effective_port))
if _profile: # pragma: no cover
profile('server.run()', globals(), locals(), (), False)
else:
server.run()
def serve(app, **kw):
_server = kw.pop('_server', WSGIServer) # test shim
_quiet = kw.pop('_quiet', False) # test shim
_profile = kw.pop('_profile', False) # test shim
if not _quiet: # pragma: no cover
# idempotent if logging has already been set up
logging.basicConfig()
server = _server(app, **kw)
if not _quiet: # pragma: no cover
print('serving on http://%s:%s' % (server.effective_host,
server.effective_port))
if _profile: # pragma: no cover
profile('server.run()', globals(), locals(), (), False)
else:
server.run()
def main(args=None, test=False):
assert os.name == "posix", "This code makes Unix-specific assumptions"
# if we hup, restart by making a new Supervisor()
first = True
while 1:
options = ServerOptions()
options.realize(args, doc=__doc__)
options.first = first
options.test = test
if options.profile_options:
sort_order, callers = options.profile_options
profile('go(options)', globals(), locals(), sort_order, callers)
else:
go(options)
if test or (options.mood < SupervisorStates.RESTARTING):
break
options.close_httpservers()
options.close_logger()
first = False
def main(args=None, test=False):
assert os.name == "posix", "This code makes Unix-specific assumptions"
# if we hup, restart by making a new Supervisor()
first = True
while 1:
options = ServerOptions()
options.realize(args, doc=__doc__)
options.first = first
options.test = test
if options.profile_options:
sort_order, callers = options.profile_options
profile('go(options)', globals(), locals(), sort_order, callers)
else:
go(options)
if test or (options.mood < SupervisorStates.RESTARTING):
break
options.close_httpservers()
options.close_logger()
first = False
def PSSM(seq, sc, residues, S):
'''This function return a PSSM given a sequence, a substitution matrix, a list of possible residues or nucleotides and a multiple alignment'''
f = profile(S, residues)
M = []
for i in range(len(seq)):
a = seq[i]
tmp = []
for j in range(len(f)):
acc = 0.0
for b in residues:
acc = acc + f[j].get(a, 0) * sc.get((a, b), 0)
tmp.append(acc)
M.append(tmp)
return M
def main(args=None, test=False):
assert os.name == "posix", "This code makes Unix-specific assumptions"
# if we hup, restart by making a new Supervisor()
first = True
# while 1:
if 1:
options = ServerOptions()
# attribute_value = options.__dict__
# for key,value in attribute_value.items():
# print(key,value)
# __doc__ 该文件下
options.realize(args, doc=__doc__)
options.first = first
options.test = test
if options.profile_options:
sort_order, callers = options.profile_options
profile('go(options)', globals(), locals(), sort_order, callers)
else:
go(options)
options.close_httpservers()
options.close_logger()
first = False
# setting profile.Profile.bias improves the performance measurement,
# but you have to determine the correct value for your specific machine
# first.
# profile.Profile.bias = 0.0000106
profile.run(what, 'profile')
import pstats
profile = pstats.Stats('profile')
profile.strip_dirs().sort_stats('cumulative').print_stats(32)
profile.strip_dirs().sort_stats('time').print_stats(20)
def main(start_state=None):
puit.gamemaster = Gamemaster(start_state)
puit.gamemaster.start()
if __name__ == '__main__':
import getopt, sys
options, args = getopt.getopt(sys.argv[1:], 'pt:', ['profile', 'test='])
do_profile = False
test = None
for opt, arg in options:
if opt in ('-p', '--profile'):
do_profile = True
elif opt in ('-t', '--test'):
test = arg
if do_profile:
if test is None:
profile('main()')
else:
profile('main(start_state="' + test + '")')
else:
main(start_state=test)
pr.dump_stats(filename)
return result
def speed_test(uuid):
try:
print("Starting speed test")
t0 = time.time()
with SessionContext(commit = True) as session:
# Load the article
a = Article.load_from_uuid(uuid, session)
if a is not None:
# Parse it and store the updated version
a.parse(session, verbose = True)
t1 = time.time()
print("Parsing finished in {0:.2f} seconds".format(t1 - t0))
finally:
Article.cleanup()
print("Welcome to speedtest")
Settings.read(os.path.join(basepath, "config/Reynir.conf"))
with Fast_Parser() as fp:
pass
#speed_test("dbc585e4-736c-11e6-a2bb-04014c605401")
profile(speed_test, "dbc585e4-736c-11e6-a2bb-04014c605401")
print("speedtest done")
##################################################
# for testing/debug performance only
# https://www.clips.uantwerpen.be/tutorials/python-performance-optimization
def profile(function, *args, **kwargs):
""" Returns performance statistics (as a string) for the given function.
"""
def _run():
function(*args, **kwargs)
import cProfile as profile
import pstats
import os
import sys
sys.modules['__main__'].__profile_run__ = _run
id = function.__name__ + '()'
profile.run('__profile_run__()', id)
p = pstats.Stats(id)
p.stream = open(id, 'w')
p.sort_stats('time').print_stats(20)
p.stream.close()
s = open(id).read()
os.remove(id)
return s
###################################################
# Main()
if __name__ == '__main__':
print(profile(Run))
from random import randrange
import profile
def disjoin1(A, B, C):
"""Return True if there is no element common to all three lists."""
for a in A:
for b in B:
for c in C:
if a == b == c: # Common value found
return False
return True
def disjoin2(A, B, C):
for a in A:
for b in B:
if a == b: # only check C if A && B
for c in C:
if a == c: # Common value found
return False
return True
data_1 = [ randrange(0, 100) for k in range(0, 10 * 3)]
data_2 = [ randrange(0, 100) for k in range(0, 10 * 3)]
data_3 = [ randrange(0, 100) for k in range(0, 10 * 3)]
profile(disjoin1, )
return table[b]
from itertools import permutations
perm = permutations([1,2,3])
for i in list(perm):
print i
import profile
def fib(n):
if n==0:
return 0
elif n==1:
return 1
else:
return fib(n-1) + fib(n-2)
fib = profile(fib)
fib(20)
x=[1,2,3,4]
y=reversed(x)
y.next()
def grep(pattern, dir):
for f in dir:
for line in open(f):
if pattern in line:
print line,
grep(".py","Downloads")
def update_windowT(
source_path='', #输入视频(raw)帧本地路径
start_frameW='',
end_frameW='', # 以确定需要处理的video window
segment_time='',
knob_values='', # 所有对应的knob的取值空间
k='', # top-k的k的值
inputFps='',
profile_time=None,
golden_configration=None, #作为ground truth的configration / k个中选一个最佳为的次优ground truth（分析窗口的第一个段与剩余段的ground truth不同）
configrationW=None, #该 window的k个configration
isLeader=None,
cost=None,
analyseConfigration=None,
cover_thre=None,
f1_thre=None,
pipe=None,
lock=None):
i = 0
configration = [] # 存储该profilewindow每个segment最佳的configration
# 对leader video的profile window的第一个segment进行configration的全分析（取segment前一秒）
# 返回top-k的configration
start_frameP = start_frameW
end_frameP = start_frameW + profile_time * inputFps
if end_frameP > end_frameW:
end_frameP = end_frameW
#检查configrationW是否为空，一般不会执行
if configrationW == None:
configrationW = profile(source_path, start_frameP, end_frameP,
knob_values, k, golden_configration, cost,
inputFps, cover_thre, f1_thre)
####configrationW=[[2,[1280,720]],[5,[1280,960]],[15,[1280,720]],[2,[1280,960]],[5,[1280,720]]]
if isLeader == 1:
#第一个segment的最佳configration即为configrationW的第0个
configration.append(configrationW[0])
#segment的起始帧、结束帧
start_frameS = start_frameW
end_frameS = start_frameS + segment_time * int(inputFps)
if end_frameS > end_frameW:
end_frameS = end_frameW
#获取configration中各knob的具体值
if start_frameS % 4 > 2:
frame_rate = 5
image_W = 1200
image_H = 720
else:
frame_rate = configrationW[0][0]
image_W = configrationW[0][1][0]
image_H = configrationW[0][1][1]
#更新analyseConfigration
lock.acquire()
analyseConfigration[0] = frame_rate
analyseConfigration[1][0] = image_W
analyseConfigration[1][1] = image_H
lock.release()
#setAnalyseConfigration(frame_rate,image_W,image_H)
print("\n第", start_frameS, "-", end_frameS, "帧的segment的configration:",
frame_rate, image_W, image_H, "\n")
#yolo_video(source_path,start_frameS,end_frameS,frame_rate,image_H,image_W,inputFps,pipe)
#对profile window中从leader第二个/follower的第一个 segment开始的其余segment进行top-k中的configration的分析
#对knob_values进行更新
knob_valuesK = [None] * len(configrationW[0])
#最佳的k个configration中包含的knob值
i = 0
while i < len(configrationW[0]):
knob_valuesK[i] = []
i = i + 1
for conf in configrationW:
i = 0
while i < len(configrationW[0]):
tag = 1
for kn in knob_valuesK[i]:
if conf[i] == kn:
tag = -1
break
if tag == 1:
knob_valuesK[i].append(conf[i])
i = i + 1
print("knob_valuesK", knob_valuesK)
if isLeader == 1:
start_frameP = start_frameW + segment_time * inputFps # 第二个segment的开始帧
else:
start_frameP = start_frameW
while start_frameP < end_frameW:
k = 1 #top-k的值
end_frameP = start_frameP + profile_time * inputFps #取segmet前一秒
if end_frameP > end_frameW:
end_frameP = end_frameW
space_configration = configrationW
print("")
print("start_frameP" + str(start_frameP) + ",end_frameP" +
str(end_frameP))
configrationS = profile(source_path, start_frameP, end_frameP,
knob_valuesK, k, golden_configration, cost,
inputFps, cover_thre, f1_thre,
space_configration, knob_values)
##########开始回传video
#segment的起始帧、结束帧
start_frameS = start_frameP
end_frameS = start_frameS + segment_time * int(inputFps)
if end_frameS > end_frameW:
end_frameS = end_frameW
#获取configration中各knob的具体值
frame_rate = configrationS[0]
image_W = configrationS[1][0]
image_H = configrationS[1][1]
print("\n第", start_frameS, "-", end_frameS, "帧的segment的configration:",
frame_rate, image_W, image_H, "\n")
#更新analyseConfigration
lock.acquire()
analyseConfigration[0] = frame_rate
analyseConfigration[1][0] = image_W
analyseConfigration[1][1] = image_H
lock.release()
#setAnalyseConfigration(frame_rate,image_W,image_H)
#yolo_video(source_path,start_frameS,end_frameS,frame_rate,image_H,image_W,inputFps,pipe)
##################
configration.append(configrationS)
start_frameP = start_frameP + segment_time * inputFps
print("")
return configration
"""Return list such that, for all j, A[j] equals average of S[0], ..., S[j]."""
n = len(S)
A = [0] * n # allocate space for results
for j in range(n):
A[j] = sum(S[0:j+1]) / (j+1) # record average
return A
def prefix_average3(S):
"""Return list such that, for all j, A[j] equals average of S[0], ..., S[j]."""
n = len(S)
A = [0] * n
total = 0
for j in range(n):
total += S[j]
A[j] = total / (j+1)
return A
data_1 = [ k for k in range(0, 10 ** 3)]
data_2 = [ k for k in range(0, 10 ** 4)]
data_3 = [ k for k in range(0, 10 ** 5)]
data_sets = [data_1, data_2, data_3]
profile(prefix_average1, data_sets)
profile(prefix_average2, data_sets)
profile(prefix_average3, data_sets)
from random import randrange
import profile
def disjoin1(A, B, C):
"""Return True if there is no element common to all three lists."""
for a in A:
for b in B:
for c in C:
if a == b == c: # Common value found
return False
return True
def disjoin2(A, B, C):
for a in A:
for b in B:
if a == b: # only check C if A && B
for c in C:
if a == c: # Common value found
return False
return True
data_1 = [randrange(0, 100) for k in range(0, 10 * 3)]
data_2 = [randrange(0, 100) for k in range(0, 10 * 3)]
data_3 = [randrange(0, 100) for k in range(0, 10 * 3)]
profile(disjoin1, )
cv2.imshow("shrink", shrink)
cv2.imwrite("sample.jpg",shrink)
cv2.waitKey(0)
'''
'''
configrationR=[30,[1280,720]]
golden_configration=[30,[1280,960]]
label_locationR=[[],[],['car',(233,2),(519,96)],['car',(242,3),(521,97)],['car',(244,1),(523,97)]]
label_locationG=[[],[],['car',(233,4),(519,129)],['car',(233,4),(519,129)],['car',(233,4),(519,129)]]
f1=eval_f1(label_locationR,label_locationG,configrationR,golden_configration)
print("f1=",f1)
'''
'''
start_frame=601
end_frame=630
pathIn = './test_videos/sample2.mp4'
knob_valuesK=[None]*2
knob_valuesK[0]=[1,2]
knob_valuesK[1]=[[640,480],[1280,720],[1280,960]]
golden_configration=[30,[1280,960]]
space_configration=[[1,[640,480],[1,[1280,720]],[2,[640,480]],[2,[1280,720]],[1,[1280,960]]]
a=[1,2,5,10,30]
b=[[640,480],[1280,720],[1280,960]]
profile(pathIn,start_frame,end_frame,knob_valuesK,1,[30,[1280,960]],space_configration,knob_values)
'''
'''
print("hello_image")
pathIn = './test_imgs/image001834.jpg'
pr.dump_stats(filename)
return result
def speed_test(uuid):
try:
print("Starting speed test")
t0 = time.time()
with SessionContext(commit=True) as session:
# Load the article
a = Article.load_from_uuid(uuid, session)
if a is not None:
# Parse it and store the updated version
a.parse(session, verbose=True)
t1 = time.time()
print("Parsing finished in {0:.2f} seconds".format(t1 - t0))
finally:
Article.cleanup()
print("Welcome to speedtest")
Settings.read(os.path.join(basepath, "config/Greynir.conf"))
with Fast_Parser() as fp:
pass
#speed_test("dbc585e4-736c-11e6-a2bb-04014c605401")
profile(speed_test, "dbc585e4-736c-11e6-a2bb-04014c605401")
print("speedtest done")
home = os.path.abspath(user[5])
pl = os.path.join(home, "example.png")
pw = os.path.join(home, "example-pw.png")
sh = os.path.join(home, "example-sh.png")
m = draw()
# profit
m.save(pl)
print "wrote combined layers to %s" % pl
m.save(pw, "pinwin")
print "wrote pinwin layer to %s" % pw
m.save(sh, "shadow")
print "wrote shadow layer to %s" % sh
# hey look, code to run!
parser = optparse.OptionParser()
parser.add_option("-p", "--profile", action="store_true", help="run profiling stats", default=False)
(opts, args) = parser.parse_args()
if opts.profile :
profile()
else :
run()
_b = {}
for name, config in self.cfg['image']['creatures'].iteritems():
_b[name] = CreatureSheet(name, config, self.cfg['ui']['camera']['zoom_levels'])
return _b
if __name__ == '__main__':
def profile(function, *args, **kwargs):
""" Returns performance statistics (as a string) for the given function."""
def _run():
function(*args, **kwargs)
import cProfile as profile
import pstats
sys.modules['__main__'].__profile_run__ = _run
identifier = function.__name__ + '()'
profile.run('__profile_run__()', identifier)
p = pstats.Stats(identifier)
p.stream = open(identifier, 'w')
p.sort_stats('time').print_stats(50)
p.stream.close()
s = open(identifier).read()
os.remove(identifier)
return s
if DEBUG:
logging.basicConfig(level = logging.DEBUG)
if PROFILE:
profile_result = profile(Launcher().run)
print(profile_result)
else:
Launcher().run()
from expMethod import expMethod
from expResult import expResult
import numpy as np
from scipy import interp
import decimal
import pylab as pl
from pylab import *
import random
from sklearn.metrics import roc_curve, auc
import sys
import pickle
import os,sys
import time
dataset = expDataset("", "")
#dataset.prefix_path = '../data/link_data'
#dataset.dataset_list = ['foursquare', 'twitter']
setting = expSetting()
method = expMethod()
result = expResult()
pro = profile(dataset, setting, method, result)
print "All Start"
start = time.clock()
pro.run_baseline()
elapsed = (time.clock() - start)
print("Time used:", elapsed)
print "All Finish"
except ImportError:
import profile
self.profile = profile.Profile()
def __enter__(self):
self.profile.enable()
def __exit__(self, *a):
self.profile.disable()
self.profile.create_stats()
import pstats
stats = pstats.Stats(self.profile)
stats.sort_stats('cumulative')
stats.print_stats(.05)
def profile():
from calibre.ptempfile import TemporaryDirectory
path = sys.argv[-1]
with TemporaryDirectory() as tdir, Profiler():
return render(path,
tdir,
serialize_metadata=True,
extract_annotations=True,
virtualize_resources=False,
max_workers=1)
if __name__ == '__main__':
profile()
def update_windowS(pathIn='', #raw frame保存地址
start_frameW='',#视频分析窗口 起始帧
end_frameW='', #视频分析窗口 结束帧
segment_time='', #视频段的时间
knob_values='', #全部的knob值 / k个promising的configration包含的knob值
k='', #k个promising值 / 1个（promising中选出一个最佳的作为某个segment的configration）
fps='', #输入视频流的帧率
profile_time=None, #profile的时间（1s）
golden_configration=None, #全分析时为golden configration。
cost=None, #由offline one-time生成的全部configration的cost值
ground_configration=None, #k个中选一个最佳为次优的ground truth？
cover_thre=None, #object覆盖度阈值
f1_thre=None, #根据每帧分析的f1值，来确定该帧是否为准确帧
pipe=None, #输出视频流的pipe
analyseConfigration=None,
lock=None
):
#leader_pathIn=pathIn[0] #多个视频
#leader 的raw video本地保存路径
leader_pathIn=pathIn
#profile 部分的起始帧和结束帧
start_frameP=start_frameW
end_frameP=start_frameW+profile_time*fps
if end_frameP>end_frameW:
end_frameP=end_frameW
#获取一个window的top k个最佳configration
configrationW=profile(leader_pathIn,start_frameP,end_frameP,knob_values,k,
golden_configration,cost,fps,cover_thre,f1_thre) #leader topK
#leader profile window中每个segment的configration
isLeader=1
#若输入视频流读取完毕，更新总帧数（更新视频的window结束帧）
global frameCount
if frameCount!=0 and end_frameW>frameCount:
end_frameW=frameCount
#获取window中每个segment的最佳（1个）configration
#过渡：将不返回configration
leader_configration=update_windowT(leader_pathIn,start_frameW,end_frameW,segment_time,knob_values,k,fps,profile_time,ground_configration,configrationW,isLeader,cost,analyseConfigration,cover_thre,f1_thre,pipe,lock)
result_configration=[]
result_configration.append(leader_configration)
##
i=1
isLeader=0
#多个视频时需要获取followers的configration
#while i<len(pathIn):
#if start_frameW<total_frame[i]:
# if end_frameW>total_frame[i]:
#end_frameW=total_frame[i]
#follower_configration=update_windowT(pathIn[i],start_frameW,end_frameW,segment_time,knob_values,k,fps,profile_time,ground_configration,configrationW,isLeader,cost,cover_thre,f1_thre)
# result_configration.append(follower_configration)
# i=i+1
##
return result_configration
