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|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1a6a6d190573f01bbf7d17a030aaa51dbe22656f
|
51dcd31096526bfa6aeae4baea9f0f45657c6623
|
/ocean/tests/util.py
|
dba4670d5424620103eed74a400c139a2532af16
|
[] |
no_license
|
sopac/ocean-portal-docker
|
eba5de774e5a2b3e9b019440c39e7f0041715dd9
|
159aeba7143e66fdd9ed253de935407f898b4873
|
refs/heads/master
| 2021-01-20T08:07:58.698449
| 2017-09-10T09:24:04
| 2017-09-10T09:24:04
| 90,103,531
| 1
| 5
| null | 2017-12-13T03:30:45
| 2017-05-03T03:19:57
|
Python
|
UTF-8
|
Python
| false
| false
| 826
|
py
|
#
# (c) 2012 Commonwealth of Australia
# Australian Bureau of Meteorology, COSPPac COMP
# All Rights Reserved
#
# Authors: Danielle Madeley <d.madeley@bom.gov.au>
import os
import os.path
from glob import glob
import pytest
from ocean.config import get_server_config
config = get_server_config()
def clear_cache(product, filetype='*'):
cachedir = config['outputDir']
s = os.path.join(cachedir, '%s*.%s' % (product, filetype))
for d in glob(s):
try:
os.unlink(d)
except IOError:
raise
def unique(iterable):
__tracebackhide__ = True
vals = set()
for i in iterable:
if i in vals: return False
vals.add(i)
return True
def get_file_from_url(url):
bn = os.path.basename(url)
return os.path.join(config['outputDir'], bn)
|
[
"sachindras@spc.int"
] |
sachindras@spc.int
|
329c0354906ea7def69064595589467c698a674a
|
d2720ce687c6000b06255d51824770e0f91e04ca
|
/stepper.py
|
267c5e17ffb11e2af50b1bca497cfccc928eda5c
|
[] |
no_license
|
patildayananda/Raspberry-Pi
|
92eae96579b599b23640f2c9431a31fded3c7ed4
|
835ace7b9d6843ef8697e6b8b6efe7cf44f29282
|
refs/heads/master
| 2021-06-02T00:48:11.897537
| 2016-08-17T06:39:05
| 2016-08-17T06:39:05
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,646
|
py
|
import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
coil_A_1_pin = 24 # pink
coil_A_2_pin = 23 # orange
coil_B_1_pin = 4 # blue
coil_B_2_pin = 17 # yellow
# adjust if different
StepCount = 8
Seq = range(0, StepCount) # seq size is of 8
Seq[0] = [0,1,0,0]
Seq[1] = [0,1,0,1]
Seq[2] = [0,0,0,1] # store value for steps
Seq[3] = [1,0,0,1]
Seq[4] = [1,0,0,0]
Seq[5] = [1,0,1,0]
Seq[6] = [0,0,1,0]
Seq[7] = [0,1,1,0]
GPIO.setup(enable_pin, GPIO.OUT)
GPIO.setup(coil_A_1_pin, GPIO.OUT)
GPIO.setup(coil_A_2_pin, GPIO.OUT)
GPIO.setup(coil_B_1_pin, GPIO.OUT)
GPIO.setup(coil_B_2_pin, GPIO.OUT)
GPIO.output(enable_pin, 1)
def setStep(w1, w2, w3, w4):
GPIO.output(coil_A_1_pin, w1)
GPIO.output(coil_A_2_pin, w2)
GPIO.output(coil_B_1_pin, w3)
GPIO.output(coil_B_2_pin, w4)
def forward(delay, steps):
for i in range(steps):
for j in range(StepCount): # access the seq. list one by one(0-7)
setStep(Seq[j][0], Seq[j][1], Seq[j][2], Seq[j][3])
time.sleep(delay)
def backwards(delay, steps):
for i in range(steps):
for j in reversed(range(StepCount)): # access the seq. list one by one(7-0)
setStep(Seq[j][0], Seq[j][1], Seq[j][2], Seq[j][3])
time.sleep(delay)
if __name__ == '__main__':
while True:
delay = raw_input("Time Delay (ms)?")
steps = raw_input("How many steps forward? ")
forward(int(delay) / 1000.0, int(steps)) #function call for f/w
steps = raw_input("How many steps backwards? ")
backwards(int(delay) / 1000.0, int(steps)) #function call for b/w
|
[
"noreply@github.com"
] |
patildayananda.noreply@github.com
|
01673d7cfb58ab7724853b1300c74cb91d74ff39
|
392768f9038b6ed5752e3ce0a2fd1400da90d2e0
|
/14_List.py
|
9a3354e2e7c70b3c30d981a471af7a28a8c1a616
|
[] |
no_license
|
msbhosale/python_workshop
|
0816566ed3a37a5f6a26351f70291155b4122595
|
7403aacda74cf5c7199875067d6d0ce587017424
|
refs/heads/master
| 2020-05-03T21:30:38.944051
| 2019-04-03T07:13:52
| 2019-04-03T07:13:52
| 178,824,983
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 515
|
py
|
my_list = [15,"Jay",False,2.15,"KK"]
my_list[0] = 56
print(my_list)
# for item in my_list:
# print(item)
# my_list.append("Lunch")
# print(my_list)
# length_of_my_list = len(my_list)
# print(length_of_my_list)
# print(my_list[2:])
# for i in range(0,length_of_my_list):
# print(my_list[i])
# x = numbers[0]
# y = numbers[1]
x,y = numbers = [15,20]
print(f"X : {x}, Y : {y}")
# Swapping of numbers using unpacking
a = 15
b = 364
b, a = a , b
print(a,b)
|
[
"noreply@github.com"
] |
msbhosale.noreply@github.com
|
ec1e5dbc338ecf43d1bd53ded885b1450fb0c5be
|
da570c2047d335b3553e63c27ac7f60b57b28b7e
|
/images/urls.py
|
6c3df5aaf6b9ca607cd5fbcabe80ae605ee575b6
|
[
"MIT"
] |
permissive
|
mfannick/viewImages
|
8c799fc52566de03f4909d36f5ccc50e7fff9564
|
27e447faff455fba306ef3e677d5f2f63160065e
|
refs/heads/master
| 2021-09-09T11:53:42.786004
| 2019-10-14T09:21:16
| 2019-10-14T09:21:16
| 214,357,014
| 0
| 0
| null | 2021-09-08T01:21:15
| 2019-10-11T06:11:06
|
Python
|
UTF-8
|
Python
| false
| false
| 425
|
py
|
from django.conf.urls import url
from . import views
from django.conf import settings
from django.conf.urls.static import static
urlpatterns=[
url('^$' ,views.homePage,name='homePage'),
url(r'^search/', views.searchImageByCategory, name='searchImageByCategory'),
url(r'^description/(\d+)',views.imageDescription,name='imageDescription')
]
urlpatterns+=static(settings.MEDIA_URL,document_root=settings.MEDIA_ROOT)
|
[
"mfannick1@gmail.com"
] |
mfannick1@gmail.com
|
3c1e2609185afba2ced84ebd4fc0350d03478685
|
a0fe82f6134fa6f0423d95116ffb5c4a15f6a299
|
/Eduspace/student/views/student.py
|
fb79a9c91e56322d53d0a27a17ea7dff2f19beb9
|
[] |
no_license
|
akshaykrsinghal/demorepository
|
bdc8bc81b4944ba2effcafc8f108a335a27fce4b
|
b845150740a4e7127718e2265c5e55d60b1c11c6
|
refs/heads/master
| 2022-12-19T17:07:38.027458
| 2020-10-10T10:37:46
| 2020-10-10T10:37:46
| 302,876,650
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 349
|
py
|
from django.http import HttpResponseRedirect
from django.shortcuts import render, redirect
from ..models import *
def student(request):
a=request.session['rollno']
# image=user.objects.filter(rollno=a)
image=user.objects.filter(rollno=a)
data={'images':image}
print(image)
return render(request,'dashboard.html',data)
|
[
"59149089+Akshaykumarsinghal@users.noreply.github.com"
] |
59149089+Akshaykumarsinghal@users.noreply.github.com
|
d3059af279cb484debf3bea11242351e608798c6
|
cba86fc39209a9bb273ed9a8f1620068909578c1
|
/刘美宁/Python+Appium/test/app.py
|
3aa531b550b0e630a1cf82fc4e5102f78a71ca31
|
[] |
no_license
|
fengrao1/practice
|
c2303b7ca71e38f0029a251d2b9842384a856eb8
|
701f5d910ec39d6f575f219bf7c8f53f94b98c82
|
refs/heads/master
| 2022-11-06T05:34:13.782766
| 2020-06-07T02:25:51
| 2020-06-07T02:25:51
| 258,391,682
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 716
|
py
|
from appium import webdriver
from appium.webdriver.webdriver import WebDriver
from page.login_page import LoginPage
#初始化driver，关闭driver
class App():
driver:WebDriver=None
@classmethod
def start(cls):
cap = {"platformName": "Android",
"deviceName": "8KE5T19B11004244",
"appPackage": "com.example.lenovo.enjoyball",
"appActivity": "com.example.lenovo.Activity.LoginActivity",
"noReset": True
}
cls.driver = webdriver.Remote("http://127.0.0.1:4723/wd/hub", cap)
cls.driver.implicitly_wait(10)
return LoginPage(cls.driver)
@classmethod
def quit(cls):
cls.driver.quit()
|
[
"2996331661@qq.com"
] |
2996331661@qq.com
|
0c537c7a76a12d5ad4b319e5ecd8695d74b3b0f6
|
5c5458622ab8413fef8ab11ef5e09dcdcd42ff69
|
/1.py
|
ad47b2fba1e02ef70d242917fbf7c8954a6efe8d
|
[] |
no_license
|
zhenyakeg/Console
|
127fbbfe33cf86a0e4d5eb968c783407168364f5
|
31eea7a22a95701049872d4da2c01307f05e920d
|
refs/heads/master
| 2021-01-13T10:06:17.797796
| 2016-10-27T17:59:03
| 2016-10-27T17:59:03
| 72,119,199
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 218
|
py
|
__author__ = 'student'
# импортируем модуль
import sys
# выводим на экран список всех аргументов
s=0
for arg in sys.argv:
if len(arg) == 3:
s+=1
print (s)
|
[
"egor.rozinskiy@mail.ru"
] |
egor.rozinskiy@mail.ru
|
54bb0c609bfe5631ed4693791271a60989565bef
|
e918334824eb32c1c8b365a2821c6676eb66b25c
|
/manhattan_graph.py
|
e02881545614b0f22edbcffbef9fcd987efcfded
|
[] |
no_license
|
brianramaswami/SearchingAlgorithms
|
b4fb32f9f84d0866c6ab89a96d1785921821b3ab
|
5bb95ce31ac8d5602a6abc2df472858c2a6610ed
|
refs/heads/master
| 2022-01-30T06:34:07.861678
| 2019-07-20T22:48:18
| 2019-07-20T22:48:18
| 197,987,239
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 7,668
|
py
|
class graph_vertex:
def __init__(self, name, x, y):
self.name = name
self.position = (x, y)
def __lt__(self, other):
return self.name < other.name
thirty_third_and_madison = graph_vertex("33rd Street and Madison Avenue", 33, 4)
thirty_third_and_fifth = graph_vertex("33rd Street and 5th Avenue", 33, 5)
manhattan_mall = graph_vertex("Manhattan Mall", 33, 6)
penn_station = graph_vertex('Penn Station', 33, 7)
thirty_fourth_and_madison = graph_vertex("34th Street and Madison Avenue", 34, 4)
empire_state_building = graph_vertex('Empire State Building', 34, 5)
herald_square = graph_vertex('Herald Square', 34, 6)
thirty_fourth_and_seventh = graph_vertex("34th Street and 7th Avenue", 34, 7)
thirty_fifth_and_madison = graph_vertex("35th Street and Madison Avenue", 35, 4)
cuny_grad_center = graph_vertex("CUNY Graduate Center", 35, 5)
thirty_fifth_and_sixth = graph_vertex("35th Street and 6th Avenue", 35, 6)
macys = graph_vertex("Macy's", 35, 7)
thirty_sixth_and_madison = graph_vertex("36th Street and Madison Avenue", 36, 4)
thirty_sixth_and_fifth = graph_vertex("36th Street and 5th Avenue", 36, 5)
thirty_sixth_and_sixth = graph_vertex("36th Street and 6th Avenue", 36, 6)
thirty_sixth_and_seventh = graph_vertex("36th Street and 7th Avenue", 36, 7)
morgan_library = graph_vertex("Morgan Library and Museum", 37, 4)
thirty_seventh_and_fifth = graph_vertex("37th Street and 5th Avenue", 37, 5)
thirty_seventh_and_sixth = graph_vertex("37th Street and 6th Avenue", 37, 6)
thirty_seventh_and_seventh = graph_vertex("37th Street and 7th Avenue", 37, 7)
thirty_eighth_and_madison = graph_vertex("38th Street and Madison Avenue", 38, 4)
thirty_eighth_and_fifth = graph_vertex("38th Street and Fifth Avenue", 38, 5)
thirty_eighth_and_sixth = graph_vertex("38th Street and Sixth Avenue", 38, 6)
thirty_eighth_and_seventh = graph_vertex("38th Street and Seventh Avenue", 38, 7)
mexican_consulate = graph_vertex("Mexican Consulate General", 39, 4)
thirty_ninth_and_fifth = graph_vertex("39th Street and Fifth Avenue", 39, 5)
thirty_ninth_and_sixth = graph_vertex("39th Street and Sixth Avenue", 39, 6)
thirty_ninth_and_seventh = graph_vertex("39th Street and Seventh Avenue", 39, 7)
fortieth_and_madison = graph_vertex("40th Street and Madison Avenue", 40, 4)
fortieth_and_fifth = graph_vertex("40th Street and Fifth Avenue", 40, 5)
bryant_park_south = graph_vertex("Bryant Park South", 40, 6)
times_square_south = graph_vertex("Times Square - South", 40, 7)
forty_first_and_madison = graph_vertex("41st Street and Madison Avenue", 41, 4)
mid_manhattan_library = graph_vertex("Mid-Manhattan Library", 41, 5)
kinokuniya = graph_vertex("Kinokuniya", 41, 6)
times_square = graph_vertex("Times Square", 41, 7)
grand_central_station = graph_vertex("Grand Central Station", 42, 4)
library = graph_vertex("New York Public Library", 42, 5)
bryant_park_north = graph_vertex("Bryant Park North", 42, 6)
times_square_north = graph_vertex("Times Square - North", 42, 7)
manhattan_graph = {
thirty_third_and_madison: set([(thirty_fourth_and_madison, 1), (thirty_third_and_fifth, 3)]),
thirty_third_and_fifth: set([(thirty_third_and_madison, 3), (manhattan_mall, 3), (empire_state_building, 1)]),
manhattan_mall: set([(thirty_third_and_fifth, 3), (penn_station, 3), (herald_square, 1)]),
penn_station: set([(manhattan_mall, 3), (thirty_fourth_and_seventh, 1)]),
thirty_fourth_and_madison: set([(thirty_third_and_madison, 1), (empire_state_building, 3), (thirty_fifth_and_madison, 1)]),
empire_state_building: set([(thirty_fourth_and_madison, 3), (herald_square, 3), (thirty_third_and_fifth, 1), (cuny_grad_center, 1)]),
herald_square: set([(empire_state_building, 3), (thirty_fourth_and_seventh, 3), (manhattan_mall, 1), (thirty_fifth_and_sixth, 1)]),
thirty_fourth_and_seventh: set([(herald_square, 3), (macys, 1), (penn_station, 1)]),
thirty_fifth_and_madison: set([(thirty_fourth_and_madison, 1), (thirty_sixth_and_madison, 1), (cuny_grad_center, 3)]),
cuny_grad_center: set([(thirty_fifth_and_madison, 3), (thirty_fifth_and_sixth, 3), (empire_state_building, 1), (thirty_sixth_and_fifth, 1)]),
thirty_fifth_and_sixth: set([(cuny_grad_center, 3), (macys, 3), (herald_square, 1), (thirty_sixth_and_sixth, 1)]),
macys: set([(thirty_fifth_and_sixth, 3), (thirty_fourth_and_seventh, 1), (thirty_sixth_and_seventh, 1)]),
thirty_sixth_and_madison: set([(thirty_sixth_and_fifth, 3), (thirty_fifth_and_madison, 1), (morgan_library, 1)]),
thirty_sixth_and_fifth: set([(thirty_sixth_and_madison, 3), (thirty_sixth_and_sixth, 3), (cuny_grad_center, 1), (thirty_seventh_and_fifth, 1)]),
thirty_sixth_and_sixth: set([(thirty_sixth_and_fifth, 3), (thirty_sixth_and_seventh, 3), (thirty_fifth_and_sixth, 1), (thirty_seventh_and_sixth, 1)]),
thirty_sixth_and_seventh: set([(thirty_sixth_and_sixth, 3), (macys, 1), (thirty_seventh_and_seventh, 1)]),
morgan_library: set([(thirty_seventh_and_fifth, 3), (thirty_sixth_and_madison, 1), (thirty_eighth_and_madison, 1)]),
thirty_seventh_and_fifth: set([(morgan_library, 3), (thirty_seventh_and_sixth, 3), (thirty_sixth_and_fifth, 1), (thirty_eighth_and_fifth, 1)]),
thirty_seventh_and_sixth: set([(thirty_seventh_and_fifth, 3), (thirty_seventh_and_seventh, 3), (thirty_sixth_and_sixth, 1)]),
thirty_seventh_and_seventh: set([(thirty_seventh_and_sixth, 3), (thirty_sixth_and_seventh, 1), (thirty_eighth_and_seventh, 1)]),
thirty_eighth_and_madison: set([(thirty_eighth_and_fifth, 3), (morgan_library, 1), (mexican_consulate, 1)]),
thirty_eighth_and_fifth: set([(thirty_eighth_and_madison, 3), (thirty_eighth_and_sixth, 3), (thirty_seventh_and_fifth, 1), (thirty_ninth_and_fifth, 1)]),
thirty_eighth_and_sixth: set([(thirty_eighth_and_fifth, 3), (thirty_eighth_and_seventh, 3), (thirty_seventh_and_sixth, 1), (thirty_ninth_and_sixth, 1)]),
thirty_eighth_and_seventh: set([(thirty_eighth_and_sixth, 3), (thirty_seventh_and_seventh, 1), (thirty_ninth_and_seventh, 1)]),
mexican_consulate: set([(thirty_ninth_and_fifth, 3), (thirty_eighth_and_madison, 1), (fortieth_and_madison, 1)]),
thirty_ninth_and_fifth: set([(mexican_consulate, 3), (thirty_ninth_and_sixth, 3), (thirty_eighth_and_fifth, 1), (fortieth_and_fifth, 1)]),
thirty_ninth_and_sixth: set([(thirty_ninth_and_fifth, 3), (thirty_ninth_and_seventh, 3), (thirty_eighth_and_sixth, 1), (bryant_park_south, 1)]),
thirty_ninth_and_seventh: set([(thirty_ninth_and_sixth, 3), (thirty_eighth_and_seventh, 1), (times_square_south, 1)]),
fortieth_and_madison: set([(fortieth_and_fifth, 3), (mexican_consulate, 1), (forty_first_and_madison, 1)]),
fortieth_and_fifth: set([(fortieth_and_madison, 3), (bryant_park_south, 3), (thirty_ninth_and_fifth, 1)]),
bryant_park_south: set([(fortieth_and_fifth, 3), (times_square_south, 3), (thirty_ninth_and_sixth, 1), (kinokuniya, 1)]),
times_square_south: set([(bryant_park_south, 3), (times_square, 1), (thirty_ninth_and_seventh, 1)]),
forty_first_and_madison: set([(fortieth_and_madison, 1), (grand_central_station, 1), (mid_manhattan_library, 3)]),
mid_manhattan_library: set([(forty_first_and_madison, 3), (library, 1), (fortieth_and_fifth, 1)]),
kinokuniya: set([(times_square, 3), (bryant_park_north, 1), (bryant_park_south, 1)]),
times_square: set([(kinokuniya, 3), (times_square_north, 1), (times_square_south, 1)]),
grand_central_station: set([(library, 3), (forty_first_and_madison, 1)]),
library: set([(mid_manhattan_library, 1), (grand_central_station, 3), (bryant_park_north, 3)]),
bryant_park_north: set([(library, 3), (times_square_north, 3), (bryant_park_south, 1)]),
times_square_north: set([(times_square, 1), (bryant_park_north, 3)])
}
|
[
"brianramaswami@yahoo.com"
] |
brianramaswami@yahoo.com
|
0365a71e6ddcbf5d739bd768676f3f793715d525
|
1799fe1d9dfcf5f9619a87a11f3fa6170e1864fc
|
/00998/test_maximum_binary_tree_ii.py
|
44cc467d9b38a539320c803e7bc639b674e44c3e
|
[] |
no_license
|
SinCatGit/leetcode
|
5e52b49324d16a96de1ba4804e3d17569377e804
|
399e40e15cd64781a3cea295bf29467d2284d2ae
|
refs/heads/master
| 2021-07-05T18:51:46.018138
| 2020-04-25T04:06:48
| 2020-04-25T04:06:48
| 234,226,791
| 1
| 1
| null | 2021-04-20T19:17:43
| 2020-01-16T03:27:08
|
Python
|
UTF-8
|
Python
| false
| false
| 1,519
|
py
|
import unittest
from maximum_binary_tree_ii import Solution, TreeNode
class TestSolution(unittest.TestCase):
def test_Calculate_Solution(self):
solution = Solution()
# 6
# / \
# 1 4
# / \
# 3 2
t25 = TreeNode(6)
t21 = TreeNode(1)
t24 = TreeNode(4)
t23 = TreeNode(3)
t26 = TreeNode(2)
t25.left = t21
t25.right = t24
t24.left = t23
t24.right = t26
def dfs(r):
if r.left:
yield from dfs(r.left)
yield r.val
if r.right:
yield from dfs(r.right)
root = solution.insertIntoMaxTree(t25, 7)
self.assertEqual([1, 6, 3, 4, 2, 7], [v for v in dfs(root)])
root = solution.insertIntoMaxTree(t25, 5)
self.assertEqual([1, 6, 3, 4, 2, 5], [v for v in dfs(root)])
# 6
# / \
# 1 4
# / \
# 3 2
t25 = TreeNode(6)
t21 = TreeNode(1)
t24 = TreeNode(4)
t23 = TreeNode(3)
t26 = TreeNode(2)
t25.left = t21
t25.right = t24
t24.left = t23
t24.right = t26
root = solution.insertIntoMaxTreeV01(t25, 7)
self.assertEqual([1, 6, 3, 4, 2, 7], [v for v in dfs(root)])
root = solution.insertIntoMaxTreeV01(t25, 5)
self.assertEqual([1, 6, 3, 4, 2, 5], [v for v in dfs(root)])
if __name__ == '__main__':
unittest.main()
|
[
"sincat@126.com"
] |
sincat@126.com
|
78556512deea6fa868b272820fdf67d59eb5298e
|
c459c724af99b09b30253909898827fe9c2d79cd
|
/Advent2017/Day/Day_24.py
|
c746812a9748f60002d82994b147c63d792d3627
|
[] |
no_license
|
Rafq77/Advent2015
|
72f3e6cd598a057ed79c3a9d125898edff13182b
|
0acecb4982d46bdf63e4e35350e76da0a7196ce0
|
refs/heads/master
| 2021-01-10T16:07:57.911724
| 2019-09-10T18:36:05
| 2019-09-10T18:36:05
| 47,354,878
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,258
|
py
|
fd = open("""../Resources/Day_24.txt""", 'r')
src = fd.read()
fd.close()
lines = src.split('\n')
print("Length: " + str(len(lines)))
components = list()
for each in lines:
p1, p2 = each.split('/')
components.append((int(p1), int(p2)))
import itertools
import collections
components.sort()
#for c in components:
# print(c)
def rec(tupList):
#print(tupList)
last = tupList[-1]
candidates = list(filter(lambda x: x[0] == last[1] or x[1] == last[1], components))
for c in candidates:
if c not in tupList and c[::-1] not in tupList:
#if c not in tupList:
tmp = tupList.copy()
if c[1] == tmp[-1][1]: #rotate
tmp.append(c[::-1])
else:
tmp.append(c)
yield tmp
yield from rec(tmp)
return tupList
koth = 0
kothLen = 0
kothLenS = 0
for e in components:
if e[0] == 0:
l = list()
l.append(e)
for each in rec(l):
#print(each)
s = sum([sum(t) for t in each])
if s > koth:
koth = s
l = len(each)
if l > kothLen:
kothLen = l
kothLenS = s
|
[
"sokol-77@wp.pl"
] |
sokol-77@wp.pl
|
8c55b1b583c89eaaf63961ca00dde5c69b6b67c5
|
5e5799e0ccce7a72d514fbc76dcb0a2108013f18
|
/Textfile2DefDomGeom.py
|
710ab37655fe1cd3158b6347c04304f6a2e29644
|
[] |
no_license
|
sourcery-ai-bot/dash
|
6d68937d225473d06a18ef64079a4b3717b5c12c
|
e1d1c3a601cd397d2508bfd4bb12bdb4e878cd9a
|
refs/heads/master
| 2023-03-07T17:15:39.174964
| 2011-03-01T17:11:21
| 2011-03-01T17:11:21
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,140
|
py
|
#!/usr/bin/env python
#
# Use doms.txt or nicknames.txt file to create a default-dom-geometry file and
# print the result to sys.stdout
#
# URL: http://icecube.wisc.edu/~testdaq/database_files/nicknames.txt
import sys
from DefaultDomGeometry import DefaultDomGeometryReader, DomsTxtReader, \
NicknameReader
if __name__ == "__main__":
if len(sys.argv) < 2:
raise SystemExit("Please specify a file to load!")
if len(sys.argv) > 2:
raise SystemExit("Too many command-line arguments!")
if sys.argv[1].endswith("nicknames.txt"):
newGeom = NicknameReader.parse(sys.argv[1])
elif sys.argv[1].endswith("doms.txt"):
newGeom = DomsTxtReader.parse(sys.argv[1])
else:
raise SystemExit("File must be 'nicknames.txt' or 'doms.txt'," +
" not '%s'" % sys.argv[1])
oldDomGeom = DefaultDomGeometryReader.parse()
# rewrite the 64-DOM strings to 60 DOM strings plus 32 DOM icetop hubs
newGeom.rewrite(False)
oldDomGeom.rewrite()
oldDomGeom.mergeMissing(newGeom)
# dump the new default-dom-geometry data to sys.stdout
oldDomGeom.dump()
|
[
"dglo@icecube.wisc.edu"
] |
dglo@icecube.wisc.edu
|
546d674261f3df935f47d76c22d816e02e5c5599
|
4e0ee2b68398a90b0986975f645350033a624558
|
/tests/onnx_resnet18/test_onnx_resnet18_int8.py
|
5c23ade3f33cd92e177415de06a1d717c36ea894
|
[
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] |
permissive
|
kindsenior/nngen
|
697b80b32cf2b33e7f2c64e4d1a27eb2d739b30c
|
301b19b35e50174d8abb1a757b061ae80cdfe612
|
refs/heads/master
| 2022-09-21T05:53:34.565461
| 2020-05-03T14:58:19
| 2020-05-03T14:58:19
| 269,007,213
| 0
| 0
|
Apache-2.0
| 2020-06-03T06:26:43
| 2020-06-03T06:26:42
| null |
UTF-8
|
Python
| false
| false
| 2,129
|
py
|
from __future__ import absolute_import
from __future__ import print_function
import os
import sys
# the next line can be removed after installation
sys.path.insert(0, os.path.dirname(os.path.dirname(
os.path.dirname(os.path.abspath(__file__)))))
import nngen as ng
import veriloggen
import onnx_resnet18
act_dtype = ng.int8
weight_dtype = ng.int8
bias_dtype = ng.int16
scale_dtype = ng.int16
with_batchnorm = True
disable_fusion = False
conv2d_par_ich = 1
conv2d_par_och = 1
conv2d_par_col = 1
conv2d_par_row = 1
conv2d_concur_och = None
conv2d_stationary = 'filter'
pool_par = 1
elem_par = 1
chunk_size = 64
axi_datawidth = 32
def test(request, silent=True):
veriloggen.reset()
simtype = request.config.getoption('--sim')
rslt = onnx_resnet18.run(act_dtype, weight_dtype,
bias_dtype, scale_dtype,
with_batchnorm, disable_fusion,
conv2d_par_ich, conv2d_par_och, conv2d_par_col, conv2d_par_row,
conv2d_concur_och, conv2d_stationary,
pool_par, elem_par,
chunk_size,
axi_datawidth, silent,
filename=None, simtype=simtype,
outputfile=os.path.splitext(os.path.basename(__file__))[0] + '.out')
verify_rslt = rslt.splitlines()[-1]
assert(verify_rslt == '# verify: PASSED')
if __name__ == '__main__':
rslt = onnx_resnet18.run(act_dtype, weight_dtype,
bias_dtype, scale_dtype,
with_batchnorm, disable_fusion,
conv2d_par_ich, conv2d_par_och, conv2d_par_col, conv2d_par_row,
conv2d_concur_och, conv2d_stationary,
pool_par, elem_par,
chunk_size,
axi_datawidth, silent=False,
filename='tmp.v',
outputfile=os.path.splitext(os.path.basename(__file__))[0] + '.out')
print(rslt)
|
[
"shta.ky1018@gmail.com"
] |
shta.ky1018@gmail.com
|
82bb97b65913316755124594969ad638d47401ba
|
657a0e7550540657f97ac3f7563054eb4da93651
|
/Boilermake2018/Lib/site-packages/chatterbot/logic/low_confidence.py
|
bb8ebfd230f6cde219dcb021a1575d6b17714cb8
|
[
"LicenseRef-scancode-unknown-license-reference",
"CC0-1.0"
] |
permissive
|
TejPatel98/voice_your_professional_email
|
faf4d2c104e12be61184638913ebe298893c5b37
|
9cc48f7bcd6576a6962711755e5d5d485832128c
|
refs/heads/master
| 2022-10-15T03:48:27.767445
| 2019-04-03T16:56:55
| 2019-04-03T16:56:55
| 179,291,180
| 0
| 1
|
CC0-1.0
| 2022-10-09T13:00:52
| 2019-04-03T13:01:50
|
Python
|
UTF-8
|
Python
| false
| false
| 1,930
|
py
|
from __future__ import unicode_literals
from chatterbot.conversation import Statement
from .best_match import BestMatch
class LowConfidenceAdapter(BestMatch):
"""
Returns a default response with a high confidence
when a high confidence response is not known.
:kwargs:
* *threshold* (``float``) --
The low confidence value that triggers this adapter.
Defaults to 0.65.
* *default_response* (``str``) or (``iterable``)--
The response returned by this logic adaper.
* *response_selection_method* (``str``) or (``callable``)
The a response selection method.
Defaults to ``get_first_response``.
"""
def __init__(self, **kwargs):
super(LowConfidenceAdapter, self).__init__(**kwargs)
self.confidence_threshold = kwargs.get('threshold', 0.65)
default_responses = kwargs.get(
'default_response', "I'm sorry, I do not understand."
)
# Convert a single string into a list
if isinstance(default_responses, str):
default_responses = [
default_responses
]
self.default_responses = [
Statement(text=default) for default in default_responses
]
def process(self, input_statement):
"""
Return a default response with a high confidence if
a high confidence response is not known.
"""
# Select the closest match to the input statement
closest_match = self.get(input_statement)
# Choose a response from the list of options
response = self.select_response(input_statement, self.default_responses)
# Confidence should be high only if it is less than the threshold
if closest_match.confidence < self.confidence_threshold:
response.confidence = 1
else:
response.confidence = 0
return response
|
[
"tpa244@uky.edu"
] |
tpa244@uky.edu
|
2395d2b12aae09a4d84ec5301df48e4ee082a499
|
c33e0ec5662dad35fae8e7f1c3638c728c6a626c
|
/diseno_naiandy.py
|
3bc3941b24c138dd26603fc26443b45b2b4ebff4
|
[] |
no_license
|
Ivanjarv/NaiandyC
|
516445c5a860bfe8634ab6d6115a8eae3592e8d2
|
3fcfee7b7a51c5eac94d3f26bae6293ecd2ca340
|
refs/heads/main
| 2023-01-09T07:08:08.244458
| 2020-11-08T21:18:46
| 2020-11-08T21:18:46
| 311,152,796
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 26,797
|
py
|
#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
#
# generated by wxGlade 1.0.0a8 on Sat Sep 26 14:14:55 2020
#
import wx
class Entry(wx.Panel):
def __init__(self, *args, **kwds):
kwds["style"] = kwds.get("style", 0) | wx.TAB_TRAVERSAL
wx.Panel.__init__(self, *args, **kwds)
self.SetBackgroundColour(wx.Colour(255, 255, 255))
self.SetPos(True)
sizer_1 = wx.BoxSizer(wx.HORIZONTAL)
self.btm_img = wx.BitmapButton(self, wx.ID_ANY, wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/DATAnext.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_img.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_img.SetSize(self.btm_img.GetBestSize())
sizer_1.Add(self.btm_img, 0, 0, 0)
self.text = wx.TextCtrl(self, wx.ID_ANY, "", style=wx.BORDER_NONE)
self.text.SetMinSize((101, 18))
sizer_1.Add(self.text, 1, wx.EXPAND, 0)
self.SetSizer(sizer_1)
sizer_1.Fit(self)
self.Layout()
self.Bind(wx.EVT_KILL_FOCUS, self.onkillfocus, self.text)
self.Bind(wx.EVT_SET_FOCUS, self.onsetfocus, self.text)
def onkillfocus(self, event):
print("Event handler 'onkillfocus' not implemented!")
event.Skip()
def onsetfocus(self, event):
print("Event handler 'onsetfocus' not implemented!")
event.Skip()
class BaseNainady(wx.Frame):
def __init__(self, *args, **kwds):
kwds["style"] = kwds.get("style", 0) | wx.BORDER_SIMPLE | wx.FRAME_FLOAT_ON_PARENT | wx.RESIZE_BORDER
wx.Frame.__init__(self, *args, **kwds)
self.SetSize((700, 396))
self.szprincipal = wx.BoxSizer(wx.VERTICAL)
self.panelsup = wx.Panel(self, wx.ID_ANY)
self.panelsup.SetBackgroundColour(wx.Colour(255, 255, 255))
self.szprincipal.Add(self.panelsup, 0, wx.EXPAND, 0)
sizer_1 = wx.BoxSizer(wx.HORIZONTAL)
self.szpu = wx.BoxSizer(wx.HORIZONTAL)
sizer_1.Add(self.szpu, 1, wx.BOTTOM | wx.EXPAND | wx.TOP, 3)
self.btm_firth = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\DATAfirst.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_firth.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_firth.SetSize(self.btm_firth.GetBestSize())
self.szpu.Add(self.btm_firth, 0, wx.ALL, 3)
self.btm_previous = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\DATAprevious.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_previous.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_previous.SetSize(self.btm_previous.GetBestSize())
self.szpu.Add(self.btm_previous, 0, wx.ALL, 3)
self.btm_next = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\DATAnext.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_next.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_next.SetSize(self.btm_next.GetBestSize())
self.szpu.Add(self.btm_next, 0, wx.ALL, 3)
self.btm_last = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\DATAlast.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_last.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_last.SetSize(self.btm_last.GetBestSize())
self.szpu.Add(self.btm_last, 0, wx.ALL, 3)
self.btm_print = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\impresora.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_print.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_print.SetSize(self.btm_print.GetBestSize())
self.szpu.Add(self.btm_print, 0, wx.ALL, 3)
self.btm_save = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\pendrive.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_save.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_save.SetSize(self.btm_save.GetBestSize())
self.szpu.Add(self.btm_save, 0, wx.ALL, 3)
sizer_3 = wx.BoxSizer(wx.HORIZONTAL)
sizer_1.Add(sizer_3, 0, wx.BOTTOM | wx.EXPAND | wx.TOP, 3)
self.btm_minimizar = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:\\Users\\Dell\\Documents\\python\\Nainady App\\imagenes\\minimizar.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_minimizar.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_minimizar.SetSize(self.btm_minimizar.GetBestSize())
sizer_3.Add(self.btm_minimizar, 0, wx.ALL, 3)
self.btm_maximizar = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/cubo.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_maximizar.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_maximizar.SetSize(self.btm_maximizar.GetBestSize())
sizer_3.Add(self.btm_maximizar, 0, wx.ALL, 3)
self.btm_close = wx.BitmapButton(self.panelsup, wx.ID_ANY, wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/cerrar.png", wx.BITMAP_TYPE_ANY), style=wx.BORDER_NONE | wx.BU_AUTODRAW | wx.BU_EXACTFIT | wx.BU_NOTEXT)
self.btm_close.SetBackgroundColour(wx.Colour(255, 255, 255))
self.btm_close.SetSize(self.btm_close.GetBestSize())
sizer_3.Add(self.btm_close, 0, wx.ALL, 3)
self.szprincipal.Add((0, 0), 0, 0, 0)
self.panelsup.SetSizer(sizer_1)
self.SetSizer(self.szprincipal)
self.Layout()
self.Centre()
self.Bind(wx.EVT_LEFT_DOWN, self.onleftdown, self.panelsup)
self.Bind(wx.EVT_LEFT_UP, self.onleftup, self.panelsup)
self.Bind(wx.EVT_MOTION, self.onmousemove, self.panelsup)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenter, self.btm_firth)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavve, self.btm_firth)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenter, self.btm_previous)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavve, self.btm_previous)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenter, self.btm_next)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavve, self.btm_next)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenter, self.btm_last)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavve, self.btm_last)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenter, self.btm_print)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavve, self.btm_print)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenter, self.btm_save)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavve, self.btm_save)
self.Bind(wx.EVT_BUTTON, self.minimizar, self.btm_minimizar)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenterright, self.btm_minimizar)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavveright, self.btm_minimizar)
self.Bind(wx.EVT_BUTTON, self.maximizar, self.btm_maximizar)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenterright, self.btm_maximizar)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavveright, self.btm_maximizar)
self.Bind(wx.EVT_BUTTON, self.close, self.btm_close)
self.Bind(wx.EVT_ENTER_WINDOW, self.btnonenterright, self.btm_close)
self.Bind(wx.EVT_LEAVE_WINDOW, self.btnleavveright, self.btm_close)
def onleftdown(self, event):
print("Event handler 'onleftdown' not implemented!")
event.Skip()
def onleftup(self, event):
print("Event handler 'onleftup' not implemented!")
event.Skip()
def onmousemove(self, event):
print("Event handler 'onmousemove' not implemented!")
event.Skip()
def btnonenter(self, event):
print("Event handler 'btnonenter' not implemented!")
event.Skip()
def btnleavve(self, event):
print("Event handler 'btnleavve' not implemented!")
event.Skip()
def minimizar(self, event):
print("Event handler 'minimizar' not implemented!")
event.Skip()
def btnonenterright(self, event):
print("Event handler 'btnonenterright' not implemented!")
event.Skip()
def btnleavveright(self, event):
print("Event handler 'btnleavveright' not implemented!")
event.Skip()
def maximizar(self, event):
print("Event handler 'maximizar' not implemented!")
event.Skip()
def close(self, event):
print("Event handler 'close' not implemented!")
event.Skip()
class MainWindows(wx.Frame):
def __init__(self, *args, **kwds):
kwds["style"] = kwds.get("style", 0) | wx.DEFAULT_FRAME_STYLE
wx.Frame.__init__(self, *args, **kwds)
self.SetSize((800, 600))
self.SetTitle("Naiandy")
# Menu Bar
self.menubar = wx.MenuBar()
wxglade_tmp_menu = wx.Menu()
self.menubar.mregisto = wxglade_tmp_menu.Append(wx.ID_ANY, "&Registro\tCTRL-R", "Entreda de Diario")
self.Bind(wx.EVT_MENU, self.onregistro, self.menubar.mregisto)
self.menubar.mcxc = wxglade_tmp_menu.Append(wx.ID_ANY, "Cuenta por &Cobrar\tF1", "Factura a Cliente")
self.Bind(wx.EVT_MENU, self.cuentaporcobrar, self.menubar.mcxc)
self.menubar.mcxp = wxglade_tmp_menu.Append(wx.ID_ANY, "Cuenta por &Pagar\tF3", "Factura a Proveedor")
self.Bind(wx.EVT_MENU, self.cuentaporpagar, self.menubar.mcxp)
self.menubar.mrecibodemercancia = wxglade_tmp_menu.Append(wx.ID_ANY, "Recibo de &Mercancia\tCTRL-M", "Registro de Mercancia Recibida")
self.Bind(wx.EVT_MENU, self.recibodemercancia, self.menubar.mrecibodemercancia)
self.menubar.mcatalogodeuenta = wxglade_tmp_menu.Append(wx.ID_ANY, "C&atalogo de Cuenta\tCTRL-L", "Catalogo de Cuenta")
self.Bind(wx.EVT_MENU, self.catalogodecuenta, self.menubar.mcatalogodeuenta)
self.menubar.mcuenta = wxglade_tmp_menu.Append(wx.ID_ANY, "C&uenta\tCTRL-U", "Create Cueta")
self.Bind(wx.EVT_MENU, self.cuenta, self.menubar.mcuenta)
wxglade_tmp_menu.AppendSeparator()
self.menubar.mbloquearapp = wxglade_tmp_menu.Append(wx.ID_ANY, "&Bloquear App\tCTRL-B", u"Bloque la Aplicación")
self.Bind(wx.EVT_MENU, self.bloquearapp, self.menubar.mbloquearapp)
self.menubar.mquit = wxglade_tmp_menu.Append(wx.ID_ANY, "&Quit\tCTRL-Q", u"Cierra la Applicación")
self.Bind(wx.EVT_MENU, self.onquit, self.menubar.mquit)
self.menubar.Append(wxglade_tmp_menu, "&Regitro")
wxglade_tmp_menu = wx.Menu()
wxglade_tmp_menu_sub = wx.Menu()
self.menubar.mingreso = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Ingeso Por...\tF2", "Recibo de Ingreso")
self.Bind(wx.EVT_MENU, self.ingesopor, self.menubar.mingreso)
self.menubar.mpagode = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Pago de...\tF4", "Pagos")
self.Bind(wx.EVT_MENU, self.pagode, self.menubar.mpagode)
wxglade_tmp_menu_sub.AppendSeparator()
self.menubar.mconciliaciones = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Conciliaciones\tF5", "")
self.Bind(wx.EVT_MENU, self.conciliaciones, self.menubar.mconciliaciones)
wxglade_tmp_menu.Append(wx.ID_ANY, "&Banco", wxglade_tmp_menu_sub, "")
item = wxglade_tmp_menu.Append(wx.ID_ANY, "Balanza de &Comprobacion", u"Balanza de Comprobaciòn")
self.Bind(wx.EVT_MENU, self.balanza_de_comprobacion, item)
wxglade_tmp_menu.AppendSeparator()
wxglade_tmp_menu_sub = wx.Menu()
self.menubar.balance_general = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Balance General", "Genera el Balance General")
self.Bind(wx.EVT_MENU, self.balance_general, self.menubar.balance_general)
self.menubar.estado_de_resultado = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Estado de Resultado", "Genera el Estado de Resultado")
self.Bind(wx.EVT_MENU, self.estado_de_resultado, self.menubar.estado_de_resultado)
self.menubar.flujo_de_efectivo = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Flujo de Esfectivo", "Geenera el Estado de Flujo de Esfectivo")
self.Bind(wx.EVT_MENU, self.flujo_de_efectivo, self.menubar.flujo_de_efectivo)
wxglade_tmp_menu_sub_sub = wx.Menu()
self.menubar.estado_de_capital = wxglade_tmp_menu_sub_sub.Append(wx.ID_ANY, "Estado de &Capita", "Genera el Estado de Capital")
self.Bind(wx.EVT_MENU, self.Estado_de_capital, self.menubar.estado_de_capital)
wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Otros Estado", wxglade_tmp_menu_sub_sub, "")
wxglade_tmp_menu.Append(wx.ID_ANY, "&Estado Finacieros", wxglade_tmp_menu_sub, "")
self.menubar.Append(wxglade_tmp_menu, "&Finanza")
wxglade_tmp_menu = wx.Menu()
self.menubar.mhabilitar = wxglade_tmp_menu.Append(wx.ID_ANY, "&Desabilitar Barrra de Herramienta\tCTRL-H", "Habilita o Desabilitar la Barra de Herramienta", wx.ITEM_CHECK)
self.Bind(wx.EVT_MENU, self.habilitar, self.menubar.mhabilitar)
self.menubar.Append(wxglade_tmp_menu, "&Habilitar")
wxglade_tmp_menu = wx.Menu()
self.menubar.itbis_en_compra = wxglade_tmp_menu.Append(wx.ID_ANY, "ITBIS en &Compra 606", "General el formulario 606")
self.Bind(wx.EVT_MENU, self.itbis_en_compra, self.menubar.itbis_en_compra)
self.menubar.itbis_en_venta = wxglade_tmp_menu.Append(wx.ID_ANY, "ITBIS en &Venta 607", "General el formulario 607")
self.Bind(wx.EVT_MENU, self.itbis_en_venta, self.menubar.itbis_en_venta)
self.menubar.Formulario_de_NCF_Nulo = wxglade_tmp_menu.Append(wx.ID_ANY, "&Formulario de NCF Nulo 608", "Genera el formulario 608")
self.Bind(wx.EVT_MENU, self.Formulario_de_NCF_Nulo, self.menubar.Formulario_de_NCF_Nulo)
self.menubar.itbis_en_aduana = wxglade_tmp_menu.Append(wx.ID_ANY, "ITBIS en &Aduana 609", "Genera elFormulario 609")
self.Bind(wx.EVT_MENU, self.itbis_en_aduana, self.menubar.itbis_en_aduana)
wxglade_tmp_menu.AppendSeparator()
self.menubar.ir_dicisiete = wxglade_tmp_menu.Append(wx.ID_ANY, "IR-17", "Genera el formulario de IR-17")
self.Bind(wx.EVT_MENU, self.ir_dicisiete, self.menubar.ir_dicisiete)
self.menubar.ir_tres = wxglade_tmp_menu.Append(wx.ID_ANY, "IR-3", "Genera el Formulario IR-3")
self.Bind(wx.EVT_MENU, self.ir_tres, self.menubar.ir_tres)
self.menubar.Append(wxglade_tmp_menu, "&Impueto")
wxglade_tmp_menu = wx.Menu()
self.menubar.mcrearusuario = wxglade_tmp_menu.Append(wx.ID_ANY, "Cear &Usuario\tF10", "Crea un Nuevo Usuario")
self.Bind(wx.EVT_MENU, self.crearusuario, self.menubar.mcrearusuario)
self.menubar.mcxcempleado = wxglade_tmp_menu.Append(wx.ID_ANY, "&CXC EMPLEADO\tCTRL-C", "Crear Cuenta por Cobrar a Empleado")
self.Bind(wx.EVT_MENU, self.oncxcempleado, self.menubar.mcxcempleado)
self.menubar.mdescuento = wxglade_tmp_menu.Append(wx.ID_ANY, "&Decuento a Empleado\tCTRL-D", "Descueto a Empleado")
self.Bind(wx.EVT_MENU, self.ondescuentoaempleado, self.menubar.mdescuento)
wxglade_tmp_menu.AppendSeparator()
wxglade_tmp_menu_sub = wx.Menu()
self.menubar.magnadirempleado = wxglade_tmp_menu_sub.Append(wx.ID_ANY, u"&Añadir Empleado\tF6", "Regitrar en empleado ")
self.Bind(wx.EVT_MENU, self.agnadirempleado, self.menubar.magnadirempleado)
self.menubar.magnadirnomina = wxglade_tmp_menu_sub.Append(wx.ID_ANY, u"Añadir &Nomina\tF7", u"Añade Nomina")
self.Bind(wx.EVT_MENU, self.agnomina, self.menubar.magnadirnomina)
self.menubar.mimpuestonomina = wxglade_tmp_menu_sub.Append(wx.ID_ANY, "&Impuesto Nominales\tF8", "Configura los Impuestos Nominales")
self.Bind(wx.EVT_MENU, self.impuestonomina, self.menubar.mimpuestonomina)
wxglade_tmp_menu.Append(wx.ID_ANY, "&Nomina", wxglade_tmp_menu_sub, "")
self.menubar.Append(wxglade_tmp_menu, "&Gestion")
wxglade_tmp_menu = wx.Menu()
self.menubar.mconfiguraciones = wxglade_tmp_menu.Append(wx.ID_ANY, "&Configuraciones Generales\tF12", "Configuraciones de la Aplicacion")
self.Bind(wx.EVT_MENU, self.configuraciones, self.menubar.mconfiguraciones)
self.menubar.Append(wxglade_tmp_menu, "&Configuraciones")
self.macerca = wx.Menu()
self.menubar.Append(self.macerca, "&Acerca...")
self.SetMenuBar(self.menubar)
# Menu Bar end
self.statusbar = self.CreateStatusBar(1)
self.statusbar.SetStatusWidths([-1])
# Tool Bar
self.toolbar = wx.ToolBar(self, -1)
tool = self.toolbar.AddTool(wx.ID_ANY, "Registro", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/notebook.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Entrada de Diario", "Abre el formulario para hacer una entada en el Libro Diario")
self.Bind(wx.EVT_TOOL, self.onregistro, id=tool.GetId())
tool = self.toolbar.AddTool(wx.ID_ANY, "cxc", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/facturacion.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Cuenta por Cobrar", "Abrir formulario de Cuenta por Cobrar")
self.Bind(wx.EVT_TOOL, self.cuentaporcobrar, id=tool.GetId())
tool = self.toolbar.AddTool(wx.ID_ANY, "ingreso", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/business-color_money-bag_icon-icons.com_53447.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Recibo de Ingreso", "Abril formulario de Recibo de Ingreso")
self.Bind(wx.EVT_TOOL, self.resivodeingreso, id=tool.GetId())
tool = self.toolbar.AddTool(wx.ID_ANY, "cxp", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/receipt_106581.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Cuenta por Pagar", "Abrir formulario de Cuenta por Pagar")
self.Bind(wx.EVT_TOOL, self.cuentaporpagar, id=tool.GetId())
tool = self.toolbar.AddTool(wx.ID_ANY, "pago", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/pay_cash_payment_money_dollar_bill_icon_143267.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Hacer Pagos", "Abril formulario de Pago a Proveedores")
self.Bind(wx.EVT_TOOL, self.pagos, id=tool.GetId())
tool = self.toolbar.AddTool(wx.ID_ANY, "mercancia", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/task_calendar_timeline_plan_start_date_due_date_icon_142241.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Mercancia Recibida", "Abril formulario de Mercacia Recibida")
self.Bind(wx.EVT_TOOL, self.mercanciaresibida, id=tool.GetId())
self.toolbar.AddSeparator()
tool = self.toolbar.AddTool(wx.ID_ANY, "cuenta", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/expediente.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Crea una Cuenta", "Crea una Nueva Cuenta")
self.Bind(wx.EVT_TOOL, self.cuenta, id=tool.GetId())
self.toolbar.AddSeparator()
tool = self.toolbar.AddTool(wx.ID_ANY, "Bloquear", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/escudo.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, u"Bloque la Aplicación", u"Bloque la aplicación hasta que se introduzca la contraseña nuevamente")
self.Bind(wx.EVT_TOOL, self.bloquear, id=tool.GetId())
tool = self.toolbar.AddTool(wx.ID_ANY, "salir", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/Exit.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, u"Cerrar Aplicación", u"Cierre de la Aplicación")
self.Bind(wx.EVT_TOOL, self.close, id=tool.GetId())
self.SetToolBar(self.toolbar)
self.toolbar.Realize()
# Tool Bar end
self.Layout()
self.Centre()
def onregistro(self, event):
print("Event handler 'onregistro' not implemented!")
event.Skip()
def cuentaporcobrar(self, event):
print("Event handler 'cuentaporcobrar' not implemented!")
event.Skip()
def cuentaporpagar(self, event):
print("Event handler 'cuentaporpagar' not implemented!")
event.Skip()
def recibodemercancia(self, event):
print("Event handler 'recibodemercancia' not implemented!")
event.Skip()
def catalogodecuenta(self, event):
print("Event handler 'catalogodecuenta' not implemented!")
event.Skip()
def cuenta(self, event):
print("Event handler 'cuenta' not implemented!")
event.Skip()
def bloquearapp(self, event):
print("Event handler 'bloquearapp' not implemented!")
event.Skip()
def onquit(self, event):
print("Event handler 'onquit' not implemented!")
event.Skip()
def ingesopor(self, event):
print("Event handler 'ingesopor' not implemented!")
event.Skip()
def pagode(self, event):
print("Event handler 'pagode' not implemented!")
event.Skip()
def conciliaciones(self, event):
print("Event handler 'conciliaciones' not implemented!")
event.Skip()
def balanza_de_comprobacion(self, event):
print("Event handler 'balanza_de_comprobacion' not implemented!")
event.Skip()
def balance_general(self, event):
print("Event handler 'balance_general' not implemented!")
event.Skip()
def estado_de_resultado(self, event):
print("Event handler 'estado_de_resultado' not implemented!")
event.Skip()
def flujo_de_efectivo(self, event):
print("Event handler 'flujo_de_efectivo' not implemented!")
event.Skip()
def Estado_de_capital(self, event):
print("Event handler 'Estado_de_capital' not implemented!")
event.Skip()
def habilitar(self, event):
print("Event handler 'habilitar' not implemented!")
event.Skip()
def itbis_en_compra(self, event):
print("Event handler 'itbis_en_compra' not implemented!")
event.Skip()
def itbis_en_venta(self, event):
print("Event handler 'itbis_en_venta' not implemented!")
event.Skip()
def Formulario_de_NCF_Nulo(self, event):
print("Event handler 'Formulario_de_NCF_Nulo' not implemented!")
event.Skip()
def itbis_en_aduana(self, event):
print("Event handler 'itbis_en_aduana' not implemented!")
event.Skip()
def ir_dicisiete(self, event):
print("Event handler 'ir_dicisiete' not implemented!")
event.Skip()
def ir_tres(self, event):
print("Event handler 'ir_tres' not implemented!")
event.Skip()
def crearusuario(self, event):
print("Event handler 'crearusuario' not implemented!")
event.Skip()
def oncxcempleado(self, event):
print("Event handler 'oncxcempleado' not implemented!")
event.Skip()
def ondescuentoaempleado(self, event):
print("Event handler 'ondescuentoaempleado' not implemented!")
event.Skip()
def agnadirempleado(self, event):
print("Event handler 'agnadirempleado' not implemented!")
event.Skip()
def agnomina(self, event):
print("Event handler 'agnomina' not implemented!")
event.Skip()
def impuestonomina(self, event):
print("Event handler 'impuestonomina' not implemented!")
event.Skip()
def configuraciones(self, event):
print("Event handler 'configuraciones' not implemented!")
event.Skip()
def acerca(self, event):
print("Event handler 'acerca' not implemented!")
event.Skip()
def resivodeingreso(self, event):
print("Event handler 'resivodeingreso' not implemented!")
event.Skip()
def pagos(self, event):
print("Event handler 'pagos' not implemented!")
event.Skip()
def mercanciaresibida(self, event):
print("Event handler 'mercanciaresibida' not implemented!")
event.Skip()
def bloquear(self, event):
print("Event handler 'bloquear' not implemented!")
event.Skip()
def close(self, event):
print("Event handler 'close' not implemented!")
event.Skip()
class MyFrame(wx.MDIParentFrame):
def __init__(self, *args, **kwds):
kwds["style"] = kwds.get("style", 0) | wx.DEFAULT_FRAME_STYLE
wx.MDIChildFrame.__init__(self, *args, **kwds)
self.SetSize((400, 294))
self.SetTitle("frame")
# Menu Bar
self.frame_menubar = wx.MenuBar()
wxglade_tmp_menu = wx.Menu()
item = wxglade_tmp_menu.Append(wx.ID_ANY, "&Open", "Abril Ventana")
self.Bind(wx.EVT_MENU, self.open, item)
self.frame_menubar.Append(wxglade_tmp_menu, "&File")
self.SetMenuBar(self.frame_menubar)
# Menu Bar end
# Tool Bar
self.frame_toolbar = wx.ToolBar(self, -1, style=wx.TB_DEFAULT_STYLE)
tool = self.frame_toolbar.AddTool(wx.ID_ANY, "&open CTRL-O", wx.Bitmap("C:/Users/Dell/Documents/python/Nainady App/imagenes/business-color_money-bag_icon-icons.com_53447.png", wx.BITMAP_TYPE_ANY), wx.NullBitmap, wx.ITEM_NORMAL, "Abril Ventana", "Abril Ventana")
self.Bind(wx.EVT_TOOL, self.open, id=tool.GetId())
self.SetToolBar(self.frame_toolbar)
self.frame_toolbar.Realize()
# Tool Bar end
self.Layout()
self.Centre()
def open(self, event):
print("Event handler 'open' not implemented!")
f = MyFrame1(self, -1, "juan")
f.Show()
event.Skip()
class MyFrame1(wx.MDIChildFrame):
def __init__(self, *args, **kwds):
kwds["style"] = kwds.get("style", 0) | wx.DEFAULT_FRAME_STYLE
wx.MDIChildFrame.__init__(self, *args, **kwds)
self.SetSize((400, 300))
self.SetTitle("frame_1")
self.panel_1 = wx.Panel(self, wx.ID_ANY)
sizer_1 = wx.BoxSizer(wx.VERTICAL)
sizer_1.Add((0, 0), 0, 0, 0)
self.panel_1.SetSizer(sizer_1)
self.Layout()
class MyApp(wx.App):
def OnInit(self):
self.mainwindows = MainWindows(None, wx.ID_ANY, "")
self.SetTopWindow(self.mainwindows)
self.mainwindows.Show()
return True
if __name__ == "__main__":
app = MyApp(0)
app.MainLoop()
|
[
"jrvadez@gmail.com"
] |
jrvadez@gmail.com
|
ed817dc1416c6f9ee3bd63420344cf905981be76
|
f8b77d8b7d90dabfa3b222116d9fe462d890e89b
|
/plans/fixed_ensemble_resnet_linear_4.py
|
53480a497b356b8478b73ceacb2478cfd372a96e
|
[
"BSD-2-Clause"
] |
permissive
|
dbis-uibk/MediaEval2021
|
94e4041d6e82a28ceb95c68994808d0acc725915
|
14d754d9cea36415090aaa115db81f5ace465964
|
refs/heads/master
| 2023-08-27T19:12:17.758042
| 2021-11-03T12:12:57
| 2021-11-03T12:12:57
| 424,210,495
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,196
|
py
|
"""Ensemble plan manually split by type moode/theme."""
import json
from dbispipeline.evaluators import FixedSplitEvaluator
from dbispipeline.evaluators import ModelCallbackWrapper
import numpy as np
from sklearn.pipeline import Pipeline
from mediaeval2021 import common
from mediaeval2021.dataloaders.melspectrograms import MelSpectPickleLoader
from mediaeval2021.models.ensemble import Ensemble
from mediaeval2021.models.wrapper import TorchWrapper
dataloader = MelSpectPickleLoader('data/mediaeval2020/melspect_1366.pickle')
label_splits = [
np.arange(0, 14, 1),
np.arange(14, 28, 1),
np.arange(28, 42, 1),
np.arange(42, 56, 1),
]
pipeline = Pipeline([
('model',
Ensemble(
base_estimator=TorchWrapper(
model_name='ResNet-18',
dataloader=dataloader,
batch_size=64,
early_stopping=True,
),
label_splits=label_splits,
epochs=100,
)),
])
evaluator = ModelCallbackWrapper(
FixedSplitEvaluator(**common.fixed_split_params()),
lambda model: common.store_prediction(model, dataloader),
)
result_handlers = [
lambda results: print(json.dumps(results, indent=4)),
]
|
[
"mikevo-uibk@famv.net"
] |
mikevo-uibk@famv.net
|
09d98803d9190b4e2b6db8953c989dbe125f17b9
|
77f794a8e2c915073f32b9278e7123b49af9b71f
|
/hm_12_列表的数据统计.py
|
84e6106b2aac6bcdc6269f43cfc6c01a3a7fe07a
|
[] |
no_license
|
Chuxiaxia/python
|
5c1c1a3c511bce9bf527db151173f1a72742a024
|
b6408f2805bd890e09e1040a0b881bd3cddd4c0c
|
refs/heads/master
| 2020-04-24T09:33:05.746018
| 2019-02-21T13:40:20
| 2019-02-21T13:40:20
| 171,865,855
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 438
|
py
|
name_list = ["Xey", "ajl", "安家樑", "Xey"]
# len(length长度)函数可以统计列表中元素的总数
list_len = len(name_list)
print("列表中包含%d个元素" % list_len)
# count方法可以统计列表中某一个数据出现的次数
count = name_list.count("Xey")
print("Xey出现了%d次" % count)
# 从列表中删除第一次出现的数据，如果数据不存在程序会报错
name_list.remove("Xey")
print(name_list)
|
[
"353091935@qq.com"
] |
353091935@qq.com
|
1230bd8aea0ed2cf0e02c98811fd1bca3bac9353
|
e6d4a87dcf98e93bab92faa03f1b16253b728ac9
|
/algorithms/python/smallestGoodBase/smallestGoodBase.py
|
0fc48f86b09d916c4865349241f9dfd2a7f0a365
|
[] |
no_license
|
MichelleZ/leetcode
|
b5a58e1822e3f6ef8021b29d9bc9aca3fd3d416f
|
a390adeeb71e997b3c1a56c479825d4adda07ef9
|
refs/heads/main
| 2023-03-06T08:16:54.891699
| 2023-02-26T07:17:47
| 2023-02-26T07:17:47
| 326,904,500
| 3
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 843
|
py
|
#! /usr/bin/env python3
# -*- coding: utf-8 -*-
# Source: https://leetcode.com/problems/smallest-good-base/
# Author: Miao Zhang
# Date: 2021-02-15
class Solution:
def smallestGoodBase(self, n: str) -> str:
num = int(n)
# n = 1 + k + k^2+....k^(m - 1)
# i:m
for i in range(int(math.log(num + 1, 2)), 1, -1):
# base k
left = 2
right = pow(num, 1 / (i - 1)) + 1
while left < right:
mid = int(left + (right - left) // 2)
sums = 0
for j in range(i):
sums = sums * mid + 1
if sums == num:
return str(mid)
elif sums < num:
left = mid + 1
else:
right = mid
return str(num - 1)
|
[
"zhangdaxiaomiao@163.com"
] |
zhangdaxiaomiao@163.com
|
2e75f2970a695204c2cad568f28caace7e93c6bf
|
4834c27030b42cd710e9fd19c25f882a690cc734
|
/tools/vis.py
|
09d5d20f7597cb6909cf963d32a6d2442baf8394
|
[
"MIT"
] |
permissive
|
Muphys/ship_detection
|
c80d348bc8d541100b2b871f4f6fe945698c6563
|
9e6ce6a11c51843ebb877e471546f15438b09718
|
refs/heads/main
| 2023-01-21T09:25:53.275309
| 2020-12-04T08:44:12
| 2020-12-04T08:44:12
| 318,425,830
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,072
|
py
|
import numpy as np
import matplotlib.pyplot as plt
# %matplotlib inline
def get_data(str, tag):
tmp = str.split(f"{tag}: ")[1].split(" ")[0]
return float(tmp)
if __name__ == '__main__':
it = []
total_loss = []
loss_cls = []
loss_box_reg = []
loss_mask = []
loss_rpn_cls = []
loss_rpn_loc =[]
lr=[]
log_file = '../train/output_r50_200000_ROI512_augment/r50_200000_ROI512_augment.log'
with open(log_file) as f:
for line in f:
if "eta" not in line:
continue
it.append(get_data(line, 'iter'))
total_loss.append(get_data(line, 'total_loss'))
loss_cls.append(get_data(line, 'loss_cls'))
loss_box_reg.append(get_data(line, 'loss_box_reg'))
loss_mask.append(get_data(line, 'loss_mask'))
loss_rpn_cls.append(get_data(line, 'loss_rpn_cls'))
loss_rpn_loc.append(get_data(line, 'loss_rpn_loc'))
lr.append(get_data(line, 'lr'))
fig = plt.figure(figsize=(8,6))
ax2 = fig.add_subplot(111)
ax1 = ax2.twinx()
ax1.plot(it, total_loss, color='red', label='total_loss')
ax1.plot(it, loss_cls, color='purple', label='loss_cls')
ax1.plot(it, loss_box_reg, color='blue', label='loss_box_reg')
ax1.plot(it, loss_mask, color='orange', label='loss_mask')
ax1.plot(it, loss_rpn_cls, color='olive', label='loss_rpn_cls')
ax1.plot(it, loss_rpn_loc, color='green', label='loss_rpn_loc')
#设置坐标轴范围
ax1.set_xlim((0,it[-1]))
ax1.set_ylim((0,1))
# 设置坐标轴、图片名称
ax1.set_xlabel('iters')
log_name = log_file.split('.log')[0].split('/')[-1]
cfg = log_name.split('_')
ax1.set_title(f'{cfg[-2]}_{cfg[-1]}')
ax2.plot(it, lr, color='black', label='lr')
ax2.set_ylim([0, max(lr)*1.1])
ax1.legend(loc='upper right')
ax2.legend(loc='center right')
ax1.set_ylabel('loss')
ax2.set_ylabel('learning rate')
plt.savefig('../train/output_r50_200000_ROI512_augment/'+ log_name + '.png')
plt.show()
|
[
"971199215@qq.com"
] |
971199215@qq.com
|
5d8e997cb1f97285a004ae94b1041e7d033ef71e
|
54e9710eb0e8da36d420acf1d74426aaad4a85d0
|
/main.py
|
c86a5c77f47f45b54cdad4eeb7a2a15b37425004
|
[] |
no_license
|
syedhassanabbas347/ADM-HW3
|
2fc632c26f8afff8d612de15b86b046a5637a8eb
|
f455a4ed5f2e5c7571d80a73dd3e60abec39efcf
|
refs/heads/master
| 2020-09-03T20:09:50.679499
| 2019-11-17T22:58:06
| 2019-11-17T22:58:06
| 219,557,215
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 6,360
|
py
|
#!/usr/bin/env python
# coding: utf-8
# In[32]:
import urllib.request
from bs4 import BeautifulSoup
import requests
import csv
import pandas as pd
import json
import collections
import math
# we write routines functions that will clean our data
# In[44]:
# we load the dictionnary we just created
with open('dic1.json') as json_file:
data = json.load(json_file)
with open('dicvoc.json') as json_file:
listemot = json.load(json_file)
with open('dic2.json') as json_file:
dicInverted = json.load(json_file)
with open('listedoc2.json') as json_file:
listedoc2 = json.load(json_file)
with open('dicvoc.json') as json_file:
listemot2 = json.load(json_file)
with open('number_words_doc.json') as json_file:
dic_words_doc = json.load(json_file)
import import_ipynb
from index_utils import preprocess
from collector_utils1 import file_to_parse
df = file_to_parse(3)
# In[45]:
def search_engine1(query):
query = preprocess((query)) #we preprocess it
listedocuments = []
tfidf_query = collections.Counter(query) #turn our query into a dictionnary (key = word, value = occurence)
for key in tfidf_query.keys():
if key not in listemot2:
print("Word(s) in your query does not exist")
return
for element in query: # we preprocess the query, and we iterring into the words
if element in listemot: #we check if the word is in the list of words
i = listemot.index(element) # we get the index of the word
listedocuments.append(data[str(i)]) # we go into the dictionnary to get the documents that contain the word
#we do the intersection of all the list to get the document that contain all the word of the query
result = list(set(listedocuments[0]).intersection(*listedocuments[:len(listedocuments)]))
if len(result) == 0:
print('No document contains all your words')
return
listetitle = []
listeintro = []
listeurl = []
for element in result: #element is a number of tsv document
with open(r'C:\Users\danyl\OneDrive\Documents\tsv\document_'+element+'.tsv', encoding = 'utf8') as tsvfile:
reader = csv.reader(tsvfile, delimiter='\t')
for row in reader:
if len(row)>0:
a = row[0] #we get the title
b = row[1] #get the intro
listetitle.append(a)
listeintro.append(b)
listeurl.append(df.iloc[int(element)][0]) #we get the url using the dataframe of the beginning
dfresult = pd.DataFrame(list(zip(listetitle, listeintro,listeurl)),
columns =['Title', 'Intro', 'URL']) #we group the result in a dataframe
return(dfresult)
def search_engine_2(query):
query = preprocess((query)) #we preprocess it
listedocuments = []
tfidf_query = collections.Counter(query) #turn our query into a dictionnary (key = word, value = occurence)
for key in tfidf_query.keys():
if key not in listemot2:
print("Word(s) in your query does not exist")
return
for key,values in tfidf_query.items():
tf = values/len(query) #for each word in the query we calculate the tf-idf
tfidf_query[key] = tf*(1+math.log(float(29981/len(dicInverted[str(listemot2.index(key))]))))
# as we have done in the first part, we get the documents that contains all we words of the query
listedocuments = []
for element in query:
if element in listemot2:
i = listemot2.index(element)
listedocuments.append(dicInverted[str(i)].keys())
results = list(set(listedocuments[0]).intersection(*listedocuments[:len(listedocuments)]))
if len(results) == 0:
print('No document contains all your words')
return
#we create a dictionnary (key = document, value = dictionnary (key = words in query, value = tf-idf))
dic_final = {}
for result in results :
dic_result = {}
for element in query:
i = listemot2.index(element)
dic_result[element] = dicInverted[str(i)][str(result)]
dic_final[result] = dic_result
# we compute the cosine similary which is just a formula, using the tf-idf of each word with respect to the documents, and the tf-idf of the query
dic_cosine = {}
for keys, values in dic_final.items():
dot_prod = 0
norm_query = 0
norm_doc = 0
for key in tfidf_query.keys():
dot_prod = dot_prod + values[key] * tfidf_query[key]
norm_query = norm_query + tfidf_query[key]**2
norm_doc = norm_doc + values[key]**2
norm_query = math.sqrt(norm_query)
norm_doc = math.sqrt(norm_doc)
cosine_similarity = dot_prod/(norm_query*norm_doc)
dic_cosine[keys] = cosine_similarity
#we store the cosine_similarity of each document with the query in a dictionnary (key = document, value = cosine_similarity
pd.options.display.max_colwidth = 50
#we compute the same code we used in the first part
listetitle = []
listeintro = []
listeurl = []
listecosine = []
for element in results:
with open(r'C:\Users\danyl\OneDrive\Documents\tsv\document_'+element+'.tsv', encoding = 'utf8') as tsvfile:
reader = csv.reader(tsvfile, delimiter='\t')
for row in reader:
if len(row)>0:
a = row[0]
b = row[1]
listetitle.append(a)
listeintro.append(b)
listeurl.append(df.iloc[int(element)][0])
listecosine.append(round(dic_cosine[element],2)) #we just add the calcul of the cosine similarity of each document
dfresult = pd.DataFrame(list(zip(listetitle, listeintro,listeurl,listecosine)),
columns =['Title', 'Intro', 'URL','Similarity'])
dfresult = dfresult.sort_values(by=['Similarity'], ascending = False)
return(dfresult)
# In[46]:
nbr = int(input("Choose the search engine (1 or 2)"))
query = str(input("Enter your query"))
if nbr == 1:
result = search_engine1(query)
else:
result = search_engine_2(query)
result
# In[ ]:
|
[
"noreply@github.com"
] |
syedhassanabbas347.noreply@github.com
|
a99d095a7e339d7dba315704bd84f046d2fd11f5
|
2a10ec3bc377beb0bfb0998b02ce2a0fab98ede0
|
/venv/Scripts/pip3-script.py
|
20403cd6bd20f168b34ece56f0949e0072b33b9d
|
[
"ISC",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause",
"Zlib",
"LicenseRef-scancode-openssl",
"LicenseRef-scancode-ssleay-windows",
"BSD-3-Clause",
"OpenSSL",
"MIT"
] |
permissive
|
bopopescu/StockMarketGame
|
6a3dd8d22c23a9dafef6415000df1acd4d751923
|
48e777e1bda31c663c40fe18ff3229eeb2257b46
|
refs/heads/master
| 2022-11-22T10:08:18.542410
| 2019-11-10T01:54:43
| 2019-11-10T01:54:43
| 281,805,787
| 0
| 0
| null | 2020-07-22T23:42:10
| 2020-07-22T23:42:10
| null |
UTF-8
|
Python
| false
| false
| 424
|
py
|
#!C:\Users\estigum\Documents\GitHub\StockMarketGame\venv\Scripts\python.exe
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==10.0.1','console_scripts','pip3'
__requires__ = 'pip==10.0.1'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('pip==10.0.1', 'console_scripts', 'pip3')()
)
|
[
"estigum@gmail.com"
] |
estigum@gmail.com
|
ad03fec15fe1915e7eea4a6164a1ec3c19cc4515
|
12373d8a1dacbd7eb87d3af22d7f80b0cab7712e
|
/store_locator/asgi.py
|
c5389502121bb5c911bc96f3c8561a58fc320ac5
|
[] |
no_license
|
mayurbiw/store_locator
|
e1672149a8bfd2751801919cde6e93ebcf9611ba
|
afec4b3dfc7db40731c8e39a288d9c60f9e5db39
|
refs/heads/main
| 2023-01-30T23:50:30.487494
| 2020-12-18T16:38:43
| 2020-12-18T16:38:43
| 319,128,325
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 403
|
py
|
"""
ASGI config for store_locator project.
It exposes the ASGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/3.1/howto/deployment/asgi/
"""
import os
from django.core.asgi import get_asgi_application
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'store_locator.settings')
application = get_asgi_application()
|
[
"mayurbiw@gmail.com"
] |
mayurbiw@gmail.com
|
b454e42a2bc91d38dbdb4c2052da1a603fdaf6db
|
4f026ddcf8f058d884f15259f0e42c2178eb2157
|
/clare/clare/application/factories.py
|
0dadccd763c699f4a366d61970db657bafff708f
|
[
"MIT"
] |
permissive
|
dnguyen0304/roomlistwatcher
|
afd95e5f601f77fc8d7c4cd4307e60f36b53162c
|
7ac4d5172de22dd8906662da521995c8e06c2617
|
refs/heads/master
| 2021-01-20T22:55:04.289589
| 2017-11-16T04:09:49
| 2017-11-16T04:09:49
| 101,829,306
| 0
| 0
| null | 2017-11-16T04:09:49
| 2017-08-30T02:38:56
|
Python
|
UTF-8
|
Python
| false
| false
| 2,677
|
py
|
# -*- coding: utf-8 -*-
import Queue
import os
import threading
import uuid
from . import applications
from . import download_bot
from . import room_list_watcher
class Application(object):
def __init__(self, infrastructure, properties):
"""
Parameters
----------
infrastructure : clare.infrastructure.infrastructures.ApplicationInfrastructure
properties : collections.Mapping
"""
self._infrastructure = infrastructure
self._properties = properties
def create(self):
"""
Returns
-------
clare.application.applications.Application
"""
queue = Queue.Queue()
# Construct the room list watcher.
room_list_watcher_factory = room_list_watcher.factories.Producer(
infrastructure=self._infrastructure.room_list_watcher,
properties=self._properties['room_list_watcher'])
room_list_watcher_ = room_list_watcher_factory.create()
# Include threading.
kwargs = {
'interval': self._properties['room_list_watcher']['interval']
}
room_list_watcher_ = threading.Thread(name='room_list_watcher',
target=room_list_watcher_.produce,
kwargs=kwargs)
room_list_watcher_.daemon = True
# Construct the download bot.
download_bot_factory = download_bot.factories.Factory(
queue=queue,
properties=self._properties['download_bot'])
directory_path = os.path.join(
self._properties['download_bot']['factory']['root_directory_path'],
str(uuid.uuid4()))
download_bot_ = download_bot_factory.create(
download_directory_path=directory_path)
# Include threading.
kwargs = {
'interval': self._properties['download_bot']['interval'],
'timeout': self._properties['download_bot']['timeout']
}
download_bot_ = threading.Thread(name='download_bot',
target=download_bot_.consume,
kwargs=kwargs)
download_bot_.daemon = True
# Construct the application.
application = applications.Application(
room_list_watcher=room_list_watcher_,
download_bot=download_bot_)
return application
def __repr__(self):
repr_ = '{}(infrastructure={}, properties={})'
return repr_.format(self.__class__.__name__,
self._infrastructure,
self._properties)
|
[
"dnguyen0304@gmail.com"
] |
dnguyen0304@gmail.com
|
455f0eb252681dc48ed0c75166d18be7a3427598
|
d518877677fc47ec794bd52c874975ad05e35aba
|
/6.24/队列列表实现.py
|
72f7e5a091981d78b4988c7b0c0c2f2f49d8e222
|
[] |
no_license
|
lulu-yaya/ds
|
ea0bfa5c9a612ecf2aefe74ddefb30b4fc2e3d16
|
b4353d11b21651d0f71922e41f0474fac4219b5d
|
refs/heads/master
| 2022-11-10T19:31:40.567789
| 2020-06-26T10:01:42
| 2020-06-26T10:01:42
| 275,071,405
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 681
|
py
|
class Queue:
def __init__(self):
self.enteries=[]
self.length=0
self.front=0
def __str__(self):
printed="<"+str(self.enteries)[1:-1]+">"
return printed
# 入队
def put(self,item):
self.enteries.append(item)
self.length +=1
# 出队,先进先出
def get(self):
self.length=self.length-1
dequeued=self.enteries[self.front]
self.enteries=self.enteries[1:]
return dequeued
def front(self):
return self.enteries[0]
def size(self):
return self.length
q=Queue()
q.put(1)
q.put(2)
q.put(5)
print(q)
q.get()
print(q)
print(q.front)
print(q.size())
|
[
"1319040466@qq.com"
] |
1319040466@qq.com
|
3c23686db6886c323c64f68a9b984e0c008fc6a3
|
1383830de3ffb5cd88d82a124da502d0a4145a4e
|
/ANN-Lab2/CompLearning2D.py
|
906832a5177072a02e6f89efff4d6365e6875315
|
[] |
no_license
|
ayoubbargach/ANN-Examples
|
5f835659d08235635809aef525b7e35181dcab57
|
bdbdd0188b6c641a9ef942b09e5e7854426d1f15
|
refs/heads/master
| 2020-04-02T03:59:52.841409
| 2018-10-21T10:07:52
| 2018-10-21T10:07:52
| 153,994,500
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 9,207
|
py
|
import math
import random
import numpy as np
import matplotlib.pyplot as plt
import argparse
from sklearn.neural_network import MLPRegressor
np.set_printoptions(threshold=np.nan) #Always print the whole matrix
def CL(RBF_Nodes, input_pattern, leaky = False):
iters = 1000
cl_learning_rate = 0.25
for _ in range (0, iters):
# pick random training vector
i = random.randint(0, len(input_pattern) - 1)
training_vector = np.asarray((input_pattern[i][0], input_pattern[i][1]))
# find closest rbf_node
closest_node = None
second_closest_node = None
closest_distance = float('inf')
for node in RBF_Nodes:
npNode = np.asarray((node.x, node.y))
distance = np.linalg.norm(training_vector - npNode)
if distance < closest_distance:
second_closest_node = closest_node
closest_distance = distance
closest_node = node
if closest_node == None:
continue
# move closest rbf_node closer to traning vector, dw = eta(x - w)
delta_node = cl_learning_rate * (training_vector - np.asarray((closest_node.x, closest_node.y)))
closest_node.x += delta_node[0]
closest_node.y += delta_node[1]
# consider strategy for dead units (e.g., leaky cl)
if leaky:
leaky_learning_rate = 0.1
'''
if second_closest_node == None:
continue
#second_winner = RBF_Nodes[random.randint(0, len(RBF_Nodes) - 1)]
second_winner = second_closest_node
second_delta_node = leaky_learning_rate * (training_vector - np.asarray((second_winner.x, second_winner.y)))
second_winner.x += second_delta_node[0]
second_winner.y += second_delta_node[1]
'''
for node in RBF_Nodes:
if node != closest_node:
# use gauss function to limit how leaky it is, nodes further away are less affected
gauss_factor = transfer_function(training_vector, node, 0.05)
delta_node = gauss_factor * leaky_learning_rate * (training_vector - np.asarray((node.x, node.y)))
node.x += delta_node[0]
node.y += delta_node[1]
def adjust_widths(RBF_Nodes):
for i in range(0, len(RBF_Nodes)):
min_dist = float('inf')
current_node = RBF_Nodes[i]
np_current_node = np.asarray((current_node.x, current_node.y))
for j in range(0, len(RBF_Nodes)):
if i == j:
continue
np_other_node = np.asarray((RBF_Nodes[j].x, RBF_Nodes[j].y))
dist = np.linalg.norm(np_current_node - np_other_node)
if dist < min_dist:
min_dist = dist
current_node.variance = max(min_dist * 1.35, 0.2)
def adjust_widths_smart(RBF_Nodes, input_pattern):
for i in range(0, len(RBF_Nodes)):
min_dist = float('inf')
current_node = RBF_Nodes[i]
np_current_node = np.asarray((current_node.x, current_node.y))
for j in range(0, len(input_pattern)):
if i == j:
continue
np_other_node = np.asarray((input_pattern[j][0], input_pattern[j][1]))
dist = np.linalg.norm(np_current_node - np_other_node)
if dist < min_dist:
min_dist = dist
current_node.variance = max(min_dist * 1.35, 0.2)
training_input = []
training_target = []
with open('data_lab2/ballist.dat') as f:
for line in f:
line_numbers = [float(x) for x in line.split()]
training_input.append(np.asarray([line_numbers[0], line_numbers[1]]))
training_target.append(np.asarray([line_numbers[2], line_numbers[3]]))
test_input = []
test_target = []
with open('data_lab2/balltest.dat') as f:
for line in f:
line_numbers = [float(x) for x in line.split()]
test_input.append(np.asarray([line_numbers[0], line_numbers[1]]))
test_target.append(np.asarray([line_numbers[2], line_numbers[3]]))
test_target = np.asarray(test_target)
learning_rate = 0.01
random.seed(a=None)
# Class that represents a 2d input and what type it should be classified as
class Node:
def __init__(self, x, y, v):
self.x = x
self.y = y
self.variance = v
def __repr__(self):
return "<x:%s y:%s v:%s>" % (self.x, self.y, self.variance)
def __str__(self):
return "member of Test"
def asarray(self):
return np.asarray([self.x, self.y])
# Mean squared error
def mean_squared_error(expected, predicted):
return np.sum((expected - predicted) ** 2)/len(expected)
# Squared error
def squared_error(expected, predicted):
return np.sum((expected - predicted) ** 2)
# Absolute residual error
def absolute_residual_error(expected, predicted):
return np.sum(abs(expected - predicted))/len(expected)
# We use Gaussian RBF's with the following transfer function
def transfer_function(x, position, variance):
return (math.exp((-(np.linalg.norm(x - position.asarray()))**2) / (2*(variance**2))))
def euclidean_distance(x1, y1, x2, y2):
return (math.sqrt(((x1 - x2)**2) + ((y1 - y2)**2)))
# Sets values in input_pattern that are >= 0 to 1 and values < 0 to -1
def binary(input_pattern):
for v in range (0, len(input_pattern)):
if (input_pattern[v] >= 0):
input_pattern[v] = 1
else:
input_pattern[v] = -1
return input_pattern
# Adds noise to input_pattern and then returns it as output_pattern
def noise(input_pattern):
output_pattern = []
for i in range(0, len(input_pattern)):
output_pattern.append(input_pattern[i] + np.random.normal(0, 0.1, 1)[0])
return output_pattern
# Generate function data
errors = []
comp_errors = []
# Initiate RBF nodes and WEIGHTS
NUM_NODES_ROWS = 5
NUM_NODES_COLS = 5
nodes = NUM_NODES_ROWS * NUM_NODES_COLS
min_x = 0
max_x = 1
min_y = 0
max_y = 0
variance = 0.2
mu, sigma = 0, 0.1 # used for weight initialization
RBF_Nodes = []
comp_RBF_Nodes = []
weight = []
comp_weight = []
for r in range(0, NUM_NODES_ROWS):
for c in range(0, NUM_NODES_COLS):
x = c / (NUM_NODES_COLS - 1)
y = r / (NUM_NODES_ROWS - 1)
#x = -(NUM_NODES_COLS - 1) * variance + c * 2 * variance + (NUM_NODES_COLS * variance)
#y = -(NUM_NODES_ROWS - 1) * variance + r * 2 * variance + NUM_NODES_ROWS * variance
init_weights = np.random.normal(mu, sigma, 2)
weight.append(np.asarray([init_weights[0], init_weights[1]]))
comp_weight.append(np.asarray([init_weights[0], init_weights[1]]))
RBF_Nodes.append(Node(x, y, variance))
comp_RBF_Nodes.append(Node(x, y, variance))
weight = np.array(weight)
comp_weight = np.array(comp_weight)
CL(comp_RBF_Nodes, training_input, True)
adjust_widths(comp_RBF_Nodes)
#adjust_widths_smart(comp_RBF_Nodes, training_input)
# Calculate SIN phi
training_phi = np.zeros((len(training_input), nodes))
comp_training_phi = np.zeros((len(training_input), nodes))
test_phi = np.zeros((len(training_input), nodes))
comp_test_phi = np.zeros((len(training_input), nodes))
for p in range (0, len(training_input)):
for n in range (0, len(RBF_Nodes)):
training_phi[p][n] = transfer_function(training_input[p], RBF_Nodes[n], RBF_Nodes[n].variance)
comp_training_phi[p][n] = transfer_function(training_input[p], comp_RBF_Nodes[n], comp_RBF_Nodes[n].variance)
test_phi[p][n] = transfer_function(test_input[p], RBF_Nodes[n], RBF_Nodes[n].variance)
comp_test_phi[p][n] = transfer_function(test_input[p], comp_RBF_Nodes[n], comp_RBF_Nodes[n].variance)
epochs = 1000
# Sequential Delta rule--------------------------------------------------------------------------------------------------------------------------------------------
for i in range(0, epochs):
for o in range(0, len(training_target)):
weight = weight + np.dot(np.transpose(learning_rate*(training_target[o] - np.dot(training_phi[o].reshape(1, -1), weight))),training_phi[o].reshape(1, -1)).transpose()
comp_weight = comp_weight + np.dot(np.transpose(learning_rate*(training_target[o] - np.dot(comp_training_phi[o].reshape(1, -1), comp_weight))),comp_training_phi[o].reshape(1, -1)).transpose()
test_output = np.dot(test_phi, weight)
comp_test_output = np.dot(comp_test_phi, comp_weight)
errors.append(absolute_residual_error(test_target, test_output))
comp_errors.append(absolute_residual_error(test_target, comp_test_output))
print("Epoch:", i, "SIN Sequential Delta rule error:", comp_errors[-1])
# Plot
ax = plt.gca()
plot_error = True
if plot_error:
ax.plot(errors)
ax.plot(comp_errors)
ax.legend(['Manually placed', 'Competitive learning'])
plt.ylabel('Absolute residual error')
plt.xlabel('Epochs')
plt.xlim([0, 200])
else:
comp = False
if comp:
X = []
Y = []
Circles = []
for node in comp_RBF_Nodes:
X.append(node.x)
Y.append(node.y)
Circles.append(plt.Circle((node.x, node.y), node.variance, color='k', fill=False, alpha= 0.1))
ax.plot(X, Y, "ro", alpha= 0.1)
for circle in Circles:
ax.add_artist(circle)
ax.scatter(np.asarray(test_input)[:,0], np.asarray(test_input)[:,1])
else:
X = []
Y = []
Circles = []
for node in RBF_Nodes:
X.append(node.x)
Y.append(node.y)
Circles.append(plt.Circle((node.x, node.y), node.variance, color='k', fill=False, alpha= 0.1))
ax.plot(X, Y, "ro", alpha= 0.1)
for circle in Circles:
ax.add_artist(circle)
ax.scatter(np.asarray(test_input)[:,0], np.asarray(test_input)[:,1])
plt.show()
|
[
"bargachayoub@gmail.com"
] |
bargachayoub@gmail.com
|
215c8f57546333741fc0493c871ce51784463d85
|
0838c6d72c707380865767759bb47f084af361ab
|
/Multiples_of_3_and_5.py
|
4827b837aefa70113549e10897f61e5c972194c7
|
[] |
no_license
|
gsmcclellan/project_euler
|
ecb4fc23bfc6e92eac23d7b37ba7d33890cadc02
|
4140bf5004fd5395c8625f7f0a0027fc049b7018
|
refs/heads/master
| 2021-01-19T11:34:19.079026
| 2013-09-22T03:55:47
| 2013-09-22T03:55:47
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 262
|
py
|
def sum_of_multiples(lower_limit, upper_limit):
numbers = [x for x in range(lower_limit, upper_limit) if x % 3 == 0 or x % 5 == 0]
sum = 0
for num in numbers:
sum += num
return sum
sum = sum_of_multiples(1, 1000)
print(sum)
|
[
"gsmcclellan@gmail.com"
] |
gsmcclellan@gmail.com
|
4d04156b9c968e0dc15e18554f9ec5ba6c3673cc
|
07bfbab59aaf8b5d9853139a3c5a4c0ac0bdb6c4
|
/server/expedition_manager.py
|
e51490cfd9c52f61f09a93a4d1c63d553e94ec26
|
[] |
no_license
|
AngXingLong/ict2x01-2019t1-team16
|
a45e9262f40a01e3f183a9d1293b2b61ad0503c5
|
1a4c042c46b39b2e44f32c4853dd935e71d4df9b
|
refs/heads/master
| 2022-12-09T07:03:45.895243
| 2019-11-28T12:54:23
| 2019-11-28T12:54:23
| 220,923,826
| 0
| 0
| null | 2019-11-18T09:06:46
| 2019-11-11T07:20:41
|
Python
|
UTF-8
|
Python
| false
| false
| 7,116
|
py
|
import mysql_helper
from expedition import expeditionClass
import user_manager
import datetime
import random
import unittest
"""
Send in a User Object
"""
"""
Author: Felix Wang
Purpose: Returns a list of Expedition Objects
Returns: List of Expedition Objects
Parameters: hero_power_level : int
"""
def getExpeditionByID(expedition_id):
sql_statement = "SELECT * FROM myexpedition WHERE expeditionID = '" + expedition_id + "';"
try:
ex = mysql_helper.select_statement(sql_statement)[0]
except IndexError:
print("ERROR: Expedition ID does not exist.")
return [1]
expedition = expeditionClass(ex[0], ex[1], ex[2], ex[3], ex[4], ex[5], ex[6], 'Y')
return [0, expedition]
"""
Author: Felix Wang
Purpose: Returns a list of Expedition Objects
Returns: List of Expedition Objects
Parameters: User_OBJ
"""
def getExpeditions(User):
expeditionObjList = []
sql_statement = "SELECT * FROM myexpedition"
expeditionList = mysql_helper.select_statement(sql_statement)
for ex in expeditionList:
expedition = expeditionClass(ex[0], ex[1], ex[2], ex[3], ex[4], ex[5], ex[6], checkEligibleExpedition(ex[1], User.PowerLevel))
expeditionObjList.append(expedition)
return expeditionObjList
"""
Author: Felix Wang
Purpose: Checks if user is eligible for expedition
Returns: True (Eligible) / False (Illegible)
Parameter: required_power_level : int, hero_power_level: int
"""
def checkEligibleExpedition(required_power_level, hero_power_level):
if required_power_level <= hero_power_level:
return True
else:
return False
"""
Author: Felix Wang
Purpose: Start Expedition - Set the start and end time of the expedition
"""
"** TESTING **"
def startExpedition(userID, expeditionID):
# Get the Expedition ID.
response = getExpeditionByID(expeditionID)
if not response[0] == 0:
print("ERROR: Expedition ID does not exist.")
return False
expedition_obj = response[1]
# Get the start and end timings (start_timing, end_timing)
timings = getTiming(expedition_obj.TimeTaken)
# Get a randomized HToken value. +50 or -50)
randomizedHToken = randomizeHToken(expedition_obj.HToken)
# Insert record into myUserExpedition table.
values = [userID, 'Y', expeditionID, timings[0], timings[1], randomizedHToken]
sql_statement = "INSERT INTO myuserexpedition (userId, isOngoing, expeditionId, startTime, endTime, hTokens) " \
"VALUES (%s, %s, %s, %s, %s, %s)"
response = mysql_helper.sql_operation(sql_statement, values)
if not response:
return 1
print("Insertion into myUserExpedition successful")
# Need to disable user expedition status by updating the table to 'N'
sql_statement = "UPDATE myuser SET isAvailable = %s WHERE id = %s"
values = ['N', userID]
response = mysql_helper.sql_operation(sql_statement, values)
if not response:
return 1
print("User availability updated to 'N'")
return 0
"""
Author: Felix Wang
Purpose: Checks if user is eligible for expedition
Returns: True (Eligible) / False (Illegible)
Parameter: required_power_level : int, hero_power_level: int
"""
def randomizeHToken(HToken):
return HToken + random.randint(-50, 50)
"""
Author: Felix Wang
Purpose: Checks if user is eligible for expedition
Returns: True (Eligible) / False (Illegible)
Parameter: required_power_level : int, hero_power_level: int
"""
def getTiming(timeTaken):
start_timestamp = datetime.datetime.now()
end_timestamp = datetime.datetime.now() + datetime.timedelta(minutes = timeTaken)
return start_timestamp, end_timestamp
"""
Gets ongoing expeditions and returns it.
"""
def get_ongoing_expeditions(userID):
sql_statement = "SELECT * FROM myuserexpedition as ue INNER JOIN myexpedition as e on ue.expeditionId = e.expeditionId WHERE ue.userId = '" + str(userID) + "' AND ue.isOngoing = 'Y';"
response = mysql_helper.select_statement(sql_statement)
if not response:
return [1]
return [0, {"USER_ID": response[0][0],
"IS_ONGOING": response[0][1],
"EXPEDITION_ID": response[0][2],
"START_TIME": response[0][3],
"END_TIME": response[0][4],
"H_TOKENS": response[0][5],
"POWER_LEVEL": response[0][8],
"IMAGE": response[0][9],
"DESCRIPTION": response[0][10],
"TITLE": response[0][11],
"TIME_TAKEN": response[0][12],
"EST_H_TOKEN" : response[0][13]}]
"""
Gets completed expeditions and returns it.
"""
def get_completed_expeditions(userID):
sql_statement = "SELECT * FROM myuserexpedition as ue INNER JOIN myexpedition as e on ue.expeditionId = e.expeditionId WHERE ue.userId = '" + str(
userID) + "' AND ue.isOngoing = 'P';"
response = mysql_helper.select_statement(sql_statement)
if not response:
return [1]
return [0, {"USER_ID": response[0][0],
"IS_ONGOING": response[0][1],
"EXPEDITION_ID": response[0][2],
"START_TIME": response[0][3],
"END_TIME": response[0][4],
"H_TOKENS": response[0][5],
"POWER_LEVEL": response[0][8],
"IMAGE": response[0][9],
"DESCRIPTION": response[0][10],
"TITLE": response[0][11],
"TIME_TAKEN": response[0][12],
"EST_H_TOKEN" : response[0][13]}]
"""
End User Expedition. Update isAvailable to 'P' (Pending) and set expedition isongoing to 'N'
"""
def end_expedition(userID):
sql_statement = "UPDATE myuser set isAvailable = %s WHERE id = %s"
response = mysql_helper.sql_operation(sql_statement, ['P', str(userID)])
if not response:
print("First Statement has errors")
return 1
sql_statement = "UPDATE myuserexpedition set isOngoing = %s WHERE userId = %s and isOngoing = %s"
print(sql_statement)
response = mysql_helper.sql_operation(sql_statement, ['P', str(userID), 'Y'])
if not response:
print("Second statement has error")
return 1
return 0
"""
End User Expedition. Update isAvailable to 'P' (Pending) and set expedition isongoing to 'N'
"""
def complete_expedition(userID):
sql_statement = "UPDATE myuser set isAvailable = %s WHERE id = %s"
response = mysql_helper.sql_operation(sql_statement, ['Y', str(userID)])
if not response:
print("First Statement has errors")
return 1
sql_statement = "UPDATE myuserexpedition set isOngoing = %s WHERE userId = %s and isOngoing = %s"
print(sql_statement)
response = mysql_helper.sql_operation(sql_statement, ['N', str(userID), 'P'])
if not response:
print("Second statement has error")
return 1
return 0
|
[
"leeyuma.ly@gmail.com"
] |
leeyuma.ly@gmail.com
|
ff019f07eb5c8e7f8b76ea211847e34d492d6b19
|
ad06ae5cfcb8a30233d741a349fbcae47bdd67f6
|
/gwn/__init__.py
|
d49c771cd60ba3c8ea6f3fb723f58ee135f89829
|
[] |
no_license
|
temiolugbade/GlobalWorkspaceNetwork
|
36d351e801ecd39e87e29a20a23ee57f3465a542
|
ef6f74740fe3b1062a41fcee95264ac381090e8e
|
refs/heads/master
| 2023-03-25T04:35:57.046662
| 2019-09-01T12:18:47
| 2019-09-01T12:18:47
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 33
|
py
|
# __init__.py
# author: Cong Bao
|
[
"bao_cong@outlook.com"
] |
bao_cong@outlook.com
|
776d1393cd969acc0453d91a41711836eed317e4
|
9483dd999c98dcfcd564e15eaa3182ea561a6ab3
|
/migrations/versions/97fd285963c7_.py
|
6524521410bb060f8fca5069fd2e55f00e244a76
|
[] |
no_license
|
Rhpozzo/FlaskAPI
|
3ff441300b867fe728d5e25b3c3e2b45070e94b8
|
6748fa1376e3ca6659e082ff14e4cbde4a09018a
|
refs/heads/master
| 2021-07-02T21:43:19.909968
| 2020-01-24T01:37:41
| 2020-01-24T01:37:41
| 234,431,197
| 0
| 0
| null | 2021-05-06T19:58:20
| 2020-01-16T23:24:49
|
Python
|
UTF-8
|
Python
| false
| false
| 786
|
py
|
"""empty message
Revision ID: 97fd285963c7
Revises: 540192f3b71d
Create Date: 2020-01-18 20:07:20.091637
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '97fd285963c7'
down_revision = '540192f3b71d'
branch_labels = None
depends_on = None
def upgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.add_column('person', sa.Column('full_name', sa.String(length=120), nullable=False))
op.create_unique_constraint(None, 'person', ['full_name'])
# ### end Alembic commands ###
def downgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.drop_constraint(None, 'person', type_='unique')
op.drop_column('person', 'full_name')
# ### end Alembic commands ###
|
[
"guest_@Gabys-MacBook-Pro.local"
] |
guest_@Gabys-MacBook-Pro.local
|
3ab2c27c1233ee479a6aa9263023772ffa279da1
|
ac53f97ed730da035a0decb391aef03528e0e628
|
/test.py
|
bc5babfe9c27e996599600c9590f076c717b805d
|
[] |
no_license
|
jerryqypan/rl_rubiks
|
575a96e2c4d8c4fefecc2bdd6254b8cf685dd8aa
|
9710bfe8bebd7964174964b94ef3fc248b29f2d8
|
refs/heads/master
| 2021-08-29T14:12:15.028096
| 2017-12-14T02:45:12
| 2017-12-14T02:45:12
| 114,042,029
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 236
|
py
|
import random
import numpy as np
import pycuber as pc
move = ["R","R'","R2","U","U'","U2","F","F'","F2","D","D'","D2","B","B'","B2","L","L'","L2"]
shuffle = ' '.join(np.random.choice(move,20))
cube = pc.Cube()
cube(shuffle)
print(cube)
|
[
"qp7@duke.edu"
] |
qp7@duke.edu
|
dabb78bebf00d0ba0d51170326598ab7bc9dadee
|
34a134afbbcd3aa242b1f6bd05dace8a390caf64
|
/src/ui/window.py
|
ccbf45f9c147111b406c849b0cd0929ba7bc3957
|
[
"MIT"
] |
permissive
|
tulustul/MusicPlayer
|
ca6279fe114d7e2b4ac955015fbc72bf194f8953
|
e44ea89a00c3cf46936544e579191fbbf64b0417
|
refs/heads/master
| 2020-07-16T16:15:20.628072
| 2019-06-02T21:37:05
| 2019-06-02T21:37:05
| 73,945,357
| 4
| 0
|
MIT
| 2019-05-16T21:07:08
| 2016-11-16T17:44:50
|
Python
|
UTF-8
|
Python
| false
| false
| 3,132
|
py
|
import asyncio
import curses
import logging
from typing import Dict, Optional, List
import os
from core import keyboard
from core.config import config
from . import colors
from .renderer import Renderer
from .components.abstract_component import AbstractComponent
from .components.layout import Layout
from .components.input import InputComponent
from .rect import Rect
logger = logging.getLogger("ui.window")
os.environ.setdefault("ESCDELAY", "25")
class Window:
def __init__(self):
self.components: Dict[object, AbstractComponent] = {}
self.active_component_stack: List[AbstractComponent] = []
self.screen = None
self.create()
colors.init()
self.renderer = Renderer()
self.root_component = Layout()
self.root_component.renderer = self.renderer
self.root_component.set_rect(Rect(0, 0, curses.COLS, curses.LINES))
self.input_component = InputComponent()
self.input_container: Optional[Layout] = None
self.input_mode = False
self.running = True
def create(self):
self.screen = curses.initscr()
curses.noecho()
curses.cbreak()
curses.curs_set(0)
self.screen.keypad(1)
self.screen.nodelay(1)
try:
curses.start_color()
except Exception:
pass
self.screen.refresh()
def destroy(self):
curses.echo()
curses.nocbreak()
curses.curs_set(1)
self.screen.keypad(0)
self.screen.nodelay(0)
curses.endwin()
async def process_input(self):
interval = config.get("input_interval", 0.02)
while self.running:
self.renderer.update()
await asyncio.sleep(interval)
ch = 0
while ch != -1:
try:
ch = self.screen.getch()
if ch != -1:
keyboard.raw_keys.on_next(ch)
except curses.error as e:
logger.error(e)
except KeyboardInterrupt:
self.hide_view(self.active_component)
def get_component(self, component_class: type):
return self.root_component.get_component(component_class)
def focus(self, component: AbstractComponent):
self.active_component_stack.append(component)
def blur_active_component(self):
self.active_component_stack.pop()
@property
def active_component(self):
if self.active_component_stack:
return self.active_component_stack[-1]
return None
def quit(self):
self.running = False
async def input(self, prompt: str, default_value=""):
if not self.input_container:
raise ValueError("No input_container")
self.input_container.add(self.input_component)
self.root_component.update_layout()
self.input_mode = True
result = await self.input_component.request_value(
prompt, default_value,
)
self.input_component.detach()
self.input_mode = False
return result
|
[
"tulfm@poczta.fm"
] |
tulfm@poczta.fm
|
74e2f3fa38eda7d3f367db73cc95cbfd4cf52c1c
|
a07103a8180702f1a835c17f06f2561755473dc6
|
/amazon_spider/middlewares.py
|
c9b05e691a663f4b7c3411f3f8e608fa09919ba9
|
[] |
no_license
|
dejesusjmb/amazon_spider
|
245fc3f1362490aabc7aaa2daceffde8218f0b8a
|
38c51d43df3960501578e65ec73c5aaba9b18097
|
refs/heads/main
| 2023-06-16T18:36:33.974325
| 2021-07-02T10:12:56
| 2021-07-02T10:12:56
| 380,139,391
| 1
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,660
|
py
|
# Define here the models for your spider middleware
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
from scrapy import signals
# useful for handling different item types with a single interface
from itemadapter import is_item, ItemAdapter
class AmazonSpiderSpiderMiddleware:
# Not all methods need to be defined. If a method is not defined,
# scrapy acts as if the spider middleware does not modify the
# passed objects.
@classmethod
def from_crawler(cls, crawler):
# This method is used by Scrapy to create your spiders.
s = cls()
crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
return s
def process_spider_input(self, response, spider):
# Called for each response that goes through the spider
# middleware and into the spider.
# Should return None or raise an exception.
return None
def process_spider_output(self, response, result, spider):
# Called with the results returned from the Spider, after
# it has processed the response.
# Must return an iterable of Request, or item objects.
for i in result:
yield i
def process_spider_exception(self, response, exception, spider):
# Called when a spider or process_spider_input() method
# (from other spider middleware) raises an exception.
# Should return either None or an iterable of Request or item objects.
pass
def process_start_requests(self, start_requests, spider):
# Called with the start requests of the spider, and works
# similarly to the process_spider_output() method, except
# that it doesn’t have a response associated.
# Must return only requests (not items).
for r in start_requests:
yield r
def spider_opened(self, spider):
spider.logger.info('Spider opened: %s' % spider.name)
class AmazonSpiderDownloaderMiddleware:
# Not all methods need to be defined. If a method is not defined,
# scrapy acts as if the downloader middleware does not modify the
# passed objects.
@classmethod
def from_crawler(cls, crawler):
# This method is used by Scrapy to create your spiders.
s = cls()
crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
return s
def process_request(self, request, spider):
# Called for each request that goes through the downloader
# middleware.
# Must either:
# - return None: continue processing this request
# - or return a Response object
# - or return a Request object
# - or raise IgnoreRequest: process_exception() methods of
# installed downloader middleware will be called
return None
def process_response(self, request, response, spider):
# Called with the response returned from the downloader.
# Must either;
# - return a Response object
# - return a Request object
# - or raise IgnoreRequest
return response
def process_exception(self, request, exception, spider):
# Called when a download handler or a process_request()
# (from other downloader middleware) raises an exception.
# Must either:
# - return None: continue processing this exception
# - return a Response object: stops process_exception() chain
# - return a Request object: stops process_exception() chain
pass
def spider_opened(self, spider):
spider.logger.info('Spider opened: %s' % spider.name)
|
[
"jdejesus@buildzoom.com"
] |
jdejesus@buildzoom.com
|
35b1952b06b8274553605dae56d4b25d5da81a3d
|
77900cdd9a815caf1cd04705321ca93f5072179f
|
/Project/.history/product_20211116215222.py
|
58d5bb8d7d70ef65639f0d85425607bc5e56f6aa
|
[] |
no_license
|
Bom19990111/helloword_python
|
717799d994223d65de5adaeabecf396ff2bc1fb7
|
2ee2e67a60043f03c1ce4b070470c7d2dcdc72a7
|
refs/heads/master
| 2023-09-06T04:17:02.057628
| 2021-11-21T20:00:46
| 2021-11-21T20:00:46
| 407,063,273
| 0
| 1
| null | 2021-11-21T20:00:47
| 2021-09-16T07:18:35
|
Python
|
UTF-8
|
Python
| false
| false
| 11,136
|
py
|
import data as list_product
import random
import pandas as pd
# def __init__(self, Id, Product_code, Product_name, Brand, Year, Size):
# self.Id = Id
# self.Product_code = Product_code
# self.Product_name = Product_name
# self.Brand = Brand
# self.Year = Year
# self.Size = Size
# Thêm sản phẩm
def AddProduct():
print("THÊM SẢN PHẨM")
product = {
"Id": "",
"Product_code": "",
"Product_name": "",
"Brand": "",
"Price": "",
"Year": "",
"Quantity": "",
"Size": "",
"Status": ""
}
print("Nhập ID sản phẩm:")
try:
Id = int(input())
except:
print("ID phải là kiểu số, vui lòng nhập lại".upper())
print("------------------------------------")
try:
AddProduct()
except RuntimeError:
print("Dừng chương trình!")
while True:
student = FindProductDuplicate(Id)
if student != False:
print("ID đã tồn tại, vui lòng nhập lại ID")
Id = int(input())
else:
break
product['Id'] = Id
# Mã sản phẩm random
code_product = random.randint(1, 99)
str_id = "HKSP"
if code_product <= 9:
str_id += "0" + str(code_product)
else:
str_id += str(code_product)
product["Product_code"] = str_id
print("Nhập tên sản phẩm: ")
product['Product_name'] = input()
print("Nhập thương hiệu sản phẩm: ")
product['Brand'] = input()
print("Nhập giá sản phẩm: ")
try:
product['Price'] = float(input())
except ValueError:
print("Giá phải là kiểu số, vui lòng nhập lại".upper())
print("------------------------------------")
try:
print("Nhập giá sản phẩm: ")
product['Price'] = float(input())
except:
print("Dừng chương trình!")
print("Nhập năm sản xuất: ")
try:
product['Year'] = int(input())
except ValueError:
print("Năm phải là kiểu số, vui lòng nhập lại".upper())
print("------------------------------------")
try:
print("Nhập năm sản xuất: ")
product['Year'] = int(input())
except:
print('Dừng chương trình!')
print("Nhập số lượng: ")
try:
product['Quantity'] = int(input())
except ValueError:
print("Số lượng phải là kiểu số, vui lòng nhập lại".upper())
print("------------------------------------")
try:
print("Nhập số lượng: ")
product['Quantity'] = int(input())
except:
print('Dừng chương trình!')
print("Nhập size giày: ")
product['Size'] = input()
print("Nhập tình trạng sản phẩm: ")
product['Status'] = input()
list_product.list_product.append(product)
answer = input("Bạn có muốn nhập tiếp không? Y/N ")
if answer == "y" or answer == "Y":
AddProduct()
# Tìm kiếm ID trùng lặp
def FindProductDuplicate(Id):
for i in range(0, len(list_product.list_product)):
if list_product.list_product[i]['Id'] == Id:
return [i, list_product.list_product[i]]
return False
# Hiển thị tất cả sản phẩm
def ShowAllProduct():
print("*** HIỂN THỊ TẤT CẢ SẢN PHẨM ***")
if len(list_product.list_product) == 0 or len(list_product.list_product) < 0:
print("Chưa có sản phẩm nào để hiển thị! ".upper())
for i in range(0, len(list_product.list_product)):
print("ID : \t", list_product.list_product[i]['Id']),
print("Mã sản phẩm : \t",
list_product.list_product[i]['Product_code']),
print("Tên sản phẩm : \t",
list_product.list_product[i]['Product_name']),
print("Thương hiệu : \t", list_product.list_product[i]['Brand']),
print("Giá : \t", list_product.list_product[i]['Price']),
print("Năm xuất bản : \t", list_product.list_product[i]['Year']),
print("Số lượng : \t", list_product.list_product[i]['Quantity']),
print("Size giày : \t", list_product.list_product[i]['Size'])
print("Tình trạng : \t", list_product.list_product[i]['Status'])
print("________________________________")
# Sửa thông tin sản phẩm
def UpdateProduct():
print("*** CẬP NHẬT THÔNG TIN SẢN PHẨM ***")
print("Nhập ID sản phẩm cần sửa")
try:
Id = int(input())
product = FindProductDuplicate(Id)
except:
print("Vui lòng nhập đúng định dạng ID".upper())
UpdateProduct()
if product == False:
print("Không tìm thấy sản phẩm ID = ".upper(), Id)
print("********************************")
UpdateProduct()
else:
print("""Bạn muốn cập nhật mục nào ? :
0. Thoát.
1. Tên sản phẩm.
2. Thương hiệu sản phẩm.
3. Giá sản phẩm
4. Size giày.
5. Số lượng.
6. Năm xuất bản.
7. Tình trạng """)
action = 0
while action >= 0:
if action == 1:
UpdateProductName()
elif action == 2:
UpdateProductBrand()
elif action == 3:
UpdateProductPrice()
elif action == 4:
UpdateProductSize()
elif action == 5:
UpdateProductQuatity()
elif action == 6:
UpdateProductYear()
elif action == 7:
UpdateStatus()
def UpdateProductName():
print("Nhập tên cập nhật của sản phẩm: ")
name_product = input()
product[1]['Product_name'] = name_product
def UpdateProductBrand():
print("Nhập thương hiệu muốn cập nhật: ")
name_product = input()
product[1]['Brand'] = name_product
def UpdateProductPrice():
print("Nhập giá muốn cập nhật: ")
name_product = float(input())
product[1]['Price'] = name_product
def UpdateProductSize():
print("Nhập size muốn cập nhật: ")
name_product = input()
product[1]['Size'] = name_product
def UpdateProductYear():
print("Nhập năm sản xuất muốn cập nhật: ")
name_product = int(input())
product[1]['Year'] = name_product
list_product.list_product[product[0]] = product[1]
def UpdateProductQuatity():
print("Nhập số lượng muốn cập nhật: ")
name_product = int(input())
product[1]['Quantity'] = name_product
list_product.list_product[product[0]] = product[1]
def UpdateStatus():
print("Nhập tình trạng muốn cập nhật: ")
name_product = input()
product[1]['Status'] = name_product
list_product.list_product[product[0]] = product[1]
action = int(input("Bạn chọn mục cập nhật nào? "))
if action == 0:
print("Không cập nhật mục nào".upper())
print("********************************")
break
# Xóa sản phẩm
def DeleteProduct():
print("*** XÓA SẢN PHẨM ***")
print("Nhập ID sản phẩm cần xóa:")
Id = int(input())
product = FindProductDuplicate(Id)
if product == False:
print("Không tìm thấy sản phẩm ID = ".upper(), Id)
print("********************************")
else:
answer = input("Bạn có muốn xóa sản phẩm này không? Y/N ".upper())
if answer == "y" or answer == "Y":
if product != False:
list_product.list_product.remove(product[1])
print("Xóa sản phẩm thành công!".upper())
print("********************************")
else:
print("Đã từ chối xóa sản phẩm này!".upper())
print("********************************")
# Tìm kiếm sản phẩm
def FindProductByName():
print("*** TÌM KIẾM SẢN PHẨM ***")
if (len(list_product.list_product) == 0 or len(list_product.list_product) < 0):
print("Chưa có sản phẩm nào trong giỏ!".upper())
print("********************************")
else:
NameProduct = str(
input("Nhập tên sản phẩm hoặc tên thương hiệu bạn muốn tìm kiếm: ")).upper()
is_found = False
for i in range(0, len(list_product.list_product)):
if str(list_product.list_product[i]['Product_name']).upper() in NameProduct or str(list_product.list_product[i]['Brand']).upper() in NameProduct:
is_found = True
print("ID : \t", list_product.list_product[i]['Id']),
print("Mã sản phẩm : \t",
list_product.list_product[i]['Product_code']),
print("Tên sản phẩm : \t",
list_product.list_product[i]['Product_name']),
print("Thương hiệu : \t",
list_product.list_product[i]['Brand']),
print("Giá : \t",
list_product.list_product[i]['Price']),
print("Năm xuất bản : \t",
list_product.list_product[i]['Year']),
print("Số lượng : \t",
list_product.list_product[i]['Quantity']),
print("Size giày : \t",
list_product.list_product[i]['Size'])
print("Tình trạng : \t",
list_product.list_product[i]['Status'])
print("________________________________")
if not is_found:
print("Không tìm thấy sản phẩm này @@".upper())
print("********************************")
def SortProductNameA_Z():
list_product.list_product.sort(key=lambda item: item.get("Product_name"))
def SortProductNameZ_A():
list_product.list_product.sort(
key=lambda item: item.get("Product_name"), reverse=True)
def SortPriceAsc():
list_product.list_product.sort(key=lambda item: item.get("Price"))
def SortPriceDesc():
list_product.list_product.sort(
key=lambda item: item.get("Price"), reverse=True)
def ExportExecel():
pd.DataFrame(list_product.list_product).to_excel('danhsachsanpham.xlsx', header=False, index=False)
df = pd.read_excel(xl, header=None)
print(df.head())
def ImportExecel():
xl = pd.ExcelFile('danhsachsanpham.xlsx')
df = pd.read_excel(xl, header=None)
print(df.head())
|
[
"phanthituyngoc1995@gmail.com"
] |
phanthituyngoc1995@gmail.com
|
e3b8d5850095b18d45030906c434323935662296
|
b76ead7d69245710beb9eba31c70804e3d32a3bc
|
/avro_extract.py
|
6063905d72469a16f2a4c519a663be3bd95c4303
|
[] |
no_license
|
holbech/scrap_scripts
|
d4a01d9ddc6bdaa74aab50706d138b5f6a17d8b4
|
f41b9f3af939b9f4418d816a8209644893bf98e4
|
refs/heads/master
| 2022-04-27T16:44:44.518027
| 2022-03-08T18:29:35
| 2022-03-08T18:29:35
| 16,314,209
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,881
|
py
|
#!/usr/bin/env python
import argparse
from collections import defaultdict
from itertools import chain
import sys
from multiprocessing import Pool
import fastavro as avro
parser = argparse.ArgumentParser(description='Extracts fields from avro-files to tsv lines')
parser.add_argument('filenames', nargs='+', help='if extension of file is .lst or .txt it will be assumed to be a file of filenames')
parser.add_argument('-m', '--multiprocessing', type=int, default=1, help='Parallel processes to run')
parser.add_argument('-f', '--field', nargs='*', help='Field to extract')
parser.add_argument('-l', '--list-fields', action='store_true', help='List fields in files')
parser.add_argument('-a', '--add-header', action='store_true', help='Add field names as header to output')
parser.add_argument('-s', '--sample-values', type=int, default=0, help='If larger than zero, list each field in files along with this number of sample values')
args = parser.parse_args()
def get_fields(some_record):
for k,v in some_record.iteritems():
if isinstance(v, dict):
for sf in get_fields(v):
yield (k,) + sf
else:
yield (k,)
def expand(input_filename):
if input_filename.endswith(('.txt', '.lst')):
with open(input_filename, 'r') as files:
for l in files:
yield l.strip()
else:
yield input_filename
class SampleCollector(object):
def __init__(self):
self._values = set()
self.is_full = False
def add(self, value):
if not self.is_full:
self._values.add(value)
self.is_full = len(self._values) == args.sample_values
def __iter__(self):
return iter(self._values)
samples = (args.sample_values or None) and defaultdict(SampleCollector)
def _format(value):
if value is None:
return ""
if isinstance(value, basestring):
return value
try:
return ujson.dumps(value)
except:
if isinstance(value, (tuple, list)):
return '[' + ','.join( _format(v) for v in value ) + ']'
if isinstance(value, dict):
return '{' + ','.join( _format(v) for v in value ) + '}'
if not isinstance(value, basestring):
return str(value)
NOT_FOUND = object()
def _extract(some_record, field_names):
result = some_record
for f in field_names:
result = result.get(f, NOT_FOUND)
if result is not NOT_FOUND:
result = _format(result)
result = result.replace('\t','\\t').replace('\n','\\n')
if isinstance(result, unicode):
result = result.encode('utf-8')
if samples is not None and result:
samples[field_names].add(result)
return result
else:
return "FieldNotFound"
def extract(some_record, fields):
return [ _extract(some_record, f) for f in fields ]
global_fields = tuple( f.split('/') for f in args.field or () )
def extract_file(filename):
print >> sys.stderr, "Processing " + filename
result = []
with open(filename, 'rb') as avro_file:
reader = avro.reader(avro_file)
schema = reader.schema
fields = global_fields
add_header = args.add_header
for index, record in enumerate(reader):
if not fields:
fields = tuple(get_fields(record))
if args.list_fields:
print 'Fields in %s:' % (filename,)
for f in fields:
print ' Field: ' + '/'.join(f)
break
if add_header:
print '\t'.join( '/'.join( p.encode('utf-8') for p in f ) for f in fields )
add_header = False
if index and not (index % 1000):
if samples and all( s.is_full for s in samples.itervalues() ):
break
sys.stderr.write("Read %d lines of input\r" % (index,))
extracted_values = extract(record, fields)
if samples is None:
result.append('\t'.join(extracted_values))
if samples:
print 'Samples values from %s:' % (filename,)
for f in fields:
print ' ' + '/'.join(f) + ':'
for v in sorted(samples[f]):
print ' ' + v
print >> sys.stderr, "Read %d lines of input\r" % (index,)
return result
filenames = chain.from_iterable( expand(f) for f in args.filenames )
if args.multiprocessing > 1 and not args.sample_values:
if args.add_header:
sys.stdout.writelines( l + '\n' for l in extract_file(next(filenames)) )
pool = Pool(args.multiprocessing)
sys.stdout.writelines( l + '\n' for l in chain.from_iterable(pool.imap_unordered(extract_file, filenames, chunksize=1)) )
else:
for fn in filenames:
sys.stdout.writelines( l + '\n' for l in extract_file(fn) )
|
[
"sh@realtime-targeting.com"
] |
sh@realtime-targeting.com
|
bb9ac282b2774e54759acf1c0d583b248bd85841
|
0a08281fde5c5f37f9251c6e60e8a662a880b625
|
/timing_decode.py
|
35edefb77b07b0ce7359e484add7390c515a2c1b
|
[] |
no_license
|
robzwolf/huffman
|
3f7c9b82354266363e10ffd57b5d5b4dabdfd651
|
0d51100e9a368a02d12899752a1f6c4f9c7cb4ce
|
refs/heads/master
| 2021-09-07T02:11:37.353223
| 2018-02-15T15:59:57
| 2018-02-15T15:59:57
| 120,305,463
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 141
|
py
|
import huffman
for i in range(1, 9):
print("\nCalling encode(timing_{}.txt)...".format(i))
huffman.decode("timing_{}.hc".format(i))
|
[
"5098748+robzwolf@users.noreply.github.com"
] |
5098748+robzwolf@users.noreply.github.com
|
b00220203fdd6ed05a580a478f9bdbb63a9ba0c2
|
1031f441f7077599ce0e74e53ee3b8828c2e50c4
|
/src/other/test_uni.py
|
f3da28a0afed2f0503577fd4d056a0d198199570
|
[] |
no_license
|
Sejuapig/prod_log
|
22067a584781c21829f84550fa29c9a1fb9282d6
|
69f1a2aecf1488a5a5ca9c259b8234813bcd625c
|
refs/heads/master
| 2021-06-16T09:29:09.239012
| 2017-04-04T07:33:58
| 2017-04-04T07:33:58
| 81,428,272
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 522
|
py
|
import unittest,sys
import connexion as connexion
class premierTest(unittest.TestCase):
"""
Tests pour 1.py
"""
def test0(self):
bd, cursor = connexion.run()
cursor.execute("SELECT id_activity FROM activity where nom_activity ='Triathlon'")
id = cursor.fetchone()
"""
test 0
"""
self.assertEquals(8301, id)
if __name__ == '__main__':
unittest.main()
|
[
"sejuapig@gmail.com"
] |
sejuapig@gmail.com
|
33228e114bc20b0765bb650ad30f6d98a5f253bd
|
bfdc7a8c744375f734ab286098f87bc0b802bbe9
|
/patient/apps.py
|
69be906cb849a94acc39c04165642e78e1837278
|
[] |
no_license
|
hopgausi/egpaf-project
|
a153444beb2daf8c553d0d76898636a478329a6b
|
87df3dcca0b6c1a960f1dff9efc4a93fdd0fbdee
|
refs/heads/main
| 2023-03-01T18:43:31.542909
| 2021-02-11T01:57:22
| 2021-02-11T01:57:22
| 337,459,906
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 89
|
py
|
from django.apps import AppConfig
class patientConfig(AppConfig):
name = 'patient'
|
[
"jspyhack@gmail.com"
] |
jspyhack@gmail.com
|
a819988d7ff2b5dd395cdf6647f534d1e2bd76d9
|
ac227cc22d5f5364e5d029a2cef83816a6954590
|
/applications/physbam/physbam-lib/External_Libraries/Archives/boost/tools/build/v2/test/test2.py
|
cb74b851f46253b5bae80ccdd8ca872abd5ef6de
|
[
"BSL-1.0",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] |
permissive
|
schinmayee/nimbus
|
597185bc8bac91a2480466cebc8b337f5d96bd2e
|
170cd15e24a7a88243a6ea80aabadc0fc0e6e177
|
refs/heads/master
| 2020-03-11T11:42:39.262834
| 2018-04-18T01:28:23
| 2018-04-18T01:28:23
| 129,976,755
| 0
| 0
|
BSD-3-Clause
| 2018-04-17T23:33:23
| 2018-04-17T23:33:23
| null |
UTF-8
|
Python
| false
| false
| 471
|
py
|
#!/usr/bin/python
from BoostBuild import Tester, List
from time import sleep
t = Tester()
t.set_tree("test2")
t.run_build_system("-sBOOST_BUILD_PATH=" + t.original_workdir + "/..")
file_list = 'bin/foo/$toolset/debug/runtime-link-dynamic/' * List("foo foo.o")
t.expect_addition(file_list)
t.write("foo.cpp", "int main(int, char**) { return 0; }\n")
t.run_build_system("-d2 -sBOOST_BUILD_PATH=" + t.original_workdir + "/..")
t.expect_touch(file_list)
t.pass_test()
|
[
"quhang@stanford.edu"
] |
quhang@stanford.edu
|
28d7344bcf92d96c8e335aa3a125aa44f7ff2ff3
|
1a60dbe9eafd5e7fbae95d10ecd1255dff0f6cd8
|
/stdlogger/outputs/file.py
|
35671977237c0825543299cb0751ce801b5973be
|
[
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] |
permissive
|
verm666/stdlogger
|
2dacc9ba49707d6dd722e838ea41745b6dcdd022
|
8208730d50dce52671d92d1c43ac8b631ec11a02
|
refs/heads/master
| 2021-01-15T22:28:56.427660
| 2011-09-26T20:28:38
| 2011-09-26T20:28:38
| 2,327,133
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,638
|
py
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
from threading import Thread
import os
import time
class Output(object):
"""
Class for redirect logs to file.
"""
def __init__(self, **kwargs):
# set filename
if 'filename' not in kwargs:
raise ValueError("param 'filename' is required")
self.filename = kwargs['filename']
try:
self.file = open(self.filename, 'a')
except IOError:
print("Could not open file: %s" % self.filename)
# set max_size
if 'max_size' not in kwargs:
self.max_size = 2048
else:
self.max_size = int(kwargs['max_size'])
# set count (integer index. For example: access.log.1)
if 'count' not in kwargs:
self.count = 10
else:
self.count = int(kwargs['count'])
# set max_days (date index. For example: access.log.20110905)
if 'max_days' not in kwargs:
self.max_days = 10
else:
self.max_days = int(kwargs['max_days'])
# set current date (used in 'date-based' and 'date-size-based' rotation.
# see self.__rotate__()
self.r_date = int(time.strftime("%Y%m%d")) # "run date"
def __rotate__(self, kind='date'):
"""
Size-based, date-based or both rotation
"""
if kind == "size":
# Size-based rotation
size = os.path.getsize(self.filename)
if (size >= self.max_size):
for i in range(self.count - 1, 0, -1):
try:
os.rename(self.filename + "." + str(i), self.filename + "." + str(i + 1))
except OSError:
pass
os.rename(self.filename, self.filename + ".1")
self.file.close()
self.file = open(self.filename, 'a')
elif kind == "date":
# Date-based rotation
c_date = int(time.strftime("%Y%m%d")) # "current date"
if (self.r_date != c_date):
os.rename(self.filename, self.filename + "." + str(c_date))
self.file.close()
self.file = open(self.filename, 'a')
self.r_date = c_date
t = Thread(tarage=self.__care_old_files__, args=())
t.start()
elif kind == "date_size":
pass
def processing(self, line):
"""
Processing line (write line to file/rotate files)
"""
self.file.write(line)
self.__rotate__()
|
[
"verm666@gmail.com"
] |
verm666@gmail.com
|
04a0ae35c0b49d0518e6a68d481f6e317f214115
|
3a8c2bd3b8df9054ed0c26f48616209859faa719
|
/Challenges/surroundedRegions.py
|
570dcbb6b411e6fd035814e01998a9a4779b635f
|
[] |
no_license
|
AusCommsteam/Algorithm-and-Data-Structures-and-Coding-Challenges
|
684f1ca2f9ee3c49d0b17ecb1e80707efe305c82
|
98fb752c574a6ec5961a274e41a44275b56da194
|
refs/heads/master
| 2023-09-01T23:58:15.514231
| 2021-09-10T12:42:03
| 2021-09-10T12:42:03
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,718
|
py
|
"""
Surrounded Regions
Given a 2D board containing 'X' and 'O' (the letter O), capture all regions surrounded by 'X'.
A region is captured by flipping all 'O's into 'X's in that surrounded region.
Example:
X X X X
X O O X
X X O X
X O X X
After running your function, the board should be:
X X X X
X X X X
X X X X
X O X X
Explanation:
Surrounded regions shouldn’t be on the border, which means that any 'O' on the border of the board are not flipped to 'X'. Any 'O' that is not on the border and it is not connected to an 'O' on the border will be flipped to 'X'. Two cells are connected if they are adjacent cells connected horizontally or vertically.
"""
"""
BFS
Time: O(MN)
Space: O(N)
"""
class Solution:
def solve(self, board: List[List[str]]) -> None:
"""
Do not return anything, modify board in-place instead.
"""
queue = collections.deque()
for i in range(len(board)):
for j in range(len(board[0])):
if (i == 0 or i == len(board)-1 or j == 0 or j == len(board[0])-1) and board[i][j] == 'O':
queue.append((i, j))
directions = [(1, 0), (-1, 0), (0, -1), (0, 1)]
while queue:
i, j = queue.popleft()
if 0 <= i < len(board) and 0 <= j < len(board[0]) and board[i][j] == 'O':
board[i][j] = 'D'
for di, dj in directions:
queue.append((i + di, j + dj))
for i in range(len(board)):
for j in range(len(board[0])):
if board[i][j] == 'O':
board[i][j] = 'X'
elif board[i][j] == 'D':
board[i][j] = 'O'
|
[
"bennyhwanggggg@users.noreply.github.com"
] |
bennyhwanggggg@users.noreply.github.com
|
3d59814cd8d4c6d2a9fc0c9ed16e2cddfe7045f4
|
e44674fc2960c62812eeaa4232b6829b0273a1d0
|
/attacks/cw_l2.py
|
7f1445d77d8c3e3f4018628be21d15a047750f37
|
[
"MIT"
] |
permissive
|
psturmfels/adversarial_faces
|
890190582e158f2faa8550961b4420898a623953
|
e193a8a5b16a1085ddfe52150aa7f7a57bfa7a31
|
refs/heads/master
| 2023-01-28T09:32:02.861184
| 2020-12-04T00:00:32
| 2020-12-04T00:00:32
| 242,216,749
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 5,664
|
py
|
"""
Implements the L2 version of the Carlini-Wagner attack.
Ported into TensorFlow 2.0 from:
https://github.com/carlini/nn_robust_attacks/blob/master/li_attack.py
and
https://github.com/bethgelab/foolbox/blob/3999d4334969b7d3debdf846f3f0965eb9032013/foolbox/attacks/carlini_wagner.py
"""
import tensorflow as tf
import numpy as np
from tqdm import tqdm
from .attack import Attacker
class CWAttacker(Attacker):
def _get_default_kwargs(self, kwargs):
"""
Defines some default hyper-parameter values.
Args:
kwargs: A parameter dictionary.
"""
if 'max_iterations' not in kwargs:
kwargs['max_iterations'] = 1000
if 'initial_const' not in kwargs:
kwargs['initial_const'] = 1e-5
if 'learning_rate' not in kwargs:
kwargs['learning_rate'] = 5e-3
if 'largest_const' not in kwargs:
kwargs['largest_const'] = 2e+1
if 'const_factor' not in kwargs:
kwargs['const_factor'] = 2.0
if 'success_distance' not in kwargs:
kwargs['success_distance'] = 1.242
if 'initial_perturbation_dist' not in kwargs:
kwargs['initial_perturbation_dist'] = 0.025
if 'verbose' not in kwargs:
kwargs['verbose'] = False
if 'attack_criteria' not in kwargs:
kwargs['attack_criteria'] = 'all'
# One of all, any or mean
return kwargs
def _to_attack_space(self, x, bounds):
"""
Converts a tensor to hyperbolic tangent space.
Args:
x: A tensor
bounds: Minimum and maximum values
"""
min_, max_ = bounds
a = (min_ + max_) / 2
b = (max_ - min_) / 2
x = (x - a) / b # map from [min_, max_] to [-1, +1]
x = x * 0.999999 # from [-1, +1] to approx. (-1, +1)
x = tf.atanh(x) # from (-1, +1) to (-inf, +inf)
return x
def _to_model_space(self, x, bounds):
"""
Converts a tensor back into image space.
Args:
x: A tensor
bounds: Minimum and maximum values
"""
min_, max_ = bounds
x = tf.tanh(x) # from (-inf, +inf) to (-1, +1)
a = (min_ + max_) / 2
b = (max_ - min_) / 2
x = x * b + a # map from (-1, +1) to (min_, max_)
return x
def self_distance_attack(self, image_batch, epsilon=0.025, **kwargs):
"""
Attacks a batch of images using the Carlini Wagner attack and
the self-distance strategy.
Args:
image_batch: A batch of images.
epsilon: Amount of initial perturbation.
kwargs: Varies depending on attack.
"""
kwargs = self._get_default_kwargs(kwargs)
bounds = tf.reduce_min(image_batch), tf.reduce_max(image_batch)
# Initialize the perturbed example
noise = self._generate_noise(epsilon, image_batch)
initial_w_value = tf.clip_by_value(noise + image_batch, bounds[0], bounds[1])
initial_w_value = self._to_attack_space(initial_w_value, bounds)
perturbation_w = tf.Variable(initial_w_value)
original_embedding = self.model(image_batch)
original_embedding = self._l2_normalize(original_embedding)
optimizer = tf.keras.optimizers.Adam(learning_rate=kwargs['learning_rate'])
current_c = kwargs['initial_const']
while current_c <= kwargs['largest_const']:
perturbation_w.assign(initial_w_value)
def loss():
x_plus_delta = self._to_model_space(perturbation_w, bounds)
delta = x_plus_delta - image_batch
perturbed_embedding = self.model(x_plus_delta)
perturbed_embedding = self._l2_normalize(perturbed_embedding)
# Negative sign because we want to maximimize the distance
model_loss = -self._l2_distance(original_embedding, perturbed_embedding)
norm_loss = self._l2_norm(delta, axis=(1, 2, 3))
return current_c * model_loss + norm_loss
iterable = range(kwargs['max_iterations'])
if kwargs['verbose']:
print('Trying attack with c = {:.4f}'.format(current_c))
iterable = tqdm(iterable)
for _ in iterable:
optimizer.minimize(loss, [perturbation_w])
# Now we check if we have succeeded in our attack
x_plus_delta = self._to_model_space(perturbation_w, bounds)
perturbed_embedding = self.model(x_plus_delta)
perturbed_embedding = self._l2_normalize(perturbed_embedding)
model_loss = self._l2_distance(original_embedding, perturbed_embedding)
if kwargs['attack_criteria'] == 'all':
succeeded = tf.reduce_all(model_loss > kwargs['success_distance'])
elif kwargs['attack_criteria'] == 'any':
succeeded = tf.reduce_any(model_loss > kwargs['success_distance'])
elif kwargs['attack_criteria'] == 'mean':
succeeded = tf.reduce_mean(model_loss) > kwargs['success_distance']
if succeeded:
if kwargs['verbose']:
print('Attack succeeded with c = {:.4f}'.format(current_c))
return x_plus_delta
# If we made it here, we have to increase the constant and try again
current_c = current_c * 2.0
if kwargs['verbose']:
print('Attack failed. Returning None.')
# Return None in the case of failure
return None
|
[
"psturm@cs.washington.edu"
] |
psturm@cs.washington.edu
|
7b11a37746ad28f3e18303de213f4beb2bbb4404
|
315450354c6ddeda9269ffa4c96750783963d629
|
/CMSSW_7_0_4/src/SimTotem/RPTimingDetectorsDigiProducer/python/BeamMisalignmentFinder.py
|
3ff7d944d97f722285c3413832867036093dcd54
|
[] |
no_license
|
elizamelo/CMSTOTEMSim
|
e5928d49edb32cbfeae0aedfcf7bd3131211627e
|
b415e0ff0dad101be5e5de1def59c5894d7ca3e8
|
refs/heads/master
| 2021-05-01T01:31:38.139992
| 2017-09-12T17:07:12
| 2017-09-12T17:07:12
| 76,041,270
| 0
| 2
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 6,414
|
py
|
import ROOT
import os
import argparse
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from scipy import exp
parser = argparse.ArgumentParser(description='Finds beam misaligned between given template and misaligned ntuple')
parser.add_argument('template_file', metavar='template_file', type=str, nargs=1,
help='File containing ntuple used as template to find misaligned')
parser.add_argument('misaligned_file', metavar='misaligned_file', type=str, nargs=1,
help='File containing misaligned ntuple')
args = parser.parse_args()
ROOT.gROOT.ProcessLine('.include ' + os.environ['CMSSW_BASE'] + '/src')
ROOT.gROOT.ProcessLine(
'.L ' + os.environ['CMSSW_BASE'] + '/src/TotemAnalysis/TotemNtuplizer/interface/RPTimingDetectorsNtuplizerHit.h+g')
tree_name = 'TotemNtuple'
hit_source_types = ["reco", "filtered", "tracking_pot_210_far", "tracking_pot_220_far"]
ids = {
"reco": ["%03d" % id for id in [20, 21, 120, 121]]
}
ids["filtered"] = ids["reco"]
ids["tracking_pot_220_far"] = ids["reco"]
ids["tracking_pot_210_far"] = ids["reco"]
tracking_pot_maps = {
"tracking_pot_220_far": {
"020": "24",
"021": "25",
"120": "124",
"121": "125"
},
"tracking_pot_210_far": {
"020": "4",
"021": "5",
"120": "104",
"121": "105"
}
}
def get_branch_name(detector_id, type):
if type == "geant":
return 'rp_timing_detector_%s_hits' % detector_id
elif type == "reco":
return 'rp_timing_detector_%s_reco_hits' % detector_id
elif type == "filtered":
return 'rp_timing_detector_%s_filtered_hits' % detector_id
elif type == "tracking_pot_220_far":
return 'rp_timing_detector_%s_tracking_pot_%03.d' % (detector_id, int(tracking_pot_maps[type][detector_id]))
elif type == "tracking_pot_210_far":
return 'rp_timing_detector_%s_tracking_pot_%03.d' % (detector_id, int(tracking_pot_maps[type][detector_id]))
def load_ntuple(file_path):
tree_path = '/'.join([file_path, tree_name])
tchain = ROOT.TChain('TotemNtuple', '')
tchain.Add(tree_path)
return tchain
def gauss(x, a, x0, sigma):
return a*exp(-(x-x0)**2/(2*sigma**2))
def cut_zero_bins(histogram, bins):
first = histogram.index(next(x for x in histogram if x != 0))
last = (len(histogram) - 1) - histogram[::-1].index(
next(x for x in histogram[::-1] if x != 0))
hist_x = bins[first:last + 1]
hist_y = histogram[first:last + 1]
return hist_x, hist_y
def fit_gauss(x, y):
gauss_params, pcov = curve_fit(gauss, x, y, p0=[1., 0., 1.])
return gauss_params, np.sqrt(np.diag(pcov))
def find_misalignment(template_data, misaligned_data):
sum = 0.0
number = 0.0
template_error = 0.0
misaligned_error = 0.0
for bin_width in list(np.arange(0.1, 1.1, 0.1))[::-1]:
try:
histogram_bins = np.arange(-20, 20, bin_width)
template_histogram = list(np.histogram(template_data, bins=histogram_bins)[0])
misaligned_histogram = list(np.histogram(misaligned_data, bins=histogram_bins)[0])
template_x, template_y = cut_zero_bins(template_histogram, histogram_bins)
misaligned_x, misaligned_y = cut_zero_bins(misaligned_histogram, histogram_bins)
template_gauss_params, template_standard_deviation_error = fit_gauss(template_x, template_y)
misaligned_gauss_params, misaligned_standard_deviation_error = fit_gauss(misaligned_x, misaligned_y)
template_error += template_standard_deviation_error[1]
misaligned_error += misaligned_standard_deviation_error[1]
template_x0 = template_gauss_params[1]
misaligned_x0 = misaligned_gauss_params[1]
# plt.plot(misaligned_x, misaligned_y, 'b+:', label='data')
# plt.plot(misaligned_x, gauss(misaligned_x, *misaligned_gauss_params), 'ro:', label='fit')
# plt.legend()
# plt.savefig("foo.png")
sum += (misaligned_x0 - template_x0)
number += 1
except RuntimeError:
# print "result not found for %.2f bins width" % bin_width
pass
if number > 0:
return sum/number, template_error/number, misaligned_error/number
raise Exception('Cannot find misalignment')
if __name__ == "__main__":
template_file_name = args.template_file[0]
misaligned_file_name = args.misaligned_file[0]
template_ntuple = load_ntuple(template_file_name)
misaligned_ntuple = load_ntuple(misaligned_file_name)
# check sizes
if template_ntuple.GetEntries() != misaligned_ntuple.GetEntries():
print "Error, all sources must have te same number of events"
exit(-1)
sources_ntuples_types = ["template", "misaligned"]
hits_histograms = {}
for ntuple_type in sources_ntuples_types:
hits_histograms[ntuple_type] = {}
for hit_type in hit_source_types:
hits_histograms[ntuple_type][hit_type] = {}
for id in ids[hit_type]:
hits_histograms[ntuple_type][hit_type][id] = []
for source_name, source_ntuple in zip(sources_ntuples_types, [template_ntuple, misaligned_ntuple]):
for event in source_ntuple:
for type in hit_source_types:
for id in ids[type]:
for hits_vector in getattr(event, get_branch_name(id, type)):
if type in ["reco", "filtered"]:
hits_histograms[source_name][type][id].append(hits_vector.position.x)
elif type in ["tracking_pot_210_far", "tracking_pot_220_far"]:
hits_histograms[source_name][type][id].append(hits_vector.x)
sum = 0.0
number = 0.0
print "Calculated misalignment"
for type in hit_source_types:
for id in ids[type]:
result, template_error, misaligned_error = \
find_misalignment(hits_histograms["template"][type][id], hits_histograms["misaligned"][type][id])
sum += result
number += 1
print '%s %.2fmm; standard deviation error: template: %.2f misaligned: %.2f' % (get_branch_name(id, type), result,
template_error, misaligned_error)
print 'Average %.2fmm' % (sum/number)
|
[
"eliza@cern.ch"
] |
eliza@cern.ch
|
dece0de38d388908615b7dfa117a5a0a64cc883f
|
fe40fb53bdeb3d693174a57fe336503e92fe299b
|
/eheritage/utils.py
|
f8dbc0756aecfe7426966fb4198086045afbacea
|
[
"BSD-2-Clause"
] |
permissive
|
uq-eresearch/eheritage
|
8c8d096d43888e6e41fbbacdf55f2c6808bace27
|
e4a2f01c56d438d8b3f4de63d50d979a8105d652
|
refs/heads/master
| 2022-07-18T19:21:53.224175
| 2016-08-05T02:40:08
| 2016-08-05T02:40:08
| 18,045,275
| 0
| 0
|
BSD-3-Clause
| 2022-07-06T19:49:44
| 2014-03-23T22:33:56
|
HTML
|
UTF-8
|
Python
| false
| false
| 281
|
py
|
from flask.json import JSONEncoder
class IterableAwareEncoder(JSONEncoder):
def default(self, o):
try:
iterable = iter(o)
except TypeError:
pass
else:
return list(iterable)
return JSONEncoder.default(self, o)
|
[
"damien@omad.net"
] |
damien@omad.net
|
d79cce936c0204d7a981d5be8ec0003d8e75651e
|
84dc366925e685fb36ad06ccda4678ee0e0e6f6c
|
/CModule_Pytorch/utils/utils.py
|
bd8c4dce524f98ffb38a73116b3e6a138697d6c5
|
[] |
no_license
|
thanhpt55/Efficientnet-Pytorch
|
def9ea6dd6726034a6f514b8a7729077767b7977
|
40648b9d8ed5ea4d9c5ecbb73eead24652fc23c2
|
refs/heads/master
| 2022-12-21T20:41:22.919313
| 2020-09-18T03:32:58
| 2020-09-18T03:32:58
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 12,993
|
py
|
from torchvision import transforms
import sys
import os
import torch.nn as nn
import torch.nn.functional as F
import torch
import numpy as np
import skimage
from prettytable import PrettyTable
from gpuinfo import GPUInfo
import cv2
import json
def set_GPU(num_of_GPUs):
current_memory_gpu = GPUInfo.gpu_usage()[1]
list_available_gpu = np.where(np.array(current_memory_gpu) < 1500)[0].astype('str').tolist()
current_available_gpu = ",".join(list_available_gpu)
if len(list_available_gpu) < num_of_GPUs:
print("==============Warning==============")
print("Your process had been terminated")
print("Please decrease number of gpus you using")
print(f"number of Devices available:\t{len(list_available_gpu)} gpu(s)")
print(f"number of Device will use:\t{num_of_GPUs} gpu(s)")
sys.exit()
elif len(list_available_gpu) > num_of_GPUs:
redundant_gpu = len(list_available_gpu) - num_of_GPUs
list_available_gpu = list_available_gpu[:redundant_gpu]
current_available_gpu = ",".join(list_available_gpu)
print("[DEBUG]***********************************************")
print(f"[DEBUG]You are using GPU(s): {current_available_gpu}")
print("[DEBUG]***********************************************")
os.environ["CUDA_VISIBLE_DEVICES"] = current_available_gpu
else:
print("[DEBUG]***********************************************")
print(f"[DEBUG]You are using GPU(s): {current_available_gpu}")
print("[DEBUG]***********************************************")
os.environ["CUDA_VISIBLE_DEVICES"] = current_available_gpu
def preprocess_input(image, advprop=False):
if advprop:
normalize = transforms.Lambda(lambda img: img * 2.0 - 1.0)
else:
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\
std=[0.229, 0.224, 0.225])
preprocess_image = transforms.Compose([transforms.ToTensor(), normalize])(image)
return preprocess_image
def to_onehot(labels, num_of_classes):
if type(labels) is list:
labels = [int(label) for label in labels]
arr = np.array(labels, dtype=np.int)
onehot = np.zeros((arr.size, num_of_classes))
onehot[np.arange(arr.size), arr] = 1
else:
onehot = np.zeros((num_of_classes,), dtype=np.int)
onehot[int(labels)] = 1
return onehot
def multi_threshold(Y, thresholds):
if Y.shape[-1] != len(thresholds):
raise ValueError('Mismatching thresholds and output classes')
thresholds = np.array(thresholds)
thresholds = thresholds.reshape((1, thresholds.shape[0]))
keep = Y > thresholds
score = keep * Y
class_id = np.argmax(score, axis=-1)
class_score = np.max(score, axis=-1)
if class_score == 0:
return None
return class_id, class_score
def load_and_crop(image_path, input_size=0, custom_size=None):
""" Load image and return image with specific crop size
This function will crop corresponding to json file and will resize respectively input_size
Input:
image_path : Ex:Dataset/Train/img01.bmp
input_size : any specific size
Output:
image after crop and class gt
"""
image = cv2.imread(image_path)
print(image_path)
json_path = image_path + ".json"
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
size_image = image.shape
try :
with open(json_path, encoding='utf-8') as json_file:
json_data = json.load(json_file)
box = json_data['box']
center_x = box['centerX'][0]
center_y = box['centerY'][0]
widthBox = box['widthBox'][0]
heightBox = box['heightBox'][0]
class_gt = json_data['classId'][0]
except:
print(f"Can't find or missing some fields: {json_path}")
# Crop center image if no json found
center_x = custom_size[0]
center_y = custom_size[1]
widthBox = 0
heightBox = 0
class_gt = "Empty"
new_w = max(widthBox, input_size)
new_h = max(heightBox, input_size)
left, right = center_x - new_w / 2, center_x + new_w / 2
top, bottom = center_y - new_h / 2, center_y + new_h / 2
left, top = round(max(0, left)), round(max(0, top))
right, bottom = round(min(size_image[1] - 0, right)), round(min(size_image[0] - 0, bottom))
cropped_image = image[int(top):int(bottom), int(left):int(right)]
# if input_size > new_w:
# changed_image = cv2.resize(cropped_image,(input_size, input_size))
# else:
# changed_image = cropped_image
return cropped_image, class_gt
def metadata_count(input_dir,classes_name_list, label_list, show_table):
Table = PrettyTable()
print(f"[DEBUG] : {input_dir}")
# print(classes_name_list)
# print(label_list)
Table.field_names = ['Defect', 'Number of images']
unique_label ,count_list = np.unique(label_list, return_counts=True)
# print(count_list)
for i in range(len(classes_name_list)):
for j in range(len(unique_label)):
if classes_name_list[i] == unique_label[j] :
Table.add_row([classes_name_list[i], count_list[j]])
if show_table :
print(f"[DEBUG] :\n{Table}")
return classes_name_list, label_list
class FocalLoss(nn.Module):
# Took from : https://discuss.pytorch.org/t/is-this-a-correct-implementation-for-focal-loss-in-pytorch/43327/8
# Addition resource : https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65938
# TODO: clean up FocalLoss class
def __init__(self, class_weight=1., gamma=2., logits = False, reduction='mean'):
super(FocalLoss, self).__init__()
self.class_weight = class_weight
self.gamma = gamma
self.logits = logits
self.reduction = reduction
def forward(self, inputs, targets):
# if self.logits:
# BCE_loss = F.binary_cross_entropy_with_logits(inputs, targets, reduce=False)
# else:
# BCE_loss = F.binary_cross_entropy(inputs, targets, reduce=False)
# pt = torch.exp(-BCE_loss)
# F_loss = self.class_weight * (1 - pt)**self.gamma * BCE_loss
log_prob = F.log_softmax(inputs, dim=-1)
prob = torch.exp(log_prob)
return F.nll_loss(
((1 - prob) ** self.gamma) * log_prob,
targets,
weight = self.class_weight,
reduction = self.reduction
)
# TODO: inspect resize_image more carefully
def resize_image(image, min_dim=None, max_dim=None, min_scale=None, mode="square"):
"""Resizes an image keeping the aspect ratio unchanged.
min_dim: if provided, resizes the image such that it's smaller
dimension == min_dim
max_dim: if provided, ensures that the image longest side doesn't
exceed this value.
min_scale: if provided, ensure that the image is scaled up by at least
this percent even if min_dim doesn't require it.
mode: Resizing mode.
none: No resizing. Return the image unchanged.
square: Resize and pad with zeros to get a square image
of size [max_dim, max_dim].
pad64: Pads width and height with zeros to make them multiples of 64.
If min_dim or min_scale are provided, it scales the image up
before padding. max_dim is ignored in this mode.
The multiple of 64 is needed to ensure smooth scaling of feature
maps up and down the 6 levels of the FPN pyramid (2**6=64).
crop: Picks random crops from the image. First, scales the image based
on min_dim and min_scale, then picks a random crop of
size min_dim x min_dim. Can be used in training only.
max_dim is not used in this mode.
Returns:
image: the resized image
window: (y1, x1, y2, x2). If max_dim is provided, padding might
be inserted in the returned image. If so, this window is the
coordinates of the image part of the full image (excluding
the padding). The x2, y2 pixels are not included.
scale: The scale factor used to resize the image
padding: Padding added to the image [(top, bottom), (left, right), (0, 0)]
"""
# Keep track of image dtype and return results in the same dtype
import cv2
image_dtype = image.dtype
# Default window (y1, x1, y2, x2) and default scale == 1.
h, w = image.shape[:2]
window = (0, 0, h, w)
scale = 1
padding = [(0, 0), (0, 0), (0, 0)]
crop = None
if mode == "none":
return image, window, scale, padding, crop
# Scale?
if min_dim:
# Scale up but not down
scale = max(1, min_dim / min(h, w))
if min_scale and scale < min_scale:
scale = min_scale
# Does it exceed max dim?
if max_dim and mode == "square":
image_max = max(h, w)
if round(image_max * scale) > max_dim:
scale = max_dim / image_max
# Resize image using bilinear interpolation
if scale != 1:
# image = cv2.resize(image, (round(h*scale), round(w*scale)), interpolation=cv2.INTER_LINEAR)
image = skimage.transform.resize(
image, (round(h * scale), round(w * scale)),
order=1, mode="constant", preserve_range=True)
# Need padding or cropping?
if mode == "square":
# Get new height and width
h, w = image.shape[:2]
top_pad = (max_dim - h) // 2
bottom_pad = max_dim - h - top_pad
left_pad = (max_dim - w) // 2
right_pad = max_dim - w - left_pad
padding = [(top_pad, bottom_pad), (left_pad, right_pad), (0, 0)]
image = np.pad(image, padding, mode='constant', constant_values=0)
window = (top_pad, left_pad, h + top_pad, w + left_pad)
elif mode == "pad64":
h, w = image.shape[:2]
# Both sides must be divisible by 64
assert min_dim % 64 == 0, "Minimum dimension must be a multiple of 64"
# Height
if h % 64 > 0:
max_h = h - (h % 64) + 64
top_pad = (max_h - h) // 2
bottom_pad = max_h - h - top_pad
else:
top_pad = bottom_pad = 0
# Width
if w % 64 > 0:
max_w = w - (w % 64) + 64
left_pad = (max_w - w) // 2
right_pad = max_w - w - left_pad
else:
left_pad = right_pad = 0
padding = [(top_pad, bottom_pad), (left_pad, right_pad), (0, 0)]
image = np.pad(image, padding, mode='constant', constant_values=0)
window = (top_pad, left_pad, h + top_pad, w + left_pad)
elif mode == "crop":
# Pick a random crop
h, w = image.shape[:2]
y = random.randint(0, (h - min_dim))
x = random.randint(0, (w - min_dim))
crop = (y, x, min_dim, min_dim)
image = image[y:y + min_dim, x:x + min_dim]
window = (0, 0, min_dim, min_dim)
else:
raise Exception("Mode {} not supported".format(mode))
return image.astype(image_dtype), window, scale, padding, crop
class CustomDataParallel(nn.DataParallel):
"""
force splitting data to all gpus instead of sending all data to cuda:0 and then moving around.
"""
def __init__(self, module, num_gpus):
super().__init__(module)
self.num_gpus = num_gpus
def scatter(self, inputs, kwargs, device_ids):
# More like scatter and data prep at the same time. The point is we prep the data in such a way
# that no scatter is necessary, and there's no need to shuffle stuff around different GPUs.
devices = ['cuda:' + str(x) for x in range(self.num_gpus)]
splits = inputs[0].shape[0] // self.num_gpus
if splits == 0:
raise Exception('Batchsize must be greater than num_gpus.')
return [(inputs[0][splits * device_idx: splits * (device_idx + 1)].to(f'cuda:{device_idx}', non_blocking=True))\
for device_idx in range(len(devices))], [kwargs] * len(devices)
def patch_replication_callback(data_parallel):
"""
Monkey-patch an existing `DataParallel` object. Add the replication callback.
Useful when you have customized `DataParallel` implementation.
Examples:
> sync_bn = SynchronizedBatchNorm1d(10, eps=1e-5, affine=False)
> sync_bn = DataParallel(sync_bn, device_ids=[0, 1])
> patch_replication_callback(sync_bn)
# this is equivalent to
> sync_bn = SynchronizedBatchNorm1d(10, eps=1e-5, affine=False)
> sync_bn = DataParallelWithCallback(sync_bn, device_ids=[0, 1])
"""
assert isinstance(data_parallel, DataParallel)
old_replicate = data_parallel.replicate
@functools.wraps(old_replicate)
def new_replicate(module, device_ids):
modules = old_replicate(module, device_ids)
execute_replication_callbacks(modules)
return modules
data_parallel.replicate = new_replicate
|
[
"turing@emageai.com"
] |
turing@emageai.com
|
22274fc64978d6fbf2abfb1060b193c21cbe7bf9
|
14bfd073b8ddb556acdc2fee88f88c0b30d3a745
|
/store/migrations/0002_variation.py
|
77690a2c7ab7caca20c48db8444cad87afdd5e80
|
[] |
no_license
|
thilanse/greatkart-django
|
e29c45244e9e6c7f25c0c3de4642ecfbe86f2d31
|
44c2d6cd476f700e75104605c142b7ea3f75b571
|
refs/heads/master
| 2023-05-31T12:35:13.613769
| 2021-06-20T06:31:11
| 2021-06-20T06:31:11
| 372,538,602
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 918
|
py
|
# Generated by Django 3.1 on 2021-06-06 07:32
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('store', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Variation',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('variation_category', models.CharField(choices=[('color', 'color'), ('size', 'size')], max_length=100)),
('variation_value', models.CharField(max_length=100)),
('is_active', models.BooleanField(default=True)),
('created_date', models.DateTimeField(auto_now=True)),
('product', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='store.product')),
],
),
]
|
[
"thilansenanayake@gmail.com"
] |
thilansenanayake@gmail.com
|
c75f937366c08e5b63af4b9e6aefd59a0a5c040f
|
25621da01d7193f6ae847953937b18c095d32258
|
/plugins/operators/load_fact.py
|
ebf85cdd6cf797b3b9308c21d73a2e48374e61d4
|
[] |
no_license
|
fpcarneiro/data-pipelines-with-airflow
|
95de37b231a1c95414661db726847616051e995d
|
e477930e2817ad4d41f09148e8dbb975232b4434
|
refs/heads/master
| 2020-07-24T10:57:58.283392
| 2019-09-17T18:07:38
| 2019-09-17T18:07:38
| 207,901,219
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,143
|
py
|
from airflow.hooks.postgres_hook import PostgresHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults
class LoadFactOperator(BaseOperator):
ui_color = '#F98866'
@apply_defaults
def __init__(self,
# Define your operators params (with defaults) here
# Example:
# conn_id = your-connection-name
redshift_conn_id,
table_to,
query,
*args, **kwargs):
super(LoadFactOperator, self).__init__(*args, **kwargs)
self.redshift_conn_id = redshift_conn_id
self.table = table_to
self.query = query
self.autocommit = True
def execute(self, context):
self.log.info(f'Initializing INSERT into {self.table} table...')
self.hook = PostgresHook(postgres_conn_id=self.redshift_conn_id)
insert_sql = f"""
INSERT INTO {self.table}
{self.query};
COMMIT;
"""
self.hook.run(insert_sql, self.autocommit)
self.log.info(f"INSERT into {self.table} command complete!")
|
[
"fpcar@yahoo.com.br"
] |
fpcar@yahoo.com.br
|
a40004ba548e520cede3f28efbf8c20e012e0185
|
373cd41477438cc8826cd2a2f8689be84f486339
|
/msticpy/config/ce_data_providers.py
|
461dd3a6013e76b92a7875acbbc937f2d5327b61
|
[
"LicenseRef-scancode-generic-cla",
"LGPL-3.0-only",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"ISC",
"LGPL-2.0-or-later",
"PSF-2.0",
"Apache-2.0",
"BSD-2-Clause",
"LGPL-2.1-only",
"Unlicense",
"Python-2.0",
"LicenseRef-scancode-python-cwi",
"MIT",
"LGPL-2.1-or-later",
"GPL-2.0-or-later",
"HPND",
"ODbL-1.0",
"GPL-1.0-or-later",
"MPL-2.0"
] |
permissive
|
RiskIQ/msticpy
|
cd42d601144299ec43631554076cc52cbb42dc98
|
44b1a390510f9be2772ec62cb95d0fc67dfc234b
|
refs/heads/master
| 2023-08-27T00:11:30.098917
| 2021-06-17T22:54:29
| 2021-06-17T22:54:29
| 374,787,165
| 1
| 0
|
MIT
| 2021-09-16T19:05:43
| 2021-06-07T20:05:09
|
Python
|
UTF-8
|
Python
| false
| false
| 1,049
|
py
|
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""Data Providers Component Edit."""
from .._version import VERSION
from .ce_provider_base import CEProviders, HELP_URIS
__version__ = VERSION
__author__ = "Ian Hellen"
# pylint: disable=too-many-ancestors, duplicate-code
class CEDataProviders(CEProviders):
"""Data providers edit component."""
_DESCRIPTION = "Settings for Data Providers"
_COMP_PATH = "DataProviders"
# _HELP_TEXT inherited from base
_HELP_URI = {
"Data Providers": (
"https://msticpy.readthedocs.io/en/latest/" + "DataAcquisition.html"
),
**HELP_URIS,
}
_COMPONENT_HELP = """
<p><b>LocalData provider <i>data_paths</i></b>
Enter one or more data paths, separated by new lines
</p>
"""
|
[
"noreply@github.com"
] |
RiskIQ.noreply@github.com
|
367cdaa2588a8d236c60d962af442c3a618499d2
|
aecaa97a62610a8821c6b9991eb2a9e6af056922
|
/backend/wallet/transaction.py
|
23985990776c99e5ab1e38bc72dc35a1c15e4248
|
[] |
no_license
|
shanni12/Blockchain
|
b720385113a2556ac25545c15b870afcac922c2c
|
331faaab253c2e8baf040068931a60ac23224eec
|
refs/heads/master
| 2022-11-25T07:53:32.200270
| 2020-07-30T17:34:43
| 2020-07-30T17:34:43
| 283,831,388
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,689
|
py
|
import uuid
import time
from backend.wallet.wallet import Wallet
from backend.config import MINING_REWARD,MINING_REWARD_INPUT
class Transaction:
def __init__(self,sender_wallet=None,recipient=None,amount=None,id=None,output=None,input=None):
self.id=id or str(uuid.uuid4())[0:8]
self.output=output or self.create_output(
sender_wallet,
recipient,
amount
)
self.input=input or self.create_input(sender_wallet,self.output)
def create_output(self,sender_wallet,recipient,amount):
if amount>sender_wallet.balance:
raise Exception('Amount exceeds balance')
output={
}
output[recipient]=amount
output[sender_wallet.address]=sender_wallet.balance-amount
return output
def create_input(self,sender_wallet,output):
return {
'timestamp':time.time_ns(),
'amount':sender_wallet.balance,
'address':sender_wallet.address,
'public_key':sender_wallet.public_key,
'signature':sender_wallet.sign(output)
}
def update(self,sender_wallet,recipient,amount):
if amount>self.output[sender_wallet.address]:
raise Exception('Amount exceeds balance')
if recipient in self.output:
self.output[recipient]=self.output[recipient]+amount
else:
self.output[recipient]=amount
self.output[sender_wallet.address]=self.output[sender_wallet.address]-amount
self.input=self.create_input(sender_wallet,self.output)
def to_json(self):
return self.__dict__
@staticmethod
def from_json(transaction_json):
return Transaction(**transaction_json
)
@staticmethod
def is_valid_transaction(transaction):
if transaction.input==MINING_REWARD_INPUT:
if list(transaction.output.values())!=[MINING_REWARD]:
raise Exception('Invalid mining reward')
return
output_total=sum(transaction.output.values())
if transaction.input['amount']!=output_total:
raise Exception('Invalid transaction output values')
if not Wallet.verify(transaction.input['public_key'],transaction.output,transaction.input['signature']):
raise Exception('Invalid signature')
@staticmethod
def reward_transaction(miner_wallet):
output={}
output[miner_wallet.address]=MINING_REWARD
return Transaction(input=MINING_REWARD_INPUT,output=output)
def main():
transaction=Transaction(Wallet(),'recipient',15)
print(f'transaction.__dict__:{transaction.__dict__}')
if __name__=='__main__':
main()
|
[
"sdshahanaj180@gmail.com"
] |
sdshahanaj180@gmail.com
|
03de0fc83a788151f867f5df447891d4ac6214e8
|
bc759393672f8e2bf40136691460713ea7ba2e97
|
/robocar/distance_sensor2.py
|
0d4faea2a8d84d1c264f7f0bfff1301bdf924ab3
|
[] |
no_license
|
gordongekko67/robocar
|
3c98a2f6f04fd9a8b3d9f12450fbfa446ded88db
|
7d6fbdc2ea57cbc46597458356aa499e40fdb7bd
|
refs/heads/master
| 2022-12-17T18:11:12.889197
| 2020-09-10T10:47:39
| 2020-09-10T10:47:39
| 294,380,202
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,694
|
py
|
#!/usr/bin/env python
# license removed for brevity
import rospy
from std_msgs.msg import String
import RPi.GPIO as GPIO
import time
# GPIO Mode (BOARD / BCM)
GPIO.setmode(GPIO.BCM)
# set GPIO Pins
GPIO_TRIGGER = 20
GPIO_ECHO = 21
# set GPIO direction (IN / OUT)
GPIO.setup(GPIO_TRIGGER, GPIO.OUT)
GPIO.setup(GPIO_ECHO, GPIO.IN)
dist = 0.00
def talker(dist):
pub = rospy.Publisher('sensore_distanza2', String, queue_size=10)
rospy.init_node('distance_sensor2', anonymous=True)
rate = rospy.Rate(10) # 10hz
while not rospy.is_shutdown():
dist_str = "Distance 2 = " + str(dist)
rospy.loginfo(dist_str)
pub.publish(dist_str)
rate.sleep()
def distance():
# set Trigger to HIGH
GPIO.output(GPIO_TRIGGER, True)
# set Trigger after 0.01ms to LOW
time.sleep(0.00001)
GPIO.output(GPIO_TRIGGER, False)
StartTime = time.time()
StopTime = time.time()
# save StartTime
while GPIO.input(GPIO_ECHO) == 0:
StartTime = time.time()
# save time of arrival
while GPIO.input(GPIO_ECHO) == 1:
StopTime = time.time()
# time difference between start and arrival
TimeElapsed = StopTime - StartTime
# multiply with the sonic speed (34300 cm/s)
# and divide by 2, because there and back
distance = (TimeElapsed * 34300) / 2
return distance
if __name__ == '__main__':
try:
while True:
dist = distance()
print("Measured Distance 2 = %.1f cm" % dist)
talker(dist)
time.sleep(1)
# Reset by pressing CTRL + C
except KeyboardInterrupt:
print("Measurement stopped by User")
GPIO.cleanup()
|
[
"noreply@github.com"
] |
gordongekko67.noreply@github.com
|
4b73eae85e7d5060c6775ebd859a11f41185e949
|
ee489a6f449d4a26bb64510e8f1bc7f03f3b090a
|
/description.py
|
429a125e7397d3d647bc4269c5c8efdd5ff73633
|
[] |
no_license
|
eduardo-and/Normalize-Data
|
dd922d37cb39420514b771e18123c97799b60fb4
|
5e70466cb8521182f81481c1cad9588df0f04f99
|
refs/heads/master
| 2022-11-04T19:25:16.134886
| 2020-06-19T00:45:47
| 2020-06-19T00:45:47
| 273,363,098
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,675
|
py
|
import normalization as norm
import pandas as pd
import numpy as np
#
# The library performs data normalization using two techniques, "0 to 1" and score-z. The function accepts the following entries: list, DataFrame pandas,
# Series pandas, and numPy array. The format of the output is the same as the input. If the data contains a column (or a 1-dimension array) with string
# or boolean data, the function will not apply normalization.
#
#
# Functions:
# The library has two functions:
#
# 1# normalizeData(data,opt)
# This function performs the recognition of the data type and converts it to list,
# once this it passes the data to the auxiliary function "normalize".
# data: list,numPy array, DataFrame or Serie
# opt: 1(default) to normalize method "1 to 0", or
# 2 to normalize method score-z.
#
# return: the same tipe of input
#
#
# 2# normalize(list,opt)
# This is a auxiliar function, she performs the normalization in input exclusively of the list type.
# Exclusive use of the first function is recommended, as it is auxiliary to the above function
# data: list
# opt: 1(default) to normalize method "1 to 0", or
# 2 to normalize method score-z.
#
# return: list
dataList = [[121,26,23,64,142],[51451,21,515,132,12],['a1',15,'a2',15,'a3']]
dataFrame = pd.DataFrame(data = [[236,632,12,32],['a12',123,654,25],[12,65,122,36],[152,15,12,32]],columns= ["col1","col2","col3","col4"],index = ["a","b","c","d"])
dataSerie = pd.Series([2232,2256,2132,1265,3269,1541,3626,1561,6266,1515,1544,3226,2321,3218,6269,3266,6964,6641,6362,6366,1548,2352],name= "test1")
dataArray = np.array([[3211,612,3262,615,166,6216,62165,61265,6515,15585,61651,1566,6365,5641,623],[2326,632,664,1555,3269,2151,621,3155,6529,2161,6326,32623,1513,1515,3620]])
dataSet = pd.read_csv("vgsales.csv")
print("List:\n")
print(dataList)
print("\ndataFrame:\n")
print(dataFrame)
print("\nSeries:\n")
print(dataSerie)
print("\nArray\n")
print(dataArray)
print("\nDataSet:\n")
print(dataSet)
print("\n")
print("List normalized with method 1:\n")
print(norm.normalizeData(dataList,1))
print("\n")
print("Dataframe normalized with method 2:\n")
print(norm.normalizeData(dataFrame,2))
print("\n")
print("Serie normalized with method 1:\n")
print(norm.normalizeData(dataSerie,1))
print("\n")
print("Array normalized with method 2\n")
print(norm.normalizeData(dataArray,2))
print("\n")
print("Here we have a exemple dataset(Video Game Sales )\n:")
print(dataSet.head)
print("\n")
print("After normalization:")
dataSet = norm.normalizeData(dataSet,1)
print(dataSet.head)
|
[
"eduardo.ufg@hotmail.com"
] |
eduardo.ufg@hotmail.com
|
c4ceb5f6147352218943fd33a4665c65102248ef
|
68103b6b90dad4661d1663c9cbc051210aa6018f
|
/bookmanage3/book3/apps.py
|
08a1f4cd71c02b6b60d455e53bb46b9f4b1ad67f
|
[] |
no_license
|
tiantao-94/python01
|
c45aeca2a79c2c7dfa33a8a155a21c7333cda695
|
2404003a80db330543b327c7c1e0b5bb57addd6d
|
refs/heads/master
| 2022-12-21T07:52:37.142300
| 2020-09-27T15:05:10
| 2020-09-27T15:05:10
| 297,329,032
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 85
|
py
|
from django.apps import AppConfig
class Book3Config(AppConfig):
name = 'book3'
|
[
"1595328432@qq.com"
] |
1595328432@qq.com
|
2cce3230a7c808e0ea29c2bc2a6e9d058a134ed0
|
9872c2c3206f1f67c72eb530a6e6446dff952872
|
/PROCESS_GiftMaster.py
|
cf868d424d6584d1ad9265f927981a594fbfc16a
|
[] |
no_license
|
saikatsengupta89/TTS
|
4a7f15b46367cddbe62753caba14cf2d452d9cd9
|
8a38c908e1ae2e06b6e7f15be8cc3330d10a0ad1
|
refs/heads/main
| 2023-03-06T22:11:50.309639
| 2021-02-13T21:14:35
| 2021-02-13T21:14:35
| 326,279,964
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,372
|
py
|
# Databricks notebook source
import pandas as pd
import numpy as np
from pyspark.sql import types
from pyspark.sql.functions import col
pathGiftMaster="/mnt/adls/TTS/raw/monthly/gift_master/"
pathPRCGiftMaster='/mnt/adls/TTS/processed/references/ref_gift_master'
#reading the latest article master from the raw layer in adls
yearGM = str(max([int(i.name.replace('/','')) for i in dbutils.fs.ls(pathGiftMaster)]))
monthGM= str(max([int(i.name.replace('/','')) for i in dbutils.fs.ls(pathGiftMaster +"/" +str(yearGM))])).zfill(2)
#fileName=dbutils.fs.ls(pathGiftMaster+yearGM+"/"+monthGM+"/")[0].name
# COMMAND ----------
giftMasterSchema = types.StructType ([
types.StructField("gift_code",types.StringType()),
types.StructField("gift_name",types.StringType()),
types.StructField("gift_type_name",types.StringType()),
types.StructField("gift_type_code",types.StringType()),
types.StructField("gift_group",types.StringType()),
types.StructField("packing_per_case",types.IntegerType()),
types.StructField("UOM",types.StringType()),
types.StructField("remaining_sl_policy",types.IntegerType()),
types.StructField("color",types.StringType()),
types.StructField("size_h",types.DoubleType()),
types.StructField("size_w",types.DoubleType()),
types.StructField("size_l",types.DoubleType()),
types.StructField("grossweight_per_case_kg",types.DoubleType()),
types.StructField("netweight_per_pc_gm",types.DoubleType()),
types.StructField("dimension_per_case_h",types.DoubleType()),
types.StructField("dimension_per_case_w",types.DoubleType()),
types.StructField("description",types.StringType()),
types.StructField("enabled",types.StringType()),
types.StructField("vat",types.StringType())
])
giftMasterDF= (spark.read
.option('header',True)
.schema(giftMasterSchema)
.csv(pathGiftMaster+yearGM+"/"+monthGM+"/"))
#createDataFrame(df, giftMasterSchema)
#giftMasterDF.createOrReplaceTempView("gift_master")
# for j in range(1,12):
# monthGM_dummy= str(max([int(i.name.replace('/','')) for i in dbutils.fs.ls(pathGiftMaster +"/" +str(yearGM))])-j).zfill(2)
# (giftMasterDF
# .write.mode("overwrite")
# .parquet(pathPRCGiftMaster+"/"+yearGM+"/"+monthGM_dummy+"/"))
(giftMasterDF
.write.mode("overwrite")
.parquet(pathPRCGiftMaster+"/"+yearGM+"/"+monthGM+"/"))
# COMMAND ----------
|
[
"noreply@github.com"
] |
saikatsengupta89.noreply@github.com
|
53184abe0b9d0cc7e28ab1ab15066c700988bf39
|
22bcb68759d516eea70d18116cd434fcd0a9d842
|
/scrap/booksadda_scrap.py
|
f8cbcbef3fd0f32b0ab736622fb7afee1cde6327
|
[] |
no_license
|
lovesh/abhiabhi-web-scrapper
|
1f5da38c873fea74870d59f61c3c4f52b50f1886
|
b66fcadc56377276f625530bdf8e739a01cbe16b
|
refs/heads/master
| 2021-01-01T17:16:51.577914
| 2014-10-18T15:56:42
| 2014-10-18T15:56:42
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 8,758
|
py
|
import downloader
import dom
import urllib
import re
import time
import datetime
import simplejson as json
import pymongo
from collections import defaultdict
import util
siteurl='http://www.bookadda.com/'
books=[]
book_urls=set()
logfile=open('bookadda_log.txt','w')
dl=downloader.Downloader()
dl.addHeaders({'Origin':siteurl,'Referer':siteurl})
debug=True
DBName='abhiabhi'
temporary=pymongo.Connection().DBName.ba_temporary
temporary.create_index('url',unique=True)
url_pattern = re.compile('bookadda.com', re.I)
def getCategories():
doc=dom.DOM(url=siteurl)
category_path='//div[@id="body_container"]//ul[@class="left_menu"][1]/li/a'
categories=[[c[0],c[1]] for c in doc.getLinksWithXpath(category_path) if c[1] != 'http://www.bookadda.com/view-books/medical-books']
return categories
def getBookUrlsFromPage(html):
book_url_path='//ul[@class="results"]//div[@class="details"]//h4/a'
page_dom=dom.DOM(string=html)
links=set(l[1] for l in page_dom.getLinksWithXpath(book_url_path))
return links
def getBookUrlsOfSubcategory(subcategory_url):
subcategory_dom=dom.DOM(url=subcategory_url)
book_url_path='//ul[@class="results"]//div[@class="details"]//h4/a'
book_urls=set(l[1] for l in subcategory_dom.getLinksWithXpath(book_url_path))
result_count_path='//div[@id="search_container"]//div[@class="contentbox"]//div[@class="head"]'
count_node=subcategory_dom.getNodesWithXpath(result_count_path)
if count_node:
count_string=count_node[0].text_content()
print count_string
count=int(re.search('\d+ of (\d+) result',count_string).group(1))
subcat_col=pymongo.Connection().DBName.ba_subcats
subcat_col.update({'subcat_url':subcategory_url},{'$set':{'num_books':count}})
if count>20:
page_urls=set(subcategory_url+'?pager.offset='+str(x) for x in xrange(20,count,20))
dl.putUrls(page_urls)
subcategory_pages=dl.download()
for s in subcategory_pages:
status=subcategory_pages[s][0]
html=subcategory_pages[s][1]
if status > 199 and status < 400:
book_urls.update(getBookUrlsFromPage(html))
#print book_urls
return book_urls
def getAllBookUrls():
global book_urls
subcategory_path='//div[@id="left_container"]/ul[@class="left_menu"][1]/li/a'
cats=getCategories()
subcat_col=pymongo.Connection().DBName.ba_subcats
subcat_col.create_index('subcat_url',unique=True)
for cat in cats:
page=dom.DOM(url=cat[1])
subcats=page.getLinksWithXpath(subcategory_path)
for subcat in subcats:
try:
subcat_col.insert({'subcat':subcat[0].strip('\n\t\r '),'subcat_url':subcat[1],'cat':cat[0],'cat_url':cat[1],'status':0})
except:
pass
try:
subcat_col.insert({'subcat':'Medical','subcat_url':'http://www.bookadda.com/view-books/medical-books','cat':'Medical','status':0})
except:
pass
subcats=[{'cat':subcat['cat'],'subcat':subcat['subcat'],'subcat_url':subcat['subcat_url']} for subcat in subcat_col.find({'status':0})]
start=time.time()
for subcat in subcats:
print 'Getting book urls of subcategory %s\n\n'%subcat['subcat_url']
logfile.write('Getting book urls of subcategory %s\n\n'%subcat['subcat_url'])
logfile.flush()
urls=getBookUrlsOfSubcategory(subcat['subcat_url'])
for url in urls:
try:
temporary.insert({'url':url,'subcat_url':subcat['subcat_url'],'categories':[[subcat['cat'],subcat['subcat']],],'status':0})
except pymongo.errors.DuplicateKeyError:
temporary.update({'url':url},{'$push':{'categories':[subcat['cat'],subcat['subcat']]}})
print "done with subcategory %s"%subcat['subcat_url']
logfile.write("done with subcategory %s\n\n"%subcat['subcat_url'])
subcat_col.update({'subcat_url':subcat['subcat_url']},{'$set':{'status':1}})
finish=time.time()
print "All book urls(%d) fetched in %s\n\n"%(len(book_urls),str(finish-start))
logfile.write("All book urls fetched in %s\n\n"%str(finish-start))
logfile.flush()
return book_urls
def parseBookPage(url=None,string=None):
book={}
if url:
try:
doc=dom.DOM(url=url,utf8=True)
except:
return False
else:
try:
doc=dom.DOM(string=string,utf8=True)
except:
return False
addBox=doc.getNodesWithXpath('//a[@id="addBox"]')
url_path='//meta[@property="og:url"]'
book['url']=doc.getNodesWithXpath(url_path)[0].get('content').strip()
if debug:
print book['url']
if url_pattern.search(book['url']) is None:
return False
if addBox: #availability check
book['availability']=1
shipping_path='//span[@class="numofdys"]/strong'
shipping=doc.getNodesWithXpath(shipping_path)
if shipping:
shipping=re.search('(\d+)-(\d+)',shipping[0].text)
book['shipping']=[shipping.group(1),shipping.group(2)]
else:
book['availability']=0
name_path='//div[@class="prdcol2"]/h1'
name = doc.getNodesWithXpath(name_path)
if len(name) > 0:
book['name']=name[0].text_content().strip()
image_path='//meta[@property="og:image"]'
image=doc.getNodesWithXpath(image_path)
if image:
book['img_url']=image[0].text_content().strip()
desc_path='//div[@class="reviews-box-cont-inner"]'
desc=doc.getNodesWithXpath(desc_path)
if desc:
book['description']=desc[0].text_content().strip()
price_path='//span[@class="actlprc"]'
price=doc.getNodesWithXpath(price_path)
if len(price) > 0:
price = price[0].text.strip()
book['price']=int(re.search('(\d+)',price).group(1))
book['scraped_datetime']=datetime.datetime.now()
book['last_modified_datetime']=datetime.datetime.now()
product_history={}
if 'price' in book:
product_history['price']=book['price']
if 'shipping' in book:
product_history['shipping'] = book['shipping']
product_history['availability'] = book['availability']
product_history['datetime'] = book['last_modified_datetime']
book['product_history'] = [product_history,]
book['site']='bookadda'
tbody_path='//div[@class="grey_background"]/table/tbody'
if len(doc.getNodesWithXpath(tbody_path)) == 0:
tbody_path='//div[@class="grey_background"]/table'
data=doc.parseTBody(tbody_path)
if 'author' in data:
data['author']=data['author'].encode('utf8').split('\xc2\xa0')
util.replaceKey(data,'number of pages','num_pages')
util.replaceKey(data,'publishing date','pubdate')
util.replaceKey(data,'isbn-13','isbn13')
if 'isbn13' in data:
data['isbn13']=data['isbn13'].split(',')[0].replace('-','').strip()
util.replaceKey(data,'book','name')
book.update(data)
return book
def go():
global books
getAllBookUrls()
temporary=pymongo.Connection().DBName.ba_temporary
con=pymongo.Connection()
coll=con[DBName]['scraped_books']
count=1 #so that the following loop starts
total=0 #keeps a track of total downloaded books
start=time.time()
while count>0:
docs=temporary.find({'status':0}).limit(500)
count=docs.count()
urls=[]
processed={}
urls=[doc['url'] for doc in docs]
dl.putUrls(urls,30)
result=dl.download()
books=[]
for r in result:
status=str(result[r][0])
html=result[r][1]
if int(status) > 199 and int(status) < 400:
book=parseBookPage(string=html)
if book:
books.append(book)
if status in processed:
processed[status].append(r)
else:
processed[status]=[r,]
coll.insert(books)
total+=total+len(books)
for status in processed:
temporary.update({'url':{'$in':processed[status]}},{'$set':{'status':int(status)}},multi=True)
finish=time.time()
logfile.write("All books parsed in %s"%str(finish-start))
def prepareXMLFeed():
go()
root=dom.XMLNode('books')
start=time.time()
for book in books:
child=root.createChildNode('book')
child.createChildNodes(book)
f=open('booksadda.xml','w')
f.write(root.nodeToString())
f.close()
finish=time.time()
logfile.write("XML file created in %s"%str(finish-start))
if __name__ == '__main__':
go()
|
[
"lovesh.bond@gmail.com"
] |
lovesh.bond@gmail.com
|
be0b1ecda58d90e672c985713d33a45eff2bee10
|
0a2c84d6c7e0f65d98ebf8c899b5b357d60a4f84
|
/all_ticker_details.py
|
0c5944bf0fc9ca2131b3fb6813c53803b58db032
|
[] |
no_license
|
Xelanor/StockNinjaPython
|
6dcff3c2345d2516a45843b188f0b8660f4fe74d
|
8e01b11fcbd0dc4254b5bc18e2a1ad9469c17ede
|
refs/heads/master
| 2020-11-24T15:45:26.520563
| 2020-02-01T05:43:58
| 2020-02-01T05:43:58
| 228,224,085
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,349
|
py
|
from constants.tickers import tickers
import json
import utils
def fetch_all_stocks():
result = []
stock_names = ",".join(tickers)
stocks_data = utils.get_current_tickers_data(stock_names)
negative = 0
total = 0
for data_dict in stocks_data:
price = data_dict["regularMarketPrice"]
prevClose = data_dict["regularMarketPreviousClose"]
rate = utils.rateCalculator(price, prevClose)
negative += 1 if rate < 0 else 0
total += 1
try:
stock_name = data_dict["symbol"]
stock_dict = {
"stockName": stock_name,
"price": price,
"dayRange": data_dict["regularMarketDayRange"],
"rate": rate
}
result.append(stock_dict)
except:
pass
result.append(negative)
result.append(total)
return result
def result(event, context):
prices = fetch_all_stocks()
return {
'statusCode': 200,
'headers': {
"Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Headers": "Content-Type, authorization",
"Access-Control-Allow-Methods": "OPTIONS,POST,GET"
},
'body': json.dumps(prices)
}
if __name__ == '__main__':
output = result("", "")
print(output["body"])
|
[
"44201710+Xelanor@users.noreply.github.com"
] |
44201710+Xelanor@users.noreply.github.com
|
71fa92b615354dcd3f6006400b3a7a0539adb78f
|
cbb2be6194ef23dbedef9a69732b210b54c8f03b
|
/users/admin.py
|
6de27bc5d23f660edec618ac95a1581c5a3a16e3
|
[] |
no_license
|
cavblk/pub-net
|
28bd7e25e26ff61115dbd29a9d7e5add0fc7b458
|
4b2ff6eaae448028135102e7c11c3cb1c1456907
|
refs/heads/master
| 2023-04-20T13:27:39.145232
| 2021-05-10T12:32:51
| 2021-05-10T12:32:51
| 365,173,363
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,281
|
py
|
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
from django.utils.translation import gettext_lazy as _
from django.urls import path
from users.models import AuthUser
from users.forms import UserCreationForm
# Register your models here.
@admin.register(AuthUser)
class AuthUserAdmin(BaseUserAdmin):
ordering = ('email',)
list_display = ('email', 'first_name', 'last_name', 'is_staff', 'profile_avatar')
fieldsets = (
(None, {'fields': ('email',)}),
(_('Personal info'), {'fields': ('first_name', 'last_name')}),
(_('Permissions'), {
'fields': ('is_active', 'is_staff', 'is_superuser', 'groups', 'user_permissions'),
}),
(_('Important dates'), {'fields': ('last_login', 'date_joined')}),
)
add_fieldsets = (
(None, {
'classes': ('wide',),
'fields': ('first_name', 'last_name', 'email'),
}),
)
search_fields = ('first_name', 'last_name', 'email', 'profile__avatar')
add_form = UserCreationForm
def profile_avatar(self, instance):
return instance.profile.avatar
profile_avatar.short_description = 'Profile Avatar'
def get_urls(self):
return super(BaseUserAdmin, self).get_urls()
|
[
"mihai@academicmerit.com"
] |
mihai@academicmerit.com
|
ecffd0cb40db3a2541dd08f1f6cbc13ea53320ed
|
ed0dd577f03a804cdc274f6c7558fafaac574dff
|
/python/pyre/weaver/mills/CxxMill.py
|
d5307d0adaae8fcbb9fa32dd74b5c3f627978cec
|
[
"Apache-2.0"
] |
permissive
|
leandromoreira/vmaf
|
fd26e2859136126ecc8e9feeebe38a51d14db3de
|
a4cf599444701ea168f966162194f608b4e68697
|
refs/heads/master
| 2021-01-19T03:43:15.677322
| 2016-10-08T18:02:22
| 2016-10-08T18:02:22
| 70,248,500
| 3
| 0
| null | 2016-10-07T13:21:28
| 2016-10-07T13:21:27
| null |
UTF-8
|
Python
| false
| false
| 701
|
py
|
#!/usr/bin/env python
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# Michael A.G. Aivazis
# California Institute of Technology
# (C) 1998-2005 All Rights Reserved
#
# <LicenseText>
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
from pyre.weaver.components.LineMill import LineMill
class CxxMill(LineMill):
names = ["c++", "cxx"]
def __init__(self):
LineMill.__init__(self, "//", "// -*- C++ -*-")
return
# version
__id__ = "$Id: CxxMill.py,v 1.1.1.1 2006-11-27 00:10:09 aivazis Exp $"
# End of file
|
[
"zli@netflix.com"
] |
zli@netflix.com
|
d4adbe198d9a9e8a3154b16d3b046067822802d5
|
2836c3caf8ca332635640a27254a345afd449081
|
/iem/regain_hour_map.py
|
b88680e83d256a083176bb0d735984295da3bb65
|
[
"Apache-2.0",
"MIT"
] |
permissive
|
akrherz/DEV
|
27cf1bac978a0d6bbfba1851b90d2495a3bdcd66
|
3b1ef5841b25365d9b256467e774f35c28866961
|
refs/heads/main
| 2023-08-30T10:02:52.750739
| 2023-08-29T03:08:01
| 2023-08-29T03:08:01
| 65,409,757
| 2
| 0
|
MIT
| 2023-09-12T03:06:07
| 2016-08-10T19:16:28
|
Jupyter Notebook
|
UTF-8
|
Python
| false
| false
| 1,689
|
py
|
"""Plot the scam that is DST"""
import ephem
import mx.DateTime
import tqdm
from pyiem.plot import MapPlot
def compute_sunrise(lat, long):
arr = []
sun = ephem.Sun()
ames = ephem.Observer()
ames.lat = lat
ames.long = long
sts = mx.DateTime.DateTime(2018, 3, 10)
interval = mx.DateTime.RelativeDateTime(days=1)
now = sts
doy = []
returnD = 0
ames.date = now.strftime("%Y/%m/%d")
rise = mx.DateTime.strptime(
str(ames.next_rising(sun)), "%Y/%m/%d %H:%M:%S"
)
rise = rise.localtime()
delta = rise.hour * 60 + rise.minute
now += interval
while True:
ames.date = now.strftime("%Y/%m/%d")
rise2 = mx.DateTime.strptime(
str(ames.next_rising(sun)), "%Y/%m/%d %H:%M:%S"
)
rise2 = rise2.localtime()
delta2 = rise2.hour * 60 + rise2.minute
if delta2 < delta:
return (rise2 - rise).days
now += interval
return doy, arr, returnD
def main():
"""Go Main Go."""
lats = []
lons = []
vals = []
for lon in tqdm.tqdm(range(-130, -60, 2)):
for lat in range(20, 55, 1):
lats.append(lat)
lons.append(lon)
vals.append(compute_sunrise(str(lat), str(lon)))
m = MapPlot(
sector="conus",
title="Days to Recover Morning Hour after Spring Saving Time Change",
subtitle=(
"days until local time of sunrise is earlier "
"than on 10 March, local DST rules ignored for plot"
),
)
m.contourf(lons, lats, vals, range(27, 78, 3), units="days")
m.postprocess(filename="180313.png")
if __name__ == "__main__":
main()
|
[
"akrherz@iastate.edu"
] |
akrherz@iastate.edu
|
e2707cb27cb58cb71c2bbf62349e32ddf30f03e5
|
12c371e397a00af391b796ae592a54794afdf42d
|
/code/FEMDataExtraction/test/testlish.py
|
e59e4bf12f81fcda546fe4e8112decd5486aea97
|
[] |
no_license
|
zhaoweisonake/FFR_FlexibleBody
|
feefa5367c908c4ce98b43b6a8a652a9d939ecad
|
2a0554b5d0a0e1b0956892e1f8a335df194f45f7
|
refs/heads/master
| 2020-05-15T03:49:59.549201
| 2015-09-04T14:03:48
| 2015-09-04T14:03:48
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 451
|
py
|
with open('testRead.txt') as input_data:
# Skips text before the beginning of the interesting block:
for line in input_data:
if line.strip() == 'Start': # Or whatever test is needed
break
# Reads text until the end of the block:
for line in input_data: # This keeps reading the file
if line.strip() == 'End':
break
print line # Line is extracted (or block_of_lines.append(line), etc.)
|
[
"wangzhanrock@gmail.com"
] |
wangzhanrock@gmail.com
|
71b73dbd03f5e6c2ae9f74bb922c758bf2c94fd9
|
71de5c4d038a470ba80bd978303a2f4438d6b7c8
|
/PyPoll/main.py
|
267bd771f8fff1291489044373f2725db6275797
|
[] |
no_license
|
tardis123/python-challenge
|
463526c5b133cc9a81df5882cc50d2e3ca02c2fc
|
7f96d9b18cd0aefc9d7bdd14a4bd1cb40f7e48a7
|
refs/heads/master
| 2021-04-03T21:06:56.355730
| 2018-03-12T23:38:15
| 2018-03-12T23:38:15
| 124,706,288
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,728
|
py
|
# Dependencies
import os
import csv
#Ask which file should be analyzed (file must be in csv format)
input_file = input("Enter the name of the file you want to analyze (without extension, must be csv file) : ") + ".csv"
# Set file path (input file should be located on the same level as the folder raw_data)
csvpath = os.path.join('raw_data', input_file)
# Append file lines to list poll_data
poll_data = []
with open(csvpath, 'r', newline ='', encoding="utf-8") as csvFile:
csvReader = csv.reader(csvFile, delimiter=',')
next(csvReader, None) # skip file header
for row in csvReader:
poll_data.append(row)
# Calculate total number of votes
total_votes = int(len(poll_data))
#print(poll_data[3]) #grab 4th row in the csv file (header not included)
#print(poll_data[3][2]) #grab value in the 3th column for the 4th row (header not included)
# Append candidate name plus total votes per candidate to dictionary candidates
candidates = {}
for i in range(total_votes):
key = poll_data[i][2]
if key not in candidates:
candidates[key] = 1
else:
candidates[key] += 1
def winner():
top_vote = 0
winner = ""
for key, value in candidates.items():
if value > top_vote:
top_vote = value
winner = key
return winner
#Print output to terminal
print("Election Results")
print("-" * 25)
print("Total Votes: {}".format(total_votes))
print("-" * 25)
relative_votes = 0
for key, value in candidates.items():
relative_votes = "{:.2%}".format(float(value/total_votes))
print("{}: {} ({})".format(key, relative_votes, value))
print("-" * 25)
print("Winner: {}".format(winner()) )
print("-" * 25)
# Set variable for output file
output_file = os.path.join("election_results.csv")
# Print output to file
# 1) Ask what the output file should be named liked (must be csv format)
output_file = input("Enter the name for the output file (without extension): ") + ".csv"
# 2) set variable for output file
output_file = os.path.join(output_file)
# 3) Open the output file
with open(output_file, "w", newline="") as datafile:
writer = csv.writer(datafile)
# Write the header row
writer.writerow(["Election Results"])
writer.writerow(["-" * 25])
writer.writerow(["Total Votes: {}".format(total_votes)])
writer.writerow(["-" * 25])
relative_votes = 0
for key, value in candidates.items():
# Relative number of votes in two digits
relative_votes = "{:.2%}".format(float(value/total_votes))
writer.writerow(["{}: {} ({})".format(key, relative_votes, value)])
writer.writerow(["-" * 25])
writer.writerow(["Winner: {}".format(winner())])
writer.writerow(["-" * 25])
|
[
"renevenema@gmail.com"
] |
renevenema@gmail.com
|
a705dfd941c63c982c157e1239484d4cc9ee5a5c
|
2417cdceb80e884ebc997c00a4203202e1e4bfe6
|
/src/754.reach-a-number/754.reach-a-number.py
|
572f45835d3ac931f4194b8582087266fa8bc01a
|
[
"MIT"
] |
permissive
|
AnestLarry/LeetCodeAnswer
|
20a7aa78d1aaaa9b20a7149a72725889d0447017
|
f15d1f8435cf7b6c7746b42139225e5102a2e401
|
refs/heads/master
| 2023-06-23T07:20:44.839587
| 2023-06-15T14:47:46
| 2023-06-15T14:47:46
| 191,561,490
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,308
|
py
|
#
# @lc app=leetcode id=754 lang=python3
#
# [754] Reach a Number
# https://leetcode.com/problems/reach-a-number/discuss/410112/Python-Solution
# @lc code=start
# You are standing at position 0 on an infinite number line. There is a goal at position target.
# On each move, you can either go left or right. During the n-th move (starting from 1), you take n steps.
# Return the minimum number of steps required to reach the destination.
# Example 1:
# Input: target = 3
# Output: 2
# Explanation:
# On the first move we step from 0 to 1.
# On the second step we step from 1 to 3.
# Example 2:
# Input: target = 2
# Output: 3
# Explanation:
# On the first move we step from 0 to 1.
# On the second move we step from 1 to -1.
# On the third move we step from -1 to 2.
# Note:
# target will be a non-zero integer in the range [-10^9, 10^9].
class Solution:
def reachNumber(self, target: int) -> int:
# Accepted
# 73/73 cases passed (120 ms)
# Your runtime beats 32.81 % of python3 submissions
# Your memory usage beats 11.11 % of python3 submissions (13.7 MB)
res = 0
target = abs(target)
while target > 0:
res += 1
target -= res
if target % 2 != 0:
res += 1+res % 2
return res
# @lc code=end
|
[
"anest@66ws.cc"
] |
anest@66ws.cc
|
0099a17b3d889215f6691b3cf3cf8b91a101bab1
|
05b4fc99b193530db6609e1eca1226ad9205e839
|
/CalUsingifelse.py
|
1705d0b8811cdf4a2856a92765088c4224a003b9
|
[] |
no_license
|
hemanth1011/coding-dump
|
c5dc26ec684a911972765a8f88c4d19681285e31
|
91a6b5d2c455e1c0cce8be12eaa503b96abf2b35
|
refs/heads/master
| 2020-06-22T19:00:23.906974
| 2019-07-25T06:02:38
| 2019-07-25T06:02:38
| 197,781,716
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 612
|
py
|
# Note : there is no switch case in python. so, here im using if and if-else statements.
#---------------------------------------------------------------------------------------
a = input("Enter first number")
b = input("Enter second number")
op = input("Enter opertion from below \n+\n-\n*\n/\n")
if(op=="+"):
Result=float(a)+float(b)
if(op=="-"):
Result=float(a)-float(b)
if(op=="*"):
Result=float(a)*float(b)
if(op=="/"):
Result=float(a)/float(b)
if(op=="+" or op=="-" or op=="*" or op=="/"):
print("Result:",a,"+",b,"=",Result)
else:
print("Unidentified Operation...")
|
[
"hemanthmanikantabunga@gmail.com"
] |
hemanthmanikantabunga@gmail.com
|
5b55fd22321c6012af593f2b24bd9b3c94ac8bc7
|
7003c85d303f0f18558cff629acebeed8e0893e4
|
/Algo/Divide and Conquer/isMajority.py
|
14401d728c2d8a0463eb10adf44cca6a502886f3
|
[] |
no_license
|
hardik96bansal/Algorithm-DS-Practice
|
6e2e9b63df4487058483133a19534815a49c4b2e
|
eb2c0d0d21f4cd1fee00eaa2988d20da9c496dc1
|
refs/heads/master
| 2023-04-30T06:52:05.994755
| 2023-04-17T13:09:55
| 2023-04-17T13:09:55
| 241,435,628
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 668
|
py
|
def isMajority(arr,num):
firOcc = firstOccur(arr,num,0,len(arr),-1)
n = len(arr)
if(firOcc == -1 or firOcc>n//2):
return False
if(arr[firOcc+n//2]==num):
return True
else:
return False
def firstOccur(arr,num,l,r,i):
if(r>l):
mid = (l+r)//2
if(arr[mid] == num):
j = mid if (mid<i or i==-1) else i
return firstOccur(arr,num,l,mid,j)
elif(num<arr[mid]):
return firstOccur(arr,num,l,mid,i)
else:
return firstOccur(arr,num,mid+1,r,i)
return i
arr = [0,1,2,3,3,3,3,3,10]
#print(firstOccur(arr,11,0,len(arr),-1))
print(isMajority(arr,10))
|
[
"hardik96bansal@gmail.com"
] |
hardik96bansal@gmail.com
|
13c9e664f8305eab4364a967fcda8656ceb1630b
|
b41fd68840e7345066189d76a3ecdd7d7c00a67f
|
/food_tracker/food/views.py
|
53455d90e81e93d7cce666ea936343808ab8d9f0
|
[] |
no_license
|
AlexisAguiluz/food_tracker
|
34064635d0260bd4143d5f0338b25201b96c1efb
|
ab3024af7eaffaa3a30f13761893c9b3460dbf53
|
refs/heads/master
| 2020-09-21T21:59:24.618266
| 2019-11-30T02:13:54
| 2019-11-30T02:13:54
| 224,947,161
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,512
|
py
|
from django.shortcuts import render
from django.http import HttpResponse
from .models import Food, Meal
from django.http import HttpResponseRedirect
from django.urls import reverse_lazy
from .forms import MealForm
def index(request):
template = 'list.html'
meals = Meal.objects.all()
context = {
'meals': meals,
}
return render(request, template, context)
# return HttpResponse("Hello, world. You're at the index page.")
def add_meal(request):
template = "add_meal.html"
if request.method == "POST":
form = MealForm(request.POST)
if form.is_valid():
form.save()
return HttpResponseRedirect(reverse_lazy('food:index'))
else:
context = {
'meal_form': MealForm(),
}
return render(request, template, context)
def delete_meal(request, meal_id):
meal = Meal.objects.get(id=int(meal_id))
meal.delete()
return HttpResponseRedirect(reverse_lazy('food:index'))
def update_meal(request, meal_id):
template = "update_meal.html"
meal = Meal.objects.get(id=int(meal_id))
if request.method == "POST":
form = MealForm(request.POST, instance=meal)
if form.is_valid():
form.save()
return HttpResponseRedirect(reverse_lazy('food:index'))
else:
context = {
'meal_form': MealForm(instance=meal),
}
return render(request, template, context)
def view_meal(request, meal_id):
template = "view_meal.html"
meal= Meal.objects.get(id=int(meal_id))
context = {
'meal': meal,
}
return render(request, template, context)
|
[
"noreply@github.com"
] |
AlexisAguiluz.noreply@github.com
|
bc518a828d6081912b765f39a3b95bd87e6fbcf1
|
bc1c3b7386b80c8aa1ee9660606084aacf499e93
|
/Bronze II/2309.py
|
6046624080cc3e450a4191c11bcbc546e2e9ae02
|
[] |
no_license
|
Thesine/BOJ_Sine
|
ad93bcd47f622cb68ae794fbd70c3b73044c76aa
|
4bde63726c0f14e9dea30eeb5d262039509b9e8b
|
refs/heads/master
| 2022-11-05T01:22:55.674606
| 2020-07-15T07:14:49
| 2020-07-15T07:14:49
| 265,505,315
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 240
|
py
|
l = []
for i in range(9):
l.append(int(input()))
sum = 0
l.sort()
for i in l:
sum += i
for i in l:
if len(l)==7:
break
for j in l:
if i+j == sum-100:
l.remove(j)
l.remove(i)
break
for i in l:
print(i)
|
[
"noreply@github.com"
] |
Thesine.noreply@github.com
|
dd2f007d5531fe7a3a72581701ad253e6d6eb614
|
9815041feb5bd2a89e39d86e544ca44c2e17e318
|
/config/settings.py
|
fdd605a6aef832ee03fc0708d15aa8ca4282d1b3
|
[] |
no_license
|
raimbaev223/django-docker-postgres-template
|
5ecb62fdc57bb3af77815c3c4d1f03c98d0fdaf3
|
f97449cf90b87daed374576ba52e545fc1694be0
|
refs/heads/master
| 2023-04-03T05:22:38.668148
| 2021-04-05T10:47:52
| 2021-04-05T10:47:52
| 354,720,373
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,247
|
py
|
"""
Django settings for djangoforprofessionals_ch3 project.
Generated by 'django-admin startproject' using Django 3.1.7.
For more information on this file, see
https://docs.djangoproject.com/en/3.1/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.1/ref/settings/
"""
from pathlib import Path
# Build paths inside the project like this: BASE_DIR / 'subdir'.
BASE_DIR = Path(__file__).resolve().parent.parent
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'j)xol&2u_4%!32uegp@x)y*=hmn8!nlp4_1tfxq#zwu#0et$46'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'djangoforprofessionals_ch3.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [BASE_DIR / 'templates']
,
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'djangoforprofessionals_ch3.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.1/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.postgresql',
'NAME': 'postgres',
'USER': 'postgres',
'PASSWORD': 'postgres',
'HOST': 'db',
'PORT': 5432
}
}
# Password validation
# https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/3.1/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/3.1/howto/static-files/
STATIC_URL = '/static/'
|
[
"raimbaev.223@gmail.com"
] |
raimbaev.223@gmail.com
|
8539aa648cbcf6f39e0fe38345d487fbf450fffa
|
bb1118b2bf391af6671c55e68121e64795791411
|
/week2/asig2/pa2-autocorrect-v1/python/StupidBackoffLanguageModel.py
|
58980bce15b3805309d064eb0dcfda14e0b21bb6
|
[] |
no_license
|
jdcheesman/python-nlp
|
5dbe65252755d205f287a90ef6c08c545936393a
|
fac11bf5fac5323031e7e11b9609f31584412b99
|
refs/heads/master
| 2020-05-29T22:37:50.739462
| 2012-06-14T15:29:24
| 2012-06-14T15:29:24
| 3,726,555
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,116
|
py
|
import math
class StupidBackoffLanguageModel:
unigrams = dict()
bigrams = dict()
total_tokens = 0
total_vocab = 0
def __init__(self, corpus):
"""Initialize your data structures in the constructor."""
# TODO your code here
self.train(corpus)
def train(self, corpus):
""" Takes a corpus and trains your language model.
Compute any counts or other corpus statistics in this function.
"""
# TODO your code here
self.load_unigrams(corpus)
self.load_bigrams(corpus)
def load_unigrams(self, corpus):
"""Load the unigrams dictionary """
for sentence in corpus.corpus:
for datum in sentence.data: # iterate over datums in the sentence
m = datum.word # get the word
self.total_tokens += 1
val = 1
if m in self.unigrams:
val = self.unigrams[m] + 1
else:
self.total_vocab += 1
self.unigrams[m] = val
def load_bigrams(self, corpus):
"""Load the bigrams dictionary"""
last_word = ''
for sentence in corpus.corpus:
for datum in sentence.data: # iterate over datums in the sentence
m = datum.word # get the word
if last_word is not '':
val = 1
new_bigram = last_word + ' ' + m
if new_bigram in self.bigrams:
val = self.bigrams[new_bigram] + 1
self.bigrams[new_bigram] = val
last_word = m
def score(self, sentence):
""" Takes a list of strings as argument and returns the log-probability of the
sentence using your language model. Use whatever data you computed in train() here.
Steps 1) count(bigram)/count(unigram) if count(unigram) > 0
otherwise 2) 0.4 * Laplace unigram for known words
3) 0.4 * Laplace unigram fro unknown words
Laplace unigram is log(count(unigram) + 1) / V + N
"""
# TODO your code here
case3_probability = 0.4 * (1.0 / (self.total_tokens + self.total_vocab + 0.0))
result = 0.0
previous_word = ''
for m in sentence:
probability = case3_probability
cntUnigram = 0.0
cntBigram = 0.0
if previous_word is '':
if m in self.unigrams:
cntUnigram = self.unigrams[m]
probability = 0.4 * ((cntUnigram + 1.0) / (self.total_tokens + self.total_vocab + 0.0))
else:
current_bigram = previous_word + ' ' + m
if previous_word in self.unigrams and current_bigram in self.bigrams:
cntUnigram = self.unigrams[previous_word]
cntBigram = self.bigrams[current_bigram]
probability = (cntBigram+0.0) / (cntUnigram+0.0)
else:
if m in self.unigrams:
cntUnigram = self.unigrams[m]
probability = 0.4 * ((cntUnigram + 1.0) / (self.total_tokens + self.total_vocab + 0.0))
result = result + math.log(probability)
previous_word = m
#print result
return result
|
[
"jim.cheesman.work@gmail.com"
] |
jim.cheesman.work@gmail.com
|
a07324a9d67bfb019bf47a4e379d797eab6ed5f3
|
728f639b8d536348e200a6c6b8dfd3e70a781d85
|
/HTMLTestRunner测试报告&unittest/可以复用项目/webTest/comm/common.py
|
967c849ad0793853febfe741f742e28639cee19c
|
[] |
no_license
|
jingshiyue/my_dict_forPython
|
00adad2a1492b7ecff66a3de44793f17682aaea6
|
7a0da28d68eb130e62d196467d0ef0ee3d8ebf95
|
refs/heads/master
| 2023-04-05T18:29:36.707082
| 2023-03-30T10:30:13
| 2023-03-30T10:30:13
| 192,511,669
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 7,436
|
py
|
# -*- coding:utf-8 -*-
import os
import readConfig as readConfig
from xlrd import open_workbook
from xml.etree import ElementTree as ElementTree
from selenium import webdriver
from selenium.common.exceptions import NoSuchElementException
from comm.webDriver import MyDriver as Driver
import time
import comm.runSet as runSet
localReadConfig = readConfig.ReadConfig()
def open_browser():
"""
open browser by url
:return:
"""
browser = webdriver.Chrome()
# 绐楀彛鏈�ぇ鍖�
browser.maximize_window()
return browser
def close_browser(browser):
"""
close browser
:param browser:
:return:
"""
browser.close()
def open_url(name):
"""
open web page by url
:param name:
:return:
"""
url = localReadConfig.get_webServer(name)
browser = open_browser()
browser.get(url)
return browser
def get_xls(xls_name, sheet_name):
"""
:param xls_name: excel file name
:param sheet_name: sheet name
:return: sheet value
"""
web = runSet.get_web()
site = runSet.get_site()
cls = []
# get excel file path
xls_path = os.path.join(readConfig.proDir, 'file', web, site, xls_name)
print("xls path:"+xls_path)
# open excel file
book = open_workbook(xls_path)
# get sheet by name
sheet = book.sheet_by_name(sheet_name)
# get nrows
nrows = sheet.nrows
for i in range(nrows):
if sheet.row_values(i)[0] != u'case_name':
cls.append(sheet.row_values(i))
# print(sheet.row_values(i))
return cls
activity = {}
def set_xml():
"""
get element
:return:
"""
web = runSet.get_web()
site = runSet.get_site()
if len(activity) == 0:
file_path = os.path.join(readConfig.proDir, 'file', web, site, 'element.xml')
tree = ElementTree.parse(file_path)
for a in tree.findall('activity'):
activity_name = a.get('name')
element = {}
for e in a.getchildren():
element_name = e.get('id')
element_child = {}
for t in e.getchildren():
element_child[t.tag] = t.text
element[element_name] = element_child
activity[activity_name] = element
def get_el_dict(activity_name, element):
"""
According to page, activity and element getting element
:param activity_name: activity name
:param element: element name
:return:
"""
set_xml()
element_dict = activity.get(activity_name).get(element)
print(element_dict)
return element_dict
class Element: #Element("shein", "www", "login", "login_link").is_exist()
def __init__(self, activity_name, element_name):
self.driver1 = Driver.get_browser()
self.driver = self.driver1.get_driver()
self.activity = activity_name
self.element = element_name
element_dict = get_el_dict(self.activity, self.element)
self.pathType = element_dict.get('pathType')
self.pathValue = element_dict.get('pathValue')
def is_exist(self):
"""
Determine element is exist
:return: TRUE OR FALSE
"""
try:
if self.pathType == 'ID':
self.driver.find_element_by_id(self.pathValue)
return True
if self.pathType == 'XPATH':
self.driver.find_elements_by_xpath(self.pathValue)
return True
if self.pathType == 'CLASSNAME':
self.driver.find_element_by_class_name(self.pathValue)
return True
if self.pathType == 'NAME':
self.driver.find_element_by_name(self.pathValue)
return True
except NoSuchElementException:
return False
def wait_element(self, wait_time):
"""
wait element appear in time
:param wait_time: wait time
:return: true or false
"""
time.sleep(wait_time)
if self.is_exist():
return True
else:
return False
def get_element(self):
"""
get element
:return: element
"""
try:
if self.pathType == 'ID':
element = self.driver.find_element_by_id(self.pathValue)
return element
if self.pathType == 'XPATH':
element = self.driver.find_elements_by_xpath(self.pathValue)
return element
if self.pathType == 'CLASSNAME':
element = self.driver.find_element_by_class_name(self.pathValue)
return element
if self.pathType == 'NAME':
element = self.driver.find_element_by_name(self.pathValue)
return element
except NoSuchElementException:
return None
def get_element_by_index(self, index):
"""
get element by index
:param index: index
:return: element
"""
try:
if self.pathType == 'ID':
element = self.driver.find_element_by_id(self.pathValue)
return element[index]
if self.pathType == 'XPATH':
element = self.driver.find_elements_by_xpath(self.pathValue)
return element[index]
if self.pathType == 'CLASSNAME':
element = self.driver.find_element_by_class_name(self.pathValue)
return element[index]
if self.pathType == 'NAME':
element = self.driver.find_element_by_name(self.pathValue)
return element[index]
except NoSuchElementException:
return None
def get_element_list(self):
"""
get element list
:return: element list
"""
try:
if self.pathType == 'ID':
element_list = self.driver.find_element_by_id(self.pathValue)
return element_list
if self.pathType == 'XPATH':
element_list = self.driver.find_elements_by_xpath(self.pathValue)
return element_list
if self.pathType == 'CLASSNAME':
element_list = self.driver.find_element_by_class_name(self.pathValue)
return element_list
if self.pathType == 'NAME':
element_list = self.driver.find_element_by_name(self.pathValue)
return element_list
except NoSuchElementException:
return None
def click(self):
"""
click element
:return:
"""
element = self.get_element()
time.sleep(1)
element.click()
def send_key(self, key):
"""
input key
:param key: input value
:return:
"""
element = self.get_element()
time.sleep(1)
element.clear()
element.send_keys(key)
def input_keys(self, index, key):
"""
By index send key
:param index: index
:param key: key
:return:
"""
element = self.get_element_by_index(index)
time.sleep(1)
element.clear()
element.send_keys(key)
def get_text_value(self):
"""
get attribute
:return:
"""
element = self.get_element()
value = element.get_attribute('text')
return str(value)
|
[
"173302591@qq.com"
] |
173302591@qq.com
|
3f2b9edec5b874889539962e8060e37f70b0e80b
|
ce03246acb0759c698b096430d7a3d8f5bf2be41
|
/ups/migrations/0007_auto_20141230_1451.py
|
58635d7a6754e9715c1a9fe260444855b77f4b1d
|
[] |
no_license
|
grovesr/mirai-clinical-ups
|
07b8f8f9b596fdad26f81622b1baec972d7bc9bb
|
89db247b3ac4431859dd65c3582a4840c3809483
|
refs/heads/master
| 2020-05-17T04:12:50.973958
| 2015-02-23T12:49:48
| 2015-02-23T12:49:48
| 28,535,784
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 979
|
py
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import datetime
from django.utils.timezone import utc
class Migration(migrations.Migration):
dependencies = [
('ups', '0006_auto_20141230_0814'),
]
operations = [
migrations.AlterField(
model_name='custorderqueryrow',
name='queryId',
field=models.DateTimeField(default=datetime.datetime(2014, 12, 30, 19, 51, 46, 892, tzinfo=utc)),
preserve_default=True,
),
migrations.AlterField(
model_name='ph',
name='PH1_STOP_SHIP_DATE',
field=models.DateTimeField(blank=True),
preserve_default=True,
),
migrations.AlterField(
model_name='pickticket',
name='DOC_DATE',
field=models.CharField(default=b'12/30/14 19:51:45', max_length=17),
preserve_default=True,
),
]
|
[
"grovesr1@yahoo.com"
] |
grovesr1@yahoo.com
|
09cebb2e4a74f46e415c95b46e898d0f613ea202
|
1dae87abcaf49f1d995d03c0ce49fbb3b983d74a
|
/programs/subroutines/Grav Comp Ramp.sub.py
|
d53530d7c120d2b2fbd9cc6eeda242696b5c8d6d
|
[] |
no_license
|
BEC-Trento/BEC1-data
|
651cd8e5f15a7d9848f9921b352e0830c08f27dd
|
f849086891bc68ecf7447f62962f791496d01858
|
refs/heads/master
| 2023-03-10T19:19:54.833567
| 2023-03-03T22:59:01
| 2023-03-03T22:59:01
| 132,161,998
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 115
|
py
|
prg_comment = ""
prg_version = "0.5.1"
def program(prg, cmd):
prg.add(0, "Grav Comp", 0.000000)
return prg
|
[
"carmelo.mordini@unitn.it"
] |
carmelo.mordini@unitn.it
|
8a6f89c809cc96aab322db6b24f652d3838b3138
|
487fb49582444005fd55158b22b1428b8146adf4
|
/models/resnet.py
|
11f4cf9e8341e90600c0c78c9b3cd99c77f7d32e
|
[] |
no_license
|
speciallan/BCNN
|
c7a7374931b581c73b8b24ec5e31b77578bdf6b0
|
6964181acb35c3005f65fb0aa38263a986efcaf0
|
refs/heads/master
| 2020-09-21T18:18:03.819322
| 2019-12-23T12:19:25
| 2019-12-23T12:19:25
| 224,879,530
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 22,474
|
py
|
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Author:Speciallan
"""ResNet, ResNetV2, and ResNeXt models for Keras.
# Reference papers
- [Deep Residual Learning for Image Recognition]
(https://arxiv.org/abs/1512.03385) (CVPR 2016 Best Paper Award)
- [Identity Mappings in Deep Residual Networks]
(https://arxiv.org/abs/1603.05027) (ECCV 2016)
- [Aggregated Residual Transformations for Deep Neural Networks]
(https://arxiv.org/abs/1611.05431) (CVPR 2017)
# Reference implementations
- [TensorNets]
(https://github.com/taehoonlee/tensornets/blob/master/tensornets/resnets.py)
- [Caffe ResNet]
(https://github.com/KaimingHe/deep-residual-networks/tree/master/prototxt)
- [Torch ResNetV2]
(https://github.com/facebook/fb.resnet.torch/blob/master/models/preresnet.lua)
- [Torch ResNeXt]
(https://github.com/facebookresearch/ResNeXt/blob/master/models/resnext.lua)
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import numpy as np
from . import get_submodules_from_kwargs
from .imagenet_utils import _obtain_input_shape
backend = None
layers = None
models = None
keras_utils = None
BASE_WEIGHTS_PATH = (
'https://github.com/keras-team/keras-applications/'
'releases/download/resnet/')
WEIGHTS_HASHES = {
'resnet50': ('2cb95161c43110f7111970584f804107',
'4d473c1dd8becc155b73f8504c6f6626'),
'resnet101': ('f1aeb4b969a6efcfb50fad2f0c20cfc5',
'88cf7a10940856eca736dc7b7e228a21'),
'resnet152': ('100835be76be38e30d865e96f2aaae62',
'ee4c566cf9a93f14d82f913c2dc6dd0c'),
'resnet50v2': ('3ef43a0b657b3be2300d5770ece849e0',
'fac2f116257151a9d068a22e544a4917'),
'resnet101v2': ('6343647c601c52e1368623803854d971',
'c0ed64b8031c3730f411d2eb4eea35b5'),
'resnet152v2': ('a49b44d1979771252814e80f8ec446f9',
'ed17cf2e0169df9d443503ef94b23b33'),
'resnext50': ('67a5b30d522ed92f75a1f16eef299d1a',
'62527c363bdd9ec598bed41947b379fc'),
'resnext101': ('34fb605428fcc7aa4d62f44404c11509',
'0f678c91647380debd923963594981b3')
}
def block1(x, filters, kernel_size=3, stride=1,
conv_shortcut=True, name=None):
"""A residual block.
# Arguments
x: input tensor.
filters: integer, filters of the bottleneck layer.
kernel_size: default 3, kernel size of the bottleneck layer.
stride: default 1, stride of the first layer.
conv_shortcut: default True, use convolution shortcut if True,
otherwise identity shortcut.
name: string, block label.
# Returns
Output tensor for the residual block.
"""
bn_axis = 3 if backend.image_data_format() == 'channels_last' else 1
if conv_shortcut is True:
shortcut = layers.Conv2D(4 * filters, 1, strides=stride,
name=name + '_0_conv')(x)
shortcut = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_0_bn')(shortcut)
else:
shortcut = x
x = layers.Conv2D(filters, 1, strides=stride, name=name + '_1_conv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_1_bn')(x)
x = layers.Activation('relu', name=name + '_1_relu')(x)
x = layers.Conv2D(filters, kernel_size, padding='SAME',
name=name + '_2_conv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_2_bn')(x)
x = layers.Activation('relu', name=name + '_2_relu')(x)
x = layers.Conv2D(4 * filters, 1, name=name + '_3_conv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_3_bn')(x)
x = layers.Add(name=name + '_add')([shortcut, x])
x = layers.Activation('relu', name=name + '_out')(x)
return x
def stack1(x, filters, blocks, stride1=2, name=None):
"""A set of stacked residual blocks.
# Arguments
x: input tensor.
filters: integer, filters of the bottleneck layer in a block.
blocks: integer, blocks in the stacked blocks.
stride1: default 2, stride of the first layer in the first block.
name: string, stack label.
# Returns
Output tensor for the stacked blocks.
"""
x = block1(x, filters, stride=stride1, name=name + '_block1')
for i in range(2, blocks + 1):
x = block1(x, filters, conv_shortcut=False, name=name + '_block' + str(i))
return x
def block2(x, filters, kernel_size=3, stride=1,
conv_shortcut=False, name=None):
"""A residual block.
# Arguments
x: input tensor.
filters: integer, filters of the bottleneck layer.
kernel_size: default 3, kernel size of the bottleneck layer.
stride: default 1, stride of the first layer.
conv_shortcut: default False, use convolution shortcut if True,
otherwise identity shortcut.
name: string, block label.
# Returns
Output tensor for the residual block.
"""
bn_axis = 3 if backend.image_data_format() == 'channels_last' else 1
preact = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_preact_bn')(x)
preact = layers.Activation('relu', name=name + '_preact_relu')(preact)
if conv_shortcut is True:
shortcut = layers.Conv2D(4 * filters, 1, strides=stride,
name=name + '_0_conv')(preact)
else:
shortcut = layers.MaxPooling2D(1, strides=stride)(x) if stride > 1 else x
x = layers.Conv2D(filters, 1, strides=1, use_bias=False,
name=name + '_1_conv')(preact)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_1_bn')(x)
x = layers.Activation('relu', name=name + '_1_relu')(x)
x = layers.ZeroPadding2D(padding=((1, 1), (1, 1)), name=name + '_2_pad')(x)
x = layers.Conv2D(filters, kernel_size, strides=stride,
use_bias=False, name=name + '_2_conv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_2_bn')(x)
x = layers.Activation('relu', name=name + '_2_relu')(x)
x = layers.Conv2D(4 * filters, 1, name=name + '_3_conv')(x)
x = layers.Add(name=name + '_out')([shortcut, x])
return x
def stack2(x, filters, blocks, stride1=2, name=None):
"""A set of stacked residual blocks.
# Arguments
x: input tensor.
filters: integer, filters of the bottleneck layer in a block.
blocks: integer, blocks in the stacked blocks.
stride1: default 2, stride of the first layer in the first block.
name: string, stack label.
# Returns
Output tensor for the stacked blocks.
"""
x = block2(x, filters, conv_shortcut=True, name=name + '_block1')
for i in range(2, blocks):
x = block2(x, filters, name=name + '_block' + str(i))
x = block2(x, filters, stride=stride1, name=name + '_block' + str(blocks))
return x
def block3(x, filters, kernel_size=3, stride=1, groups=32,
conv_shortcut=True, name=None):
"""A residual block.
# Arguments
x: input tensor.
filters: integer, filters of the bottleneck layer.
kernel_size: default 3, kernel size of the bottleneck layer.
stride: default 1, stride of the first layer.
groups: default 32, group size for grouped convolution.
conv_shortcut: default True, use convolution shortcut if True,
otherwise identity shortcut.
name: string, block label.
# Returns
Output tensor for the residual block.
"""
bn_axis = 3 if backend.image_data_format() == 'channels_last' else 1
if conv_shortcut is True:
shortcut = layers.Conv2D((64 // groups) * filters, 1, strides=stride,
use_bias=False, name=name + '_0_conv')(x)
shortcut = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_0_bn')(shortcut)
else:
shortcut = x
x = layers.Conv2D(filters, 1, use_bias=False, name=name + '_1_conv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_1_bn')(x)
x = layers.Activation('relu', name=name + '_1_relu')(x)
c = filters // groups
x = layers.ZeroPadding2D(padding=((1, 1), (1, 1)), name=name + '_2_pad')(x)
x = layers.DepthwiseConv2D(kernel_size, strides=stride, depth_multiplier=c,
use_bias=False, name=name + '_2_conv')(x)
kernel = np.zeros((1, 1, filters * c, filters), dtype=np.float32)
for i in range(filters):
start = (i // c) * c * c + i % c
end = start + c * c
kernel[:, :, start:end:c, i] = 1.
x = layers.Conv2D(filters, 1, use_bias=False, trainable=False,
kernel_initializer={'class_name': 'Constant',
'config': {'value': kernel}},
name=name + '_2_gconv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_2_bn')(x)
x = layers.Activation('relu', name=name + '_2_relu')(x)
x = layers.Conv2D((64 // groups) * filters, 1,
use_bias=False, name=name + '_3_conv')(x)
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name=name + '_3_bn')(x)
x = layers.Add(name=name + '_add')([shortcut, x])
x = layers.Activation('relu', name=name + '_out')(x)
return x
def stack3(x, filters, blocks, stride1=2, groups=32, name=None):
"""A set of stacked residual blocks.
# Arguments
x: input tensor.
filters: integer, filters of the bottleneck layer in a block.
blocks: integer, blocks in the stacked blocks.
stride1: default 2, stride of the first layer in the first block.
groups: default 32, group size for grouped convolution.
name: string, stack label.
# Returns
Output tensor for the stacked blocks.
"""
x = block3(x, filters, stride=stride1, groups=groups, name=name + '_block1')
for i in range(2, blocks + 1):
x = block3(x, filters, groups=groups, conv_shortcut=False,
name=name + '_block' + str(i))
return x
def ResNet(stack_fn,
preact,
use_bias,
model_name='resnet',
include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
"""Instantiates the ResNet, ResNetV2, and ResNeXt architecture.
Optionally loads weights pre-trained on ImageNet.
Note that the data format convention used by the model is
the one specified in your Keras config at `~/.keras/keras.json`.
# Arguments
stack_fn: a function that returns output tensor for the
stacked residual blocks.
preact: whether to use pre-activation or not
(True for ResNetV2, False for ResNet and ResNeXt).
use_bias: whether to use biases for convolutional layers or not
(True for ResNet and ResNetV2, False for ResNeXt).
model_name: string, model name.
include_top: whether to include the fully-connected
layer at the top of the network.
weights: one of `None` (random initialization),
'imagenet' (pre-training on ImageNet),
or the path to the weights file to be loaded.
input_tensor: optional Keras tensor
(i.e. output of `layers.Input()`)
to use as image input for the model.
input_shape: optional shape tuple, only to be specified
if `include_top` is False (otherwise the input shape
has to be `(224, 224, 3)` (with `channels_last` data format)
or `(3, 224, 224)` (with `channels_first` data format).
It should have exactly 3 inputs channels.
pooling: optional pooling mode for feature extraction
when `include_top` is `False`.
- `None` means that the output of the model will be
the 4D tensor output of the
last convolutional layer.
- `avg` means that global average pooling
will be applied to the output of the
last convolutional layer, and thus
the output of the model will be a 2D tensor.
- `max` means that global max pooling will
be applied.
classes: optional number of classes to classify images
into, only to be specified if `include_top` is True, and
if no `weights` argument is specified.
# Returns
A Keras model instance.
# Raises
ValueError: in case of invalid argument for `weights`,
or invalid input shape.
"""
global backend, layers, models, keras_utils
backend, layers, models, keras_utils = get_submodules_from_kwargs(kwargs)
if not (weights in {'imagenet', None} or os.path.exists(weights)):
raise ValueError('The `weights` argument should be either '
'`None` (random initialization), `imagenet` '
'(pre-training on ImageNet), '
'or the path to the weights file to be loaded.')
if weights == 'imagenet' and include_top and classes != 1000:
raise ValueError('If using `weights` as `"imagenet"` with `include_top`'
' as true, `classes` should be 1000')
# Determine proper input shape
input_shape = _obtain_input_shape(input_shape,
default_size=224,
min_size=32,
data_format=backend.image_data_format(),
require_flatten=include_top,
weights=weights)
if input_tensor is None:
img_input = layers.Input(shape=input_shape)
else:
if not backend.is_keras_tensor(input_tensor):
img_input = layers.Input(tensor=input_tensor, shape=input_shape)
else:
img_input = input_tensor
bn_axis = 3 if backend.image_data_format() == 'channels_last' else 1
x = layers.ZeroPadding2D(padding=((3, 3), (3, 3)), name='conv1_pad')(img_input)
x = layers.Conv2D(64, 7, strides=2, use_bias=use_bias, name='conv1_conv')(x)
if preact is False:
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name='conv1_bn')(x)
x = layers.Activation('relu', name='conv1_relu')(x)
x = layers.ZeroPadding2D(padding=((1, 1), (1, 1)), name='pool1_pad')(x)
x = layers.MaxPooling2D(3, strides=2, name='pool1_pool')(x)
x = stack_fn(x)
if preact is True:
x = layers.BatchNormalization(axis=bn_axis, epsilon=1.001e-5,
name='post_bn')(x)
x = layers.Activation('relu', name='post_relu')(x)
if include_top:
x = layers.GlobalAveragePooling2D(name='avg_pool')(x)
x = layers.Dense(classes, activation='softmax', name='probs')(x)
else:
if pooling == 'avg':
x = layers.GlobalAveragePooling2D(name='avg_pool')(x)
elif pooling == 'max':
x = layers.GlobalMaxPooling2D(name='max_pool')(x)
# Ensure that the model takes into account
# any potential predecessors of `input_tensor`.
if input_tensor is not None:
inputs = keras_utils.get_source_inputs(input_tensor)
else:
inputs = img_input
# Create model.
model = models.Model(inputs, x, name=model_name)
# Load weights.
if (weights == 'imagenet') and (model_name in WEIGHTS_HASHES):
if include_top:
file_name = model_name + '_weights_tf_dim_ordering_tf_kernels.h5'
file_hash = WEIGHTS_HASHES[model_name][0]
else:
file_name = model_name + '_weights_tf_dim_ordering_tf_kernels_notop.h5'
file_hash = WEIGHTS_HASHES[model_name][1]
weights_path = keras_utils.get_file(file_name,
BASE_WEIGHTS_PATH + file_name,
cache_subdir='models',
file_hash=file_hash)
by_name = True if 'resnext' in model_name else False
model.load_weights(weights_path, by_name=by_name)
elif weights is not None:
model.load_weights(weights)
return model
def ResNet50(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack1(x, 64, 3, stride1=1, name='conv2')
x = stack1(x, 128, 4, name='conv3')
x = stack1(x, 256, 6, name='conv4')
x = stack1(x, 512, 3, name='conv5')
return x
return ResNet(stack_fn, False, True, 'resnet50',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNet101(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack1(x, 64, 3, stride1=1, name='conv2')
x = stack1(x, 128, 4, name='conv3')
x = stack1(x, 256, 23, name='conv4')
x = stack1(x, 512, 3, name='conv5')
return x
return ResNet(stack_fn, False, True, 'resnet101',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNet152(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack1(x, 64, 3, stride1=1, name='conv2')
x = stack1(x, 128, 8, name='conv3')
x = stack1(x, 256, 36, name='conv4')
x = stack1(x, 512, 3, name='conv5')
return x
return ResNet(stack_fn, False, True, 'resnet152',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNet50V2(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack2(x, 64, 3, name='conv2')
x = stack2(x, 128, 4, name='conv3')
x = stack2(x, 256, 6, name='conv4')
x = stack2(x, 512, 3, stride1=1, name='conv5')
return x
return ResNet(stack_fn, True, True, 'resnet50v2',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNet101V2(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack2(x, 64, 3, name='conv2')
x = stack2(x, 128, 4, name='conv3')
x = stack2(x, 256, 23, name='conv4')
x = stack2(x, 512, 3, stride1=1, name='conv5')
return x
return ResNet(stack_fn, True, True, 'resnet101v2',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNet152V2(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack2(x, 64, 3, name='conv2')
x = stack2(x, 128, 8, name='conv3')
x = stack2(x, 256, 36, name='conv4')
x = stack2(x, 512, 3, stride1=1, name='conv5')
return x
return ResNet(stack_fn, True, True, 'resnet152v2',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNeXt50(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack3(x, 128, 3, stride1=1, name='conv2')
x = stack3(x, 256, 4, name='conv3')
x = stack3(x, 512, 6, name='conv4')
x = stack3(x, 1024, 3, name='conv5')
return x
return ResNet(stack_fn, False, False, 'resnext50',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
def ResNeXt101(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
**kwargs):
def stack_fn(x):
x = stack3(x, 128, 3, stride1=1, name='conv2')
x = stack3(x, 256, 4, name='conv3')
x = stack3(x, 512, 23, name='conv4')
x = stack3(x, 1024, 3, name='conv5')
return x
return ResNet(stack_fn, False, False, 'resnext101',
include_top, weights,
input_tensor, input_shape,
pooling, classes,
**kwargs)
setattr(ResNet50, '__doc__', ResNet.__doc__)
setattr(ResNet101, '__doc__', ResNet.__doc__)
setattr(ResNet152, '__doc__', ResNet.__doc__)
setattr(ResNet50V2, '__doc__', ResNet.__doc__)
setattr(ResNet101V2, '__doc__', ResNet.__doc__)
setattr(ResNet152V2, '__doc__', ResNet.__doc__)
setattr(ResNeXt50, '__doc__', ResNet.__doc__)
setattr(ResNeXt101, '__doc__', ResNet.__doc__)
|
[
"350394776@qq.com"
] |
350394776@qq.com
|
6c0c670495008cbd06140f21e047f3da7ee7a9c9
|
6ceea2578be0cbc1543be3649d0ad01dd55072aa
|
/src/examples/elphf/diffusion/mesh1D.py
|
b8a851a3a7a81fb4e593b52c70dcb733f0cf0331
|
[
"LicenseRef-scancode-public-domain"
] |
permissive
|
regmi/fipy
|
57972add2cc8e6c04fda09ff2faca9a2c45ad19d
|
eb4aacf5a8e35cdb0e41beb0d79a93e7c8aacbad
|
refs/heads/master
| 2020-04-27T13:51:45.095692
| 2010-04-09T07:32:42
| 2010-04-09T07:32:42
| 602,099
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 6,365
|
py
|
#!/usr/bin/env python
##
# ###################################################################
# FiPy - Python-based finite volume PDE solver
#
# FILE: "mesh1D.py"
#
# Author: Jonathan Guyer <guyer@nist.gov>
# Author: Daniel Wheeler <daniel.wheeler@nist.gov>
# Author: James Warren <jwarren@nist.gov>
# mail: NIST
# www: http://www.ctcms.nist.gov/fipy/
#
# ========================================================================
# This software was developed at the National Institute of Standards
# and Technology by employees of the Federal Government in the course
# of their official duties. Pursuant to title 17 Section 105 of the
# United States Code this software is not subject to copyright
# protection and is in the public domain. FiPy is an experimental
# system. NIST assumes no responsibility whatsoever for its use by
# other parties, and makes no guarantees, expressed or implied, about
# its quality, reliability, or any other characteristic. We would
# appreciate acknowledgement if the software is used.
#
# This software can be redistributed and/or modified freely
# provided that any derivative works bear some notice that they are
# derived from it, and any modified versions bear some notice that
# they have been modified.
# ========================================================================
#
# ###################################################################
##
r"""
A simple 1D example to test the setup of the multi-component diffusion
equations. The diffusion equation for each species in single-phase
multicomponent system can be expressed as
.. math::
\frac{\partial C_j}{\partial t}
= D_{jj}\nabla^2 C_j
+ D_{j}\nabla\cdot
\frac{C_j}{1 - \sum_{\substack{k=2\\ k \neq j}}^{n-1} C_k}
\sum_{\substack{i=2\\ i \neq j}}^{n-1} \nabla C_i
where :math:`C_j` is the concentration of the :math:`j^\text{th}` species,
:math:`t` is time, :math:`D_{jj}` is the self-diffusion coefficient of the
:math:`j^\text{th}` species, and :math:`\sum_{\substack{i=2\\ i \neq j}}^{n-1}`
represents the summation over all substitutional species in the system,
excluding the solvent and the component of interest.
We solve the problem on a 1D mesh
>>> nx = 400
>>> dx = 0.01
>>> L = nx * dx
>>> from fipy import *
>>> mesh = Grid1D(dx = dx, nx = nx)
One component in this ternary system will be designated the "solvent"
>>> class ComponentVariable(CellVariable):
... def __init__(self, mesh, value = 0., name = '',
... standardPotential = 0., barrier = 0.,
... diffusivity = None, valence = 0, equation = None):
... CellVariable.__init__(self, mesh = mesh, value = value,
... name = name)
... self.standardPotential = standardPotential
... self.barrier = barrier
... self.diffusivity = diffusivity
... self.valence = valence
... self.equation = equation
...
... def copy(self):
... return self.__class__(mesh = self.getMesh(),
... value = self.getValue(),
... name = self.getName(),
... standardPotential =
... self.standardPotential,
... barrier = self.barrier,
... diffusivity = self.diffusivity,
... valence = self.valence,
... equation = self.equation)
>>> solvent = ComponentVariable(mesh = mesh, name = 'Cn', value = 1.)
We can create an arbitrary number of components,
simply by providing a :keyword:`tuple` or :keyword:`list` of components
>>> substitutionals = [
... ComponentVariable(mesh = mesh, name = 'C1', diffusivity = 1.,
... standardPotential = 1., barrier = 1.),
... ComponentVariable(mesh = mesh, name = 'C2', diffusivity = 1.,
... standardPotential = 1., barrier = 1.),
... ]
>>> interstitials = []
>>> for component in substitutionals:
... solvent -= component
We separate the solution domain into two different concentration regimes
>>> x = mesh.getCellCenters()[0]
>>> substitutionals[0].setValue(0.3)
>>> substitutionals[0].setValue(0.6, where=x > L / 2)
>>> substitutionals[1].setValue(0.6)
>>> substitutionals[1].setValue(0.3, where=x > L / 2)
We create one diffusion equation for each substitutional component
>>> for Cj in substitutionals:
... CkSum = ComponentVariable(mesh = mesh, value = 0.)
... CkFaceSum = FaceVariable(mesh = mesh, value = 0.)
... for Ck in [Ck for Ck in substitutionals if Ck is not Cj]:
... CkSum += Ck
... CkFaceSum += Ck.getHarmonicFaceValue()
...
... convectionCoeff = CkSum.getFaceGrad() \
... * (Cj.diffusivity / (1. - CkFaceSum))
...
... Cj.equation = (TransientTerm()
... == DiffusionTerm(coeff=Cj.diffusivity)
... + PowerLawConvectionTerm(coeff=convectionCoeff))
If we are running interactively, we create a viewer to see the results
>>> if __name__ == '__main__':
... viewer = Viewer(vars=[solvent] + substitutionals,
... datamin=0, datamax=1)
... viewer.plot()
Now, we iterate the problem to equilibrium, plotting as we go
>>> for i in range(40):
... for Cj in substitutionals:
... Cj.updateOld()
... for Cj in substitutionals:
... Cj.equation.solve(var = Cj,
... dt = 10000.)
... if __name__ == '__main__':
... viewer.plot()
Since there is nothing to maintain the concentration separation in this problem,
we verify that the concentrations have become uniform
>>> substitutionals[0].allclose(0.45, rtol = 1e-7, atol = 1e-7).getValue()
1
>>> substitutionals[1].allclose(0.45, rtol = 1e-7, atol = 1e-7).getValue()
1
"""
__docformat__ = 'restructuredtext'
if __name__ == '__main__':
## from fipy.tools.profiler.profiler import Profiler
## from fipy.tools.profiler.profiler import calibrate_profiler
# fudge = calibrate_profiler(10000)
# profile = Profiler('profile', fudge=fudge)
import fipy.tests.doctestPlus
exec(fipy.tests.doctestPlus._getScript())
# profile.stop()
raw_input("finished")
|
[
"regmisk@gmail.com"
] |
regmisk@gmail.com
|
b4e3ece9d63cafcc0094b68b757097aa4f19d1a0
|
6c00499dfe1501294ac56b0d1607fb942aafc2ee
|
/eventregistry/Query.py
|
b5101c6dd57c31efc43c5f5eb21add58b4e548fd
|
[
"MIT"
] |
permissive
|
EventRegistry/event-registry-python
|
dd692729cb5c505e421d4b771804e712e5b6442b
|
bf3ce144fa61cc195840591bae5ca88b31ca9139
|
refs/heads/master
| 2023-07-06T11:04:41.033864
| 2023-06-23T08:40:31
| 2023-06-23T08:40:31
| 40,995,963
| 176
| 48
|
MIT
| 2020-10-21T09:17:06
| 2015-08-18T20:29:23
|
Python
|
UTF-8
|
Python
| false
| false
| 16,151
|
py
|
from .Base import QueryParamsBase, QueryItems
import six, datetime
from typing import Union, List
class _QueryCore(object):
def __init__(self):
self._queryObj = {}
def getQuery(self):
return self._queryObj
def setQueryParam(self, paramName, val):
self._queryObj[paramName] = val
def _setValIfNotDefault(self, propName, value, defVal):
if value != defVal:
self._queryObj[propName] = value
class BaseQuery(_QueryCore):
def __init__(self,
keyword: Union[str, QueryItems, None] = None,
conceptUri: Union[str, QueryItems, None] = None,
categoryUri: Union[str, QueryItems, None] = None,
sourceUri: Union[str, QueryItems, None] = None,
locationUri: Union[str, QueryItems, None] = None,
lang: Union[str, QueryItems, None] = None,
dateStart: Union[datetime.datetime, datetime.date, str, None] = None,
dateEnd: Union[datetime.datetime, datetime.date, str, None] = None,
sourceLocationUri: Union[str, List[str], None] = None,
sourceGroupUri: Union[str, List[str], None] = None,
# article or event search only:
dateMention: Union[datetime.datetime, datetime.date, str, None] = None,
authorUri: Union[str, List[str], None] = None,
keywordLoc: str = "body",
# event search only:
minMaxArticlesInEvent = None,
# mention search only:
industryUri: Union[str, QueryItems, None] = None,
sdgUri: Union[str, QueryItems, None] = None,
sasbUri: Union[str, QueryItems, None] = None,
esgUri: Union[str, QueryItems, None] = None,
# universal:
exclude: Union["BaseQuery", "CombinedQuery", None] = None):
"""
@param keyword: keyword(s) to query. Either None, string or QueryItems instance
@param conceptUri: concept(s) to query. Either None, string or QueryItems instance
@param sourceUri: source(s) to query. Either None, string or QueryItems instance
@param locationUri: location(s) to query. Either None, string or QueryItems instance
@param categoryUri: categories to query. Either None, string or QueryItems instance
@param lang: language(s) to query. Either None, string or QueryItems instance
@param dateStart: starting date. Either None, string or date or datetime
@param dateEnd: ending date. Either None, string or date or datetime
@param dateMention: search by mentioned dates - Either None, string or date or datetime or a list of these types
@param sourceLocationUri: find content generated by news sources at the specified geographic location - can be a city URI or a country URI. Multiple items can be provided using a list
@param sourceGroupUri: a single or multiple source group URIs. A source group is a group of news sources, commonly defined based on common topic or importance
@param authorUri: author(s) to query. Either None, string or QueryItems instance
@param keywordLoc: where should we look when searching using the keywords provided by "keyword" parameter. "body" (default), "title", or "body,title"
@param minMaxArticlesInEvent: a tuple containing the minimum and maximum number of articles that should be in the resulting events. Parameter relevant only if querying events
@param exclude: a instance of BaseQuery, CombinedQuery or None. Used to filter out results matching the other criteria specified in this query
"""
super(BaseQuery, self).__init__()
self._setQueryArrVal("keyword", keyword)
self._setQueryArrVal("conceptUri", conceptUri)
self._setQueryArrVal("categoryUri", categoryUri)
self._setQueryArrVal("sourceUri", sourceUri)
self._setQueryArrVal("locationUri", locationUri)
self._setQueryArrVal("lang", lang)
# starting date of the published articles (e.g. 2014-05-02)
if dateStart is not None:
self._queryObj["dateStart"] = QueryParamsBase.encodeDate(dateStart)
# ending date of the published articles (e.g. 2014-05-02)
if dateEnd is not None:
self._queryObj["dateEnd"] = QueryParamsBase.encodeDate(dateEnd)
# mentioned date detected in articles (e.g. 2014-05-02)
if dateMention is not None:
if isinstance(dateMention, list):
self._queryObj["dateMention"] = [QueryParamsBase.encodeDate(d) for d in dateMention]
else:
self._queryObj["dateMention"] = QueryParamsBase.encodeDate(dateMention)
self._setQueryArrVal("sourceLocationUri", sourceLocationUri)
self._setQueryArrVal("sourceGroupUri", sourceGroupUri)
self._setQueryArrVal("authorUri", authorUri)
self._setQueryArrVal("industryUri", industryUri)
self._setQueryArrVal("sdgUri", sdgUri)
self._setQueryArrVal("sasbUri", sasbUri)
self._setQueryArrVal("esgUri", esgUri)
if keywordLoc != "body":
self._queryObj["keywordLoc"] = keywordLoc
if minMaxArticlesInEvent is not None:
assert isinstance(minMaxArticlesInEvent, tuple), "minMaxArticlesInEvent parameter should either be None or a tuple with two integer values"
self._queryObj["minArticlesInEvent"] = minMaxArticlesInEvent[0]
self._queryObj["maxArticlesInEvent"] = minMaxArticlesInEvent[1]
if exclude is not None:
assert isinstance(exclude, (CombinedQuery, BaseQuery)), "exclude parameter was not a CombinedQuery or BaseQuery instance"
self._queryObj["$not"] = exclude.getQuery()
def _setQueryArrVal(self, propName: str, value):
# by default we have None - so don't do anything
if value is None:
return
# if we have an instance of QueryItems then apply it
if isinstance(value, QueryItems):
self._queryObj[propName] = { value.getOper(): value.getItems() }
# if we have a string value, just use it
elif isinstance(value, six.string_types):
self._queryObj[propName] = value
# there should be no other valid types
else:
assert False, "Parameter '%s' was of unsupported type. It should either be None, a string or an instance of QueryItems" % (propName)
class CombinedQuery(_QueryCore):
def __init__(self):
super(CombinedQuery, self).__init__()
@staticmethod
def AND(queryArr: List[Union["BaseQuery", "CombinedQuery"]],
exclude: Union["BaseQuery", "CombinedQuery", None] = None):
"""
create a combined query with multiple items on which to perform an AND operation
@param queryArr: a list of items on which to perform an AND operation. Items can be either a CombinedQuery or BaseQuery instances.
@param exclude: a instance of BaseQuery, CombinedQuery or None. Used to filter out results matching the other criteria specified in this query
"""
assert isinstance(queryArr, list), "provided argument as not a list"
assert len(queryArr) > 0, "queryArr had an empty list"
q = CombinedQuery()
q.setQueryParam("$and", [])
for item in queryArr:
assert isinstance(item, (CombinedQuery, BaseQuery)), "item in the list was not a CombinedQuery or BaseQuery instance"
q.getQuery()["$and"].append(item.getQuery())
if exclude is not None:
assert isinstance(exclude, (CombinedQuery, BaseQuery)), "exclude parameter was not a CombinedQuery or BaseQuery instance"
q.setQueryParam("$not", exclude.getQuery())
return q
@staticmethod
def OR(queryArr: List[Union["BaseQuery", "CombinedQuery"]],
exclude: Union["BaseQuery", "CombinedQuery", None] = None):
"""
create a combined query with multiple items on which to perform an OR operation
@param queryArr: a list of items on which to perform an OR operation. Items can be either a CombinedQuery or BaseQuery instances.
@param exclude: a instance of BaseQuery, CombinedQuery or None. Used to filter out results matching the other criteria specified in this query
"""
assert isinstance(queryArr, list), "provided argument as not a list"
assert len(queryArr) > 0, "queryArr had an empty list"
q = CombinedQuery()
q.setQueryParam("$or", [])
for item in queryArr:
assert isinstance(item, (CombinedQuery, BaseQuery)), "item in the list was not a CombinedQuery or BaseQuery instance"
q.getQuery()["$or"].append(item.getQuery())
if exclude is not None:
assert isinstance(exclude, (CombinedQuery, BaseQuery)), "exclude parameter was not a CombinedQuery or BaseQuery instance"
q.setQueryParam("$not", exclude.getQuery())
return q
class ComplexArticleQuery(_QueryCore):
def __init__(self,
query: Union["BaseQuery", "CombinedQuery"],
dataType: Union[str, List[str]] = "news",
minSentiment: Union[float, None] = None,
maxSentiment: Union[float, None] = None,
minSocialScore: int = 0,
minFacebookShares: int = 0,
startSourceRankPercentile: int = 0,
endSourceRankPercentile: int = 100,
isDuplicateFilter: str = "keepAll",
hasDuplicateFilter: str = "keepAll",
eventFilter: str = "keepAll"):
"""
create an article query using a complex query
@param query: an instance of CombinedQuery or BaseQuery to use to find articles that match the conditions
@param dataType: data type to search for. Possible values are "news" (news content), "pr" (PR content) or "blogs".
If you want to use multiple data types, put them in an array (e.g. ["news", "pr"])
@param minSentiment: what should be the minimum sentiment on the articles in order to return them (None means that we don't filter by sentiment)
@param maxSentiment: what should be the maximum sentiment on the articles in order to return them (None means that we don't filter by sentiment)
@param minSocialScore: at least how many times should the articles be shared on social media in order to return them
@param minFacebookShares: at least how many times should the articles be shared on Facebook in order to return them
@param startSourceRankPercentile: starting percentile of the sources to consider in the results (default: 0). Value should be in range 0-90 and divisible by 10.
@param endSourceRankPercentile: ending percentile of the sources to consider in the results (default: 100). Value should be in range 10-100 and divisible by 10.
@param isDuplicateFilter: some articles can be duplicates of other articles. What should be done with them. Possible values are:
"skipDuplicates" (skip the resulting articles that are duplicates of other articles)
"keepOnlyDuplicates" (return only the duplicate articles)
"keepAll" (no filtering, default)
@param hasDuplicateFilter: some articles are later copied by others. What should be done with such articles. Possible values are:
"skipHasDuplicates" (skip the resulting articles that have been later copied by others)
"keepOnlyHasDuplicates" (return only the articles that have been later copied by others)
"keepAll" (no filtering, default)
@param eventFilter: some articles describe a known event and some don't. This filter allows you to filter the resulting articles based on this criteria.
Possible values are:
"skipArticlesWithoutEvent" (skip articles that are not describing any known event in ER)
"keepOnlyArticlesWithoutEvent" (return only the articles that are not describing any known event in ER)
"keepAll" (no filtering, default)
"""
super(ComplexArticleQuery, self).__init__()
assert isinstance(query, (CombinedQuery, BaseQuery)), "query parameter was not a CombinedQuery or BaseQuery instance"
self._queryObj["$query"] = query.getQuery()
filter = {}
if dataType != "news":
filter["dataType"] = dataType
if minSentiment is not None:
filter["minSentiment"] = minSentiment
if maxSentiment is not None:
filter["maxSentiment"] = maxSentiment
if minSocialScore > 0:
filter["minSocialScore"] = minSocialScore
if minFacebookShares > 0:
filter["minFacebookShares"] = minFacebookShares
if startSourceRankPercentile != 0:
filter["startSourceRankPercentile"] = startSourceRankPercentile
if endSourceRankPercentile != 100:
filter["endSourceRankPercentile"] = endSourceRankPercentile
if isDuplicateFilter != "keepAll":
filter["isDuplicate"] = isDuplicateFilter
if hasDuplicateFilter != "keepAll":
filter["hasDuplicate"] = hasDuplicateFilter
if eventFilter != "keepAll":
filter["hasEvent"] = eventFilter
if len(filter) > 0:
self._queryObj["$filter"] = filter
class ComplexEventQuery(_QueryCore):
def __init__(self,
query: Union["BaseQuery", "CombinedQuery"],
minSentiment: Union[float, None] = None,
maxSentiment: Union[float, None] = None):
"""
create an event query using a complex query
@param query: an instance of CombinedQuery or BaseQuery to use to find events that match the conditions
"""
super(ComplexEventQuery, self).__init__()
assert isinstance(query, (CombinedQuery, BaseQuery)), "query parameter was not a CombinedQuery or BaseQuery instance"
filter = {}
if minSentiment is not None:
filter["minSentiment"] = minSentiment
if maxSentiment is not None:
filter["maxSentiment"] = maxSentiment
if len(filter) > 0:
self._queryObj["$filter"] = filter
self._queryObj["$query"] = query.getQuery()
class ComplexMentionQuery(_QueryCore):
def __init__(self,
query: Union["BaseQuery", "CombinedQuery"],
minSentiment: Union[float, None] = None,
maxSentiment: Union[float, None] = None,
minSentenceIndex: Union[int, None] = None,
maxSentenceIndex: Union[int, None] = None,
showDuplicates: bool = False):
"""
create a mention query using a complex query
@param query: an instance of CombinedQuery or BaseQuery to use to find events that match the conditions
@param minSentiment: the minimum sentiment of the mentions to return
@param maxSentiment: the maximum sentiment of the mentions to return
@param minSentenceIndex: the minimum sentence index of the mentions to return
@param maxSentenceIndex: the maximum sentence index of the mentions to return
"""
super(ComplexMentionQuery, self).__init__()
assert isinstance(query, (CombinedQuery, BaseQuery)), "query parameter was not a CombinedQuery or BaseQuery instance"
filter = {}
if minSentiment is not None:
filter["minSentiment"] = minSentiment
if maxSentiment is not None:
filter["maxSentiment"] = maxSentiment
if minSentenceIndex is not None:
filter["minSentenceIndex"] = minSentenceIndex
if maxSentenceIndex is not None:
filter["maxSentenceIndex"] = maxSentenceIndex
if showDuplicates:
filter["showDuplicates"] = showDuplicates
if len(filter) > 0:
self._queryObj["$filter"] = filter
self._queryObj["$query"] = query.getQuery()
|
[
"gleban@gmail.com"
] |
gleban@gmail.com
|
4f1582bbf56436afb92f7af0ff6c1f673aacefc3
|
d625191d67030c8008e3e60264ca0cfe7c0cb3d9
|
/test_rollsum.py
|
4274b65a958c8d4bc6318aa82d0f5e8c30644cf2
|
[
"MIT"
] |
permissive
|
pombredanne/camlipy
|
be809215e6aa562eb4e694fc40131b921dd94178
|
e17069e5609e5ca93baf7a484eb5975ab230d06f
|
refs/heads/master
| 2021-01-17T14:04:32.471174
| 2013-10-02T20:31:51
| 2013-10-02T20:31:51
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,278
|
py
|
# -*- coding: utf-8 -*-
__author__ = 'Thomas Sileo (thomas@trucsdedev.com)'
import random
from camlipy.rollsum import Rollsum, WINDOW_SIZE
def test_rollsum():
buf = []
for i in range(100000):
buf.append(random.randint(0, 255))
def rsum(offset, length):
""" Test function that returns Rollsum digest. """
rs = Rollsum()
for b in buf[offset:length]:
rs.roll(b)
return rs.digest()
sum1a = rsum(0, len(buf))
sum1b = rsum(1, len(buf))
assert sum1a == sum1b
sum2a = rsum(len(buf) - WINDOW_SIZE * 5 / 2, len(buf) - WINDOW_SIZE)
sum2b = rsum(0, len(buf) - WINDOW_SIZE)
assert sum2a == sum2b
sum3a = rsum(0, WINDOW_SIZE + 3)
sum3b = rsum(3, WINDOW_SIZE + 3)
assert sum3a == sum3b
def benchmark_rollsum():
bytes_size = 1024 * 1024 * 5
rs = Rollsum()
splits = 0
for i in range(bytes_size):
rs.roll(random.randint(0, 255))
if rs.on_split():
rs.bits()
splits += 1
every = int(bytes_size / splits)
print 'num splits: {0}; every {1} bytes.'.format(splits, every)
if __name__ == '__main__':
import time
start = time.time()
test_rollsum()
benchmark_rollsum()
end = time.time()
print start - end
|
[
"thomas.sileo@gmail.com"
] |
thomas.sileo@gmail.com
|
b5d487b81b641cc90591376e94929e2e5628c3a1
|
bb4d490ee0af38c02ff5ab324a69a47a5df58acc
|
/recomendr/wsgi.py
|
9dab3d4f4fcdc4d318faf3ee77b21612cced267f
|
[] |
no_license
|
courageousillumination/recomendr
|
e0c56a68fce3477ae365d0f8751bf15237e1ee5b
|
279d0571dd4560f788e50a32ac45a1a4086e0c50
|
refs/heads/master
| 2016-09-01T18:10:59.458408
| 2014-05-10T18:30:59
| 2014-05-10T18:30:59
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,428
|
py
|
"""
WSGI config for recomendr project.
This module contains the WSGI application used by Django's development server
and any production WSGI deployments. It should expose a module-level variable
named ``application``. Django's ``runserver`` and ``runfcgi`` commands discover
this application via the ``WSGI_APPLICATION`` setting.
Usually you will have the standard Django WSGI application here, but it also
might make sense to replace the whole Django WSGI application with a custom one
that later delegates to the Django one. For example, you could introduce WSGI
middleware here, or combine a Django application with an application of another
framework.
"""
import os
# We defer to a DJANGO_SETTINGS_MODULE already in the environment. This breaks
# if running multiple sites in the same mod_wsgi process. To fix this, use
# mod_wsgi daemon mode with each site in its own daemon process, or use
# os.environ["DJANGO_SETTINGS_MODULE"] = "recomendr.settings"
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "recomendr.settings")
# This application object is used by any WSGI server configured to use this
# file. This includes Django's development server, if the WSGI_APPLICATION
# setting points here.
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()
# Apply WSGI middleware here.
# from helloworld.wsgi import HelloWorldApplication
# application = HelloWorldApplication(application)
|
[
"tristanr93@gmail.com"
] |
tristanr93@gmail.com
|
f2b143296fbea3999a82fe232f7a8f0538481cb9
|
87921ae417ff1e47a086ce03747509666f9d1dd0
|
/ServerConsole/test/retstat.py
|
5a48298d0ef99fae9aa00beb0e705731f6a3f829
|
[] |
no_license
|
Demon-HY/monitor-history
|
f7e0ad0f0763a22d4afabc99ed049a634ba4790b
|
1c268d1704a87bd9369e93e5afb68e0dea6a3f59
|
refs/heads/master
| 2021-06-13T16:55:00.595005
| 2017-04-11T03:47:37
| 2017-04-11T03:47:37
| 75,525,738
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,269
|
py
|
# coding:utf8
# System Error
OK = "OK"
# 错误码：参数错误
ERR_BAD_PARAMS = "ERR_BAD_PARAMS"
# 错误码：无访问权限
ERR_FORBIDDEN = "ERR_FORBIDDEN"
# 错误码：非法JSON串
ERR_INVALID_JSON = "ERR_INVALID_JSON"
# 错误码：资源不存在
ERR_NOT_FOUND = "ERR_NOT_FOUND"
# 错误码：无法解析post数据
ERR_READ_POST_EXCEPTION = "ERR_READ_POST_EXCEPTION"
# 错误码：没有返回码
ERR_STAT_NOT_SET = "ERR_STAT_NOT_SET"
# 错误码：服务端异常
ERR_SERVER_EXCEPTION = "ERR_SERVER_EXCEPTION"
# 错误码：事件中断
ERR_EVENT_INTERRUPT = "ERR_EVENT_INTERRUPT"
# 错误码：用户没有登录
ERR_USER_NOT_LOGIN = "ERR_USER_NOT_LOGIN"
# 错误码：邮件队列已满
ERR_MAILBOX_FULL = "ERR_MAILBOX_FULL"
# 错误码：不支持该操作
ERR_OPERATION_NOT_SUPPORTED = "ERR_OPERATION_NOT_SUPPORTED"
# auth,user model
# 该账号已被使用
ERR_ACCOUNT_EXIST = "ERR_ACCOUNT_EXIST"
# 手机号已经被绑定
ERR_PHONE_ALREADY_BOUND = "ERR_PHONE_ALREADY_BOUND"
# 请不要重复发送验证码
ERR_SEND_CODE_FREQUENTLY = "ERR_SEND_CODE_FREQUENTLY"
# 验证码错误
ERR_CODE = "ERR_CODE"
# 清除用户数据失败
ERR_CLEAN_ACCOUNT_FAILED = "ERR_CLEAN_ACCOUNT_FAILED"
# 注册登录信息失败
ERR_ADD_LOGIN_ID_FAILED = "ERR_ADD_LOGIN_ID_FAILED"
# 账号不存在
ERR_NO_SUCH_ACCOUNT = "ERR_NO_SUCH_ACCOUNT"
# 用户不存在
ERR_USER_NOT_FOUND = "ERR_USER_NOT_FOUND"
# 用户信息损坏
ERR_USER_INFO_BROKEN = "ERR_USER_INFO_BROKEN"
# 密码错误
ERR_INVALID_PASSWORD = "ERR_INVALID_PASSWORD"
# 密码过期
ERR_PASSWORD_EXPIRED = "ERR_PASSWORD_EXPIRED"
# 非法账号类型
ERR_ILLEGAL_ACCOUNT_TYPE = "ERR_ILLEGAL_ACCOUNT_TYPE"
# 非法邮箱
ERR_ILLEGAL_EMAIL_ACCOUNT = "ERR_ILLEGAL_EMAIL_ACCOUNT"
# 非法手机号
ERR_ILLEGAL_PHONE_ACCOUNT = "ERR_ILLEGAL_PHONE_ACCOUNT"
# 用户还未登录
ERR_TOKEN_NOT_FOUND = "ERR_TOKEN_NOT_FOUND"
# 用户登录超时
ERR_TOKEN_EXPIRED = "ERR_TOKEN_EXPIRED"
# 验证码过期
ERR_VALIDATE_CODE_EXPIRED = "ERR_VALIDATE_CODE_EXPIRED"
# 验证码错误
ERR_INVALID_VALIDATE_CODE = "ERR_INVALID_VALIDATE_CODE"
# 登录的用户与新建token用户不为一个用户
ERR_TOKEN_UID_MISMATCHING = "ERR_TOKEN_UID_MISMATCHING"
# 错误码：用户已被锁定
ERR_USER_LOCKED = "ERR_USER_LOCKED"
|
[
"1764496637@qq.com"
] |
1764496637@qq.com
|
e4819429a7fe9df8fcb508e0a4e58e531c3b358e
|
c6d4fa98b739a64bb55a8750b4aecd0fc0b105fd
|
/ScanPi/QRbytes/472.py
|
cd01befc97225989650424096a854c59ae1dc148
|
[] |
no_license
|
NUSTEM-UK/Heart-of-Maker-Faire
|
de2c2f223c76f54a8b4c460530e56a5c74b65ca3
|
fa5a1661c63dac3ae982ed080d80d8da0480ed4e
|
refs/heads/master
| 2021-06-18T13:14:38.204811
| 2017-07-18T13:47:49
| 2017-07-18T13:47:49
| 73,701,984
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 94,948
|
py
|
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0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF,
0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF,
0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F,
0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F,
0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF,
0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF,
0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xFF, 0xFF, 0xF0,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF,
0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF,
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00,
0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0xFF,
0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF,
0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF,
0x00, 0x00, 0x00, 0xFF, 0xF0, 0x00, 0xFF, 0xFF, 0xFF, 0xFF,
0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00
]
|
[
"jonathan.sanderson@northumbria.ac.uk"
] |
jonathan.sanderson@northumbria.ac.uk
|
5cd9e9dd98ec55f0c9de426827164c6dd342b934
|
873e591baaede123face7c317e6e014df0366d65
|
/listeners/ADBCatAllListener.py
|
ce3e940144667dd926a4cc04f5e5d11ac9d9c00a
|
[] |
no_license
|
Lynazhang/UIDocMonkey
|
aa57521c86448242c12bc704b356e72e3ccfbd76
|
3fbc41b7c70b43851b2e74e5b32ac912e82d8ba4
|
refs/heads/master
| 2021-06-09T17:32:21.483718
| 2016-11-22T13:59:44
| 2016-11-22T13:59:44
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,660
|
py
|
import SocketServer
from subprocess import*
import json
from threading import Timer
class ADBCatAllListener(SocketServer.BaseRequestHandler):
"""
The RequestHandler class for our server.
It is instantiated once per connection to the server, and must
override the handle() method to implement communication to the
client.
"""
def handle(self):
# self.request is the TCP socket connected to the client
self.data = self.request.recv(10240)
self.data = self.data.strip()
print self.data
self.procs=[]
self.HandleMessage(self.data)
def HandleMessage(self,data):
try:
dicts=json.loads(data.strip())
print dicts
if "tag" in dicts:
tag=dicts["tag"]
if tag=="start":
command=dicts["command"]
filename=dicts["filename"]
duration=dicts["duration"]
proc=self.dumpLogcat(filename,command,duration)
except:
print "parse failed"
pass
def terminate(self,process):
if process.poll() is None:
try:
process.terminate()
except:
pass
def dumpLogcat(self,filename,command,duration):
print command
p = Popen(command, creationflags=CREATE_NEW_CONSOLE,stdout=PIPE, stderr=PIPE, bufsize=1, universal_newlines=True)
print "here"
timer = Timer(duration, self.terminate, args=[p])
timer.start()
f=file(filename,'w')
for line in iter(p.stdout.readline, ''):
f.write(line.strip()+"\n")
f.flush()
p.stdout.close()
p.wait()
timer.cancel()
'''
while True:
line = p.stdout.readline()
flag=self.readFlag()
print "found flag",flag
if flag:
print "ready to kill"
p.kill()
break
if not line:
break
if line.strip()!="":
f.write(line)
f.flush()
'''
return p
def dumpLogcatEvent(self):
return
if __name__ == "__main__":
HOST, PORT = "127.0.0.1", 10004
# Create the server, binding to localhost on port 9999
server = SocketServer.TCPServer((HOST, PORT), ADBCatAllListener)
# Activate the server; this will keep running until you
# interrupt the program with Ctrl-C
server.serve_forever()
|
[
"v-lzhani@microsoft.com"
] |
v-lzhani@microsoft.com
|
60d6cb2db006e20e4b18abeedfcd5b7a69a9801b
|
5d48aba44824ff9b9ae7e3616df10aad323c260e
|
/tree/653.two_sum_IV_input_is_a_BST.py
|
4ece9fd24ef54b435eb886456dcb70ac2d4e7d17
|
[] |
no_license
|
eric496/leetcode.py
|
37eab98a68d6d3417780230f4b5a840f6d4bd2a6
|
32a76cf4ced6ed5f89b5fc98af4695b8a81b9f17
|
refs/heads/master
| 2021-07-25T11:08:36.776720
| 2021-07-01T15:49:31
| 2021-07-01T15:49:31
| 139,770,188
| 3
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 940
|
py
|
"""
Given a Binary Search Tree and a target number, return true if there exist two elements in the BST such that their sum is equal to the given target.
Example 1:
Input:
5
/ \
3 6
/ \ \
2 4 7
Target = 9
Output: True
Example 2:
Input:
5
/ \
3 6
/ \ \
2 4 7
Target = 28
Output: False
"""
# Definition for a binary tree node.
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
# Solution 1:
class Solution:
def findTarget(self, root: TreeNode, k: int) -> bool:
target = set()
return self.dfs(root, k, target)
def dfs(self, root: TreeNode, k: int, target: int) -> bool:
if not root:
return False
if root.val in target:
return True
else:
target.add(k - root.val)
return self.dfs(root.left, k, target) or self.dfs(root.right, k, target)
|
[
"eric.mlengineer@gmail.com"
] |
eric.mlengineer@gmail.com
|
f3b5e09e66bafffac5eec9791d1a6b1d10af59e6
|
64ebf80fb795daab018241ee2933732866540d2a
|
/reservationapp/migrations/0004_alter_reservation_seat.py
|
e0c0c640e96a524778da1de1c7ad4c11ec3439fe
|
[] |
no_license
|
minwoo9629/ticketing_service
|
48248fb66e4cf0209d77224212d41c647dff6d05
|
2367dd3dd15a12e7ccf707ee1824d6b22662abcb
|
refs/heads/main
| 2023-08-14T16:41:32.092443
| 2021-09-24T13:18:34
| 2021-09-24T13:18:34
| 387,129,430
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 626
|
py
|
# Generated by Django 3.2.5 on 2021-08-11 17:36
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('concertapp', '0016_remove_seat_reserve'),
('reservationapp', '0003_auto_20210811_1608'),
]
operations = [
migrations.AlterField(
model_name='reservation',
name='seat',
field=models.ForeignKey(blank=True, limit_choices_to={'reservation': False}, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='reservation', to='concertapp.seat'),
),
]
|
[
"minwoo9629@gmail.com"
] |
minwoo9629@gmail.com
|
652a982f2c2c8f30b11e873185f76263a3ae85b2
|
0bc2f9fd2a8cf8acfb36e88b9fd489921b7afaa0
|
/resumes/forms.py
|
53217e956929e64f729c406117481db6bcac60d1
|
[] |
no_license
|
temitope3201/hng_resume_app
|
e83bf108be921602467b55e9934ee815f2e39f45
|
c1bfa43711d0fc5d0c82539522e42a7f857e3d32
|
refs/heads/main
| 2023-07-11T06:56:25.431978
| 2021-08-24T08:13:28
| 2021-08-24T08:13:28
| 398,298,694
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 170
|
py
|
from django import forms
from .models import Contact
class ContactForm(forms.ModelForm):
class Meta:
model = Contact
fields = ('email', 'message',)
|
[
"temitopeadebayo749@gmail.com"
] |
temitopeadebayo749@gmail.com
|
2a189c9890d4fe2943b93bd7d46bd3a23066fce2
|
c48c71b2f798361d6892d3bec88a077839366d31
|
/phy/test_scripts/tput/tput_test.py
|
56287bef55935f0f5536d2f582a2bf9d9a6689e4
|
[] |
no_license
|
wenh81/scatter-phy
|
5026d8fa6a38221e362f20c707f2b4d734c418ed
|
e9b1fec1eced5c356e753f79fd62567cca55aa02
|
refs/heads/master
| 2022-03-05T04:07:14.586517
| 2019-11-21T12:22:35
| 2019-11-21T12:22:35
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,937
|
py
|
import select
import socket
import time
import _thread
import threading
import getopt
import queue
import random
from time import sleep
import signal, os
import sys
sys.path.append('../../../')
sys.path.append('../../../communicator/python/')
from communicator.python.Communicator import Message
from communicator.python.LayerCommunicator import LayerCommunicator
import communicator.python.interf_pb2 as interf
PRB_VECTOR = [6, 15, 25, 50]
NOF_SLOTS_VECTOR = [1, 10, 25]
MCS_VECTOR = [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 31]
tx_exit_flag = False
def handler(signum, frame):
global tx_exit_flag
tx_exit_flag = True
def getExitFlag():
global tx_exit_flag
return tx_exit_flag
def kill_phy():
os.system("~/radio_api/stop.sh")
os.system("~/radio_api/kill_stack.py")
os.system("killall -9 trx")
os.system("killall -9 measure_throughput_fd_auto")
def start_phy(nof_phys, bw, center_freq, comp_bw):
cmd1 = "sudo ../../../build/phy/srslte/examples/trx -f " + str(center_freq) + " -E " + str(nof_phys) + " -B " + str(comp_bw) + " -p " + str(bw) + " &"
os.system(cmd1)
def start_tput_measurement(nof_prb, nof_slots, mcs, txgain, rxgain):
cmd1 = "sudo ../../../build/phy/srslte/examples/measure_throughput_fd_auto -b " + str(txgain) + " -g " + str(rxgain) + " -n " + str(nof_slots) + " -m " + str(mcs) + " -p " + str(nof_prb)
os.system(cmd1)
def start_scenario():
cmd1 = "colosseumcli rf start 8981 -c"
os.system(cmd1)
def save_files(nof_prb):
cmd1 = "mkdir dir_tput_prb_" + str(nof_prb)
os.system(cmd1)
cmd2 = "mv tput_prb_* dir_tput_prb_" + str(nof_prb)
os.system(cmd2)
cmd3 = "tar -cvzf" + " dir_tput_prb_" + str(nof_prb) + ".tar.gz" + " dir_tput_prb_" + str(nof_prb) + "/"
os.system(cmd3)
def get_bw_from_prb(nof_prb):
bw = 0
if(nof_prb == 6):
bw = 1400000
elif(nof_prb == 15):
bw = 3000000
elif(nof_prb == 25):
bw = 5000000
elif(nof_prb == 50):
bw = 10000000
else:
printf("Invalid number of PRB")
exit(-1)
return bw
def inputOptions(argv):
nof_prb = 25 # By dafult we set the number of resource blocks to 25, i.e., 5 MHz bandwidth.
mcs = 0 # By default MCS is set to 0, the most robust MCS.
txgain = 10 # By default TX gain is set to 10.
rxgain = 10 # By default RX gain is set to 10.
tx_slots = 1
tx_channel = 0
rx_channel = 0
run_scenario = False
center_freq = 2500000000
comp_bw = 40000000
nof_phys = 2
try:
opts, args = getopt.getopt(argv,"h",["help","bw=","mcs=","txgain=","rxgain=","txslots=","txchannel=","rxchannel=","runscenario","centerfreq=","compbw=","nofphys="])
except getopt.GetoptError:
help()
sys.exit(2)
for opt, arg in opts:
if opt in ("--help"):
sys.exit()
elif opt in ("--bw"):
nof_prb = int(arg)
elif opt in ("--mcs"):
mcs = int(arg)
elif opt in ("--txgain"):
txgain = int(arg)
elif opt in ("--rxgain"):
rxgain = int(arg)
elif opt in ("--txslots"):
tx_slots = int(arg)
elif opt in ("--txchannel"):
tx_channel = int(arg)
elif opt in ("--rxchannel"):
rx_channel = int(arg)
elif opt in ("--runscenario"):
run_scenario = True
elif opt in ("--centerfreq"):
center_freq = int(arg)
elif opt in ("--compbw"):
comp_bw = int(arg)
elif opt in ("--nofphys"):
nof_phys = int(arg)
return nof_prb, mcs, txgain, rxgain, tx_slots, tx_channel, rx_channel, run_scenario, center_freq, comp_bw, nof_phys
if __name__ == '__main__':
# Set the signal handler.
signal.signal(signal.SIGINT, handler)
nof_prb, mcs, txgain, rxgain, tx_slots, tx_channel, rx_channel, run_scenario, center_freq, comp_bw, nof_phys = inputOptions(sys.argv[1:])
if(run_scenario == True):
start_scenario()
time.sleep(10)
for prb_idx in range(0,len(PRB_VECTOR)):
nof_prb = PRB_VECTOR[prb_idx]
bw = get_bw_from_prb(nof_prb)
for mcs_idx in range(0,len(MCS_VECTOR)):
for nof_slots_idx in range(0,len(NOF_SLOTS_VECTOR)):
# Make sure PHY is not running.
kill_phy()
time.sleep(5)
# Start PHY.
start_phy(nof_phys, bw, center_freq, comp_bw)
time.sleep(15)
nof_slots = NOF_SLOTS_VECTOR[nof_slots_idx]
mcs = MCS_VECTOR[mcs_idx]
start_tput_measurement(nof_prb, nof_slots, mcs, txgain, rxgain)
if(getExitFlag() == True):
exit(0)
if(getExitFlag() == True):
exit(0)
# Save files.
save_files(nof_prb)
if(getExitFlag() == True):
exit(0)
|
[
"zz4fap@users.noreply.github.com"
] |
zz4fap@users.noreply.github.com
|
479053d6aa7c88f3da69053c1db32172e48dadc4
|
af1723ba6a09cc116c1a7697c990bcf3349dfa6e
|
/Python book/Chapter_8/even.py
|
ffc65a4aea62740f873797127a73b7d8a11f5b2d
|
[] |
no_license
|
ballib/SC-T-111-PROG
|
1eb7233c985ddb8330a604bb3191f64147ea2c78
|
24f63aa1e1a7dc7e891f3ad916039f39da58d5c3
|
refs/heads/master
| 2020-12-05T03:38:46.335547
| 2019-01-10T11:07:12
| 2019-01-10T11:07:12
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 599
|
py
|
def evens(n):
evens_list = []
for i in range(1,n+1):
evens_list.append(2*i)
return evens_list
# or
def evens2(n):
return [2*i for i in range(1, n+1)]
print(evens(5))
print(evens2(5))
#######################################
def mirror(pair):
return pair[1], pair[0]
first, second = mirror((2,3))
mirror((2,3))
print(first)
print(second)
print(first,second)
a_tuple = mirror((2,3))
print(a_tuple)
########################################
def func1(param_required, param_default = 2):
print(param_required, param_default)
print(func1(5,6))
print(func1(5))
|
[
"jonio18@ru.is"
] |
jonio18@ru.is
|
d7b88364e46a9b7f3dd0506ed9c5415e3564bb45
|
5fae31c2aa1e47f82048e9856778efc35106e248
|
/django/orm/orm/settings.py
|
3ecd159fd73b5f3d98d3dd9a05e9eea90a1f80f3
|
[] |
no_license
|
Eomazing/TIL-c9
|
989f208cf3947ef32eac9a68704d70d8aa1b2330
|
bd1e2361d3ecfc677b6851edf6fc9b49d9e74951
|
refs/heads/master
| 2020-04-17T17:18:05.943544
| 2019-05-09T10:48:10
| 2019-05-09T10:48:10
| 166,777,139
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,151
|
py
|
"""
Django settings for orm project.
Generated by 'django-admin startproject' using Django 2.1.8.
For more information on this file, see
https://docs.djangoproject.com/en/2.1/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/2.1/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '36%1b(^zz076oalcr!$k%mz*0j6e6vd*bil73=!yz54_7fdw$)'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'django_extensions',
'crud',
'onetomany',
'manytomany',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'orm.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'orm.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.1/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/2.1/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.1/howto/static-files/
STATIC_URL = '/static/'
|
[
"amuse0701@gmail.com"
] |
amuse0701@gmail.com
|
b439d7638443722eacd39df345093a0d8b47adfa
|
ded67d2ddc604fad9ff53caf33ffa69ccc229482
|
/bin/easy_install-3.7
|
ca6e4985a433e0a369c96fb8b7b1081627f8a336
|
[] |
no_license
|
CeliaGMqrz/wagtail
|
ed5c3e6ca336e6de7361d9f4aae386f69bed36ad
|
1eddebb178630119dcfcb6000cb4e2b732d823f5
|
refs/heads/main
| 2023-03-04T03:14:14.546619
| 2021-02-17T20:51:53
| 2021-02-17T20:51:53
| 332,208,660
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 255
|
7
|
#!/home/celiagm/venv/wagtail/bin/python3
# -*- coding: utf-8 -*-
import re
import sys
from setuptools.command.easy_install import main
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(main())
|
[
"celiagm@debian"
] |
celiagm@debian
|
cf59517324943219c2e5d63407b2866a634428cf
|
981901751c35eabaef52e263900d10ff22936830
|
/autoSvn.py
|
3bc4e8fa56756b2fd50f3d5bf37a861f17db5844
|
[] |
no_license
|
tsuyuzaki00/subversionScripts
|
573ba23fb75d9e15a09ebb916b4ccbe7bd04676a
|
2414f771c2483b9452b4d4c5cc217b9d124f31e1
|
refs/heads/main
| 2023-02-01T22:13:51.896457
| 2020-12-17T02:02:43
| 2020-12-17T02:02:43
| 321,924,993
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,831
|
py
|
import os
import subprocess
import svn.local
def kameSvnAdd(_path):
commit_command = [
"TortoiseProc",
"/command:add",
"/path:" + _path,
"/closeforlocal:0"
]
subprocess.call(commit_command)
def kameSvnCommit(_path):
message = "testUpdate_to_USD"
commit_command = [
"TortoiseProc",
"/command:commit",
"/logmsg:" + message,
"/path:" + _path,
"/command:update"
"/closeOnend:0"
]
subprocess.call(commit_command)
def svnUpdate(_path):
_path = "D:/Shotgun_work/new_angle_test"
os.chdir(_path)
subprocess.call('svn up')
def usdAdd(_path):
svlocal = svn.local.LocalClient(_path)
path = _path
result = svlocal.run_command("status", [path, "--non-recursive"])
while(True):
result = svlocal.run_command("status", [path, "--non-recursive"])
if(result[0] == "" or result[0][0] == "A"):
break
path, d = os.path.split(path)
os.chdir(_path)
files = os.listdir(_path)
usdfiles = [file for file in files if '.usd' in file]
for usd in usdfiles:
subprocess.call('svn add ' + usd)
def svnDCCtoUSD(_path):
svlocal = svn.local.LocalClient(_path)
path = _path
result = svlocal.run_command("status", [path, "--non-recursive"])
while(True):
result = svlocal.run_command("status", [path, "--non-recursive"])
if(result[0] == "" or result[0][0] == "A"):
break
path, d = os.path.split(path)
os.chdir(_path)
message = "Update_to_USD"
subprocess.call("svn ci -m " + message)
"""
#Run scripts
_path = "D:/Shotgun_work/new_angle_test/assets/01-Character/asset_test000/MDL/work/maya"
kameSvnAdd(_path)
kameSvnCommit(_path)
svnUpdate(_path)
usdAdd(_path)
svnDCCtoUSD(_path)
"""
|
[
"tsuyuzaki.tatsuya@engi-st.jp"
] |
tsuyuzaki.tatsuya@engi-st.jp
|
f1bfe5de0e26671054c332bdfc93d2f0d9d4265e
|
53fab060fa262e5d5026e0807d93c75fb81e67b9
|
/backup/user_070/ch74_2020_04_06_14_56_45_688915.py
|
fbd6fc22f27f23767e365de5db1099f9b9558694
|
[] |
no_license
|
gabriellaec/desoft-analise-exercicios
|
b77c6999424c5ce7e44086a12589a0ad43d6adca
|
01940ab0897aa6005764fc220b900e4d6161d36b
|
refs/heads/main
| 2023-01-31T17:19:42.050628
| 2020-12-16T05:21:31
| 2020-12-16T05:21:31
| 306,735,108
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 197
|
py
|
def conta_bigramas(x):
dicionario = {}
for i in range(len(x)-1):
dicionario[x[i],x[i+1]] = 0
for i in range(len(x)-1):
dicionario[x[i],x[i+1]] += 1
return dicionario
|
[
"you@example.com"
] |
you@example.com
|
00ae17b2c630ccf0d4036a300ee15ed0a9356121
|
4e3c976773526fd610d64ffb83589bccfaee5e68
|
/sponge-app/sponge-app-demo-service/sponge/sponge_demo_depending.py
|
ff40131a936612f5da6d6cd33534a1a8234f44d8
|
[
"Apache-2.0"
] |
permissive
|
softelnet/sponge
|
2313d2328953fcff49a002e727bb803757870627
|
7190f23ae888bbef49d0fbb85157444d6ea48bcd
|
refs/heads/master
| 2022-10-28T16:19:55.619882
| 2021-09-16T19:50:08
| 2021-09-16T19:50:08
| 95,256,030
| 10
| 2
|
Apache-2.0
| 2022-10-04T23:55:09
| 2017-06-23T20:58:49
|
Java
|
UTF-8
|
Python
| false
| false
| 2,884
|
py
|
"""
Sponge Knowledge Base
Demo
"""
class DependingArgumentsAction(Action):
def onConfigure(self):
self.withLabel("Depending arguments")
self.withArgs([
StringType("continent").withLabel("Continent").withProvided(ProvidedMeta().withValueSet()),
StringType("country").withLabel("Country").withProvided(ProvidedMeta().withValueSet().withDependency("continent")),
StringType("city").withLabel("City").withProvided(ProvidedMeta().withValueSet().withDependency("country")),
StringType("river").withLabel("River").withProvided(ProvidedMeta().withValueSet().withDependency("continent")),
StringType("weather").withLabel("Weather").withProvided(ProvidedMeta().withValueSet())
]).withResult(StringType().withLabel("Sentences"))
self.withFeatures({"icon":"flag", "showClear":True, "showCancel":True})
def onCall(self, continent, country, city, river, weather):
return "There is a city {} in {} in {}. The river {} flows in {}. It's {}.".format(city, country, continent, river, continent, weather.lower())
def onInit(self):
self.countries = {
"Africa":["Nigeria", "Ethiopia", "Egypt"],
"Asia":["China", "India", "Indonesia"],
"Europe":["Russia", "Germany", "Turkey"]
}
self.cities = {
"Nigeria":["Lagos", "Kano", "Ibadan"],
"Ethiopia":["Addis Ababa", "Gondar", "Mek'ele"],
"Egypt":["Cairo", "Alexandria", "Giza"],
"China":["Guangzhou", "Shanghai", "Chongqing"],
"India":["Mumbai", "Delhi", "Bangalore"],
"Indonesia":["Jakarta", "Surabaya", "Medan"],
"Russia":["Moscow", "Saint Petersburg", "Novosibirsk"],
"Germany":["Berlin", "Hamburg", "Munich"],
"Turkey":["Istanbul", "Ankara", "Izmir"]
}
self.rivers = {
"Africa":["Nile", "Chambeshi", "Niger"],
"Asia":["Yangtze", "Yellow River", "Mekong"],
"Europe":["Volga", "Danube", "Dnepr"]
}
def onProvideArgs(self, context):
if "continent" in context.provide:
context.provided["continent"] = ProvidedValue().withValueSet(["Africa", "Asia", "Europe"])
if "country" in context.provide:
context.provided["country"] = ProvidedValue().withValueSet(self.countries.get(context.current["continent"], []))
if "city" in context.provide:
context.provided["city"] = ProvidedValue().withValueSet(self.cities.get(context.current["country"], []))
if "river" in context.provide:
context.provided["river"] = ProvidedValue().withValueSet(self.rivers.get(context.current["continent"], []))
if "weather" in context.provide:
context.provided["weather"] = ProvidedValue().withValueSet(["Sunny", "Cloudy", "Raining", "Snowing"])
|
[
"marcin.pas@softelnet.com"
] |
marcin.pas@softelnet.com
|
9c71981567308ad84f8cdd6d9663bb32cd4dd6f4
|
bca9c2fa3c4c3d06dd612280ce39090a9dfab9bd
|
/neekanee/neekanee_solr/solr_query_builder.py
|
bb3792600dc6a9c0af8eefbc4cd05bff2fbb4fb6
|
[] |
no_license
|
thayton/neekanee
|
0890dd5e5cf5bf855d4867ae02de6554291dc349
|
f2b2a13e584469d982f7cc20b49a9b19fed8942d
|
refs/heads/master
| 2021-03-27T11:10:07.633264
| 2018-07-13T14:19:30
| 2018-07-13T14:19:30
| 11,584,212
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 5,806
|
py
|
KM_PER_MILE = 1.61
class SOLRQueryBuilder():
"""
Build a SOLR query given a GET QueryDict for a job search.
"""
def __init__(self):
self.qdict = {}
#
# Mapping of refine search query parameter names to SOLR doc
# field names. All refine search query parameters are implemented
# as filter queries. For each param in GET from the left column
# below, we add a new filter query using the field name in the
# right column and value GET[param].
#
self.refine_search_fq = {
#
# param SOLR field name
# ----- ---------------
'tld': 'tld',
'title': 'title',
'company': 'company_name',
'size': 'company_size',
'tags': 'company_tags',
'ltags': 'company_location_tags',
'awards': 'company_awards',
'vacation': 'vacation_year_1',
'country': 'country',
'state': 'state',
'city': 'city',
}
def add_fq(self, filt, val):
if filt != 'vacation_year_1':
new_fq = '%s:"%s"' % (filt,val)
else:
new_fq = '%s:%s' % (filt,val)
if self.qdict.has_key('fq'):
self.qdict['fq'].append(new_fq)
else:
self.qdict['fq'] = [new_fq]
def build_query(self, GET):
"""
GET : QueryDict object for an HTTP GET request
"""
self.qdict['q'] = '{!q.op=AND}' + GET.get('q', '*:*')
self.qdict['wt'] = 'json'
if 'lat' in GET and 'lng' and GET:
self.qdict['fq'] = [ '{!bbox}' ]
self.qdict['sfield'] = 'latlng'
self.qdict['pt'] = '%.2f,%.2f' % (float(GET['lat']),float(GET['lng']))
self.qdict['d'] = '%.2f' % (float(GET['radius']) * KM_PER_MILE)
for parm,filt in self.refine_search_fq.items():
val = GET.get(parm, None)
if val is None:
continue
if parm == 'tags' or parm == 'ltags' or parm == 'awards': # multivalued
for v in val.split():
self.add_fq(filt, v)
elif parm == 'vacation':
self.add_fq(filt, '[%d TO %d]' % (int(val), int(val)+4))
else:
self.add_fq(filt, val)
return self.qdict
class SOLRJobSearchQueryBuilder(SOLRQueryBuilder):
def __init__(self, items_per_page):
SOLRQueryBuilder.__init__(self)
self.items_per_page = items_per_page
#
# Pararms specific to job search query with faceting for the
# sidebar. The state facet field is set to 51 so that all of
# the states will show up in the map (and not just 10 of them).
#
params = {
'fl': 'id,title,url,url_data,company_id,company_name,company_ats,company_jobs_page_url,city,state,country',
'facet': 'true',
'facet.field': ['country', 'state', 'city', 'tld', 'company_size', 'company_name', 'company_tags', 'company_location_tags', 'company_awards'],
'facet.mincount': '1',
'facet.limit': '10',
'f.company_tags.facet.limit': '32',
'f.country.facet.limit': '200',
'f.state.facet.limit': '51',
'facet.range': 'vacation_year_1',
'facet.range.start': '10',
'facet.range.end': '50',
'facet.range.gap': '5',
'hl': 'true',
'hl.fl': 'desc',
'hl.snippets': 2,
'hl.alternateField': 'desc',
'hl.maxAlternateFieldLength': '210',
'rows': '%d' % self.items_per_page
}
self.qdict.update(params)
def build_query(self, GET):
page_number = int(GET.get('page', '1'))
self.qdict.update({'start': '%d' % (self.items_per_page * (page_number - 1))})
return SOLRQueryBuilder.build_query(self, GET)
class SOLRCompanyFacetQueryBuilder(SOLRQueryBuilder):
def __init__(self):
SOLRQueryBuilder.__init__(self)
params = {
'fl': 'id',
'facet': 'true',
'facet.field': ['country', 'state', 'city', 'tld', 'company_size', 'company_tags', 'company_location_tags', 'company_awards', 'company_id'],
'facet.mincount': '1',
'facet.limit': '10',
'facet.range': 'vacation_year_1',
'facet.range.start': '10',
'facet.range.end': '50',
'facet.range.gap': '5',
'f.company_tags.facet.limit': '32',
'f.country.facet.limit': '200',
'f.state.facet.limit': '51',
'f.company_id.facet.limit': '-1'
}
self.qdict.update(params)
def build_query(self, GET):
return SOLRQueryBuilder.build_query(self, GET)
class SOLRLocationFacetQueryBuilder(SOLRQueryBuilder):
def __init__(self):
SOLRQueryBuilder.__init__(self)
params = {
'fl': 'id',
'facet': 'true',
'facet.field': ['country', 'state', 'city', 'tld', 'company_size', 'company_name', 'company_tags', 'company_location_tags', 'company_awards'],
'facet.mincount': '1',
'facet.limit': '10',
'facet.range': 'vacation_year_1',
'facet.range.start': '10',
'facet.range.end': '50',
'facet.range.gap': '5',
'f.company_tags.facet.limit': '32',
'f.country.facet.limit': '200',
'f.state.facet.limit': '60',
'f.city.facet.limit': '-1'
}
self.qdict.update(params)
def build_query(self, GET):
return SOLRQueryBuilder.build_query(self, GET)
class SOLRJobTitleFacetQueryBuilder(SOLRQueryBuilder):
pass
|
[
"thayton@neekanee.com"
] |
thayton@neekanee.com
|
89e8d4c866269cd3f51dddc34d7b5e3cf06252a1
|
8993c99a50ce8813c53d6e49ac524f9ca9e5843c
|
/setup.py
|
b4098b433855c8d1114e948eab338decdcc08ccf
|
[
"BSD-2-Clause"
] |
permissive
|
thisfred/val
|
2b84d5c8c0bf704385e5f101bad6c8b8c14e6aae
|
7bbe4d892d74cc5c1bc3c9345e938f9f8f6e658f
|
refs/heads/master
| 2021-01-21T11:45:20.983710
| 2019-08-12T21:06:59
| 2019-08-12T21:06:59
| 11,887,783
| 7
| 0
| null | 2015-04-12T16:58:57
| 2013-08-05T01:28:28
|
Python
|
UTF-8
|
Python
| false
| false
| 1,516
|
py
|
"""
val: A validator for arbitrary python objects.
Copyright (c) 2013-2015
Eric Casteleijn, <thisfred@gmail.com>
"""
from setuptools import setup
import os
import re
def find_version(*file_paths):
"""Get version from python file."""
with open(os.path.join(os.path.dirname(__file__),
*file_paths)) as version_file:
contents = version_file.read()
version_match = re.search(
r"^__version__ = ['\"]([^'\"]*)['\"]", contents, re.M)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
HERE = os.path.abspath(os.path.dirname(__file__))
setup(
name='val',
version=find_version('val/__init__.py'),
author='Eric Casteleijn',
author_email='thisfred@gmail.com',
description='Python object validator',
license='BSD',
keywords='validation validators',
url='http://github.com/thisfred/val',
packages=['val'],
long_description=open('README.rst').read(),
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'Topic :: Software Development :: Libraries',
'License :: OSI Approved :: BSD License',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4'])
|
[
"ec@trapit.com"
] |
ec@trapit.com
|
492d57c20836f33c2380017662aa3dbd57fd1f04
|
21e5bbc1888ca85f68e6d511f222f9e94746632d
|
/ai/AlgoritmoGenetico.py
|
3be622e8f3bfad9204ac3e370e488daea09ee837
|
[] |
no_license
|
fgsl/classes
|
83614cc5ee654aa484a0bfd5ea91aaf97f91a282
|
e41e103beafa8b68c011c4c96486a82e47d12dd7
|
refs/heads/master
| 2020-06-05T21:15:39.342214
| 2020-03-11T17:49:12
| 2020-03-11T17:49:12
| 192,548,182
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,088
|
py
|
# coding: utf-8
import random
class AlgoritmoGenetico:
tamanhoDaPopulacao = 0
regras = None
maximoDeIteracoes = 0
def __init__(self, tamanhoDaPopulacao, regras, maximoDeIteracoes):
self.tamanhoDaPopulacao = tamanhoDaPopulacao
self.regras = regras
self.maximoDeIteracoes = maximoDeIteracoes
def executar(self):
# inicia população aleatoriamente
populacao = [0] * self.tamanhoDaPopulacao
for i,v in enumerate(populacao):
populacao[i] = self.novoIndividuo()
for i in range(0, self.maximoDeIteracoes):
print "Iteração " + str(i) + "\n"
individuosDaPopulacao = " ".join([str(elemento) for elemento in populacao])
print "População: " + individuosDaPopulacao + "\n"
novaPopulacao = []
for j,v in enumerate(populacao):
self.buscarPeloMelhorIndividuo(populacao[j])
novaPopulacao.append(populacao[j])
if novaPopulacao == []:
for j in enumerate(populacao):
populacao[j] = self.novoIndividuo()
while len(novaPopulacao) < self.tamanhoDaPopulacao:
novaPopulacao.append(self.crossover(populacao))
for j in enumerate(novaPopulacao):
novaPopulacao[j] = self.mutacao(novaPopulacao[j])
populacao = novaPopulacao
melhorIndividuo = None
for individuo in populacao:
self.buscarPeloMelhorIndividuo(individuo)
if melhorIndividuo == null:
print "Não obteve êxito \n"
def mutacao(self, individuo):
if random.randint( 0, 10 ) % 2 == 0:
individuo = self.novoIndividuo()
return individuo
def crossover(self, populacao):
return self.regras.crossover(populacao, self.regras.nvalores)
def novoIndividuo(self):
individuo = []
for i in range(0, self.regras.nvalores):
individuo.append(self.regras.randomValue())
return individuo
def buscarPeloMelhorIndividuo(self, individuo):
melhorIndividuo = self.regras.obterMelhorIndividuo(individuo)
if melhorIndividuo != None:
print "\n" + ('=' * 80)
print "\nMelhor solução: " + self.regras.mostrarIndividuo(melhorIndividuo) + "\n"
print "\n" + ('=' * 80) + "\n"
exit()
return melhorIndividuo
|
[
"flavio.lisboa@fgsl.eti.br"
] |
flavio.lisboa@fgsl.eti.br
|
8bc823c166c4a65c4048e30e2d7438e795a32306
|
018d804d6b53cc544e0adf8c38656bf27152706c
|
/ucsd_catalog_order.py
|
ed744750f3c2affb71f43eccdfbf1a19bb0c13f8
|
[] |
no_license
|
luisroco/cisco_cloud
|
c664520eb1021c7b36577a08d23dbf1b8dd7bd75
|
6bbf7c4f0c0af47860170835cfebc924f1b4c867
|
refs/heads/master
| 2021-01-09T20:11:19.048918
| 2017-02-07T19:06:58
| 2017-02-07T19:06:58
| 81,242,442
| 0
| 0
| null | 2017-02-07T18:53:53
| 2017-02-07T18:53:53
| null |
UTF-8
|
Python
| false
| false
| 3,208
|
py
|
#! /usr/bin/env python
'''
Command Line Utility to order a Catalog option
'''
import requests
import json
from ucsd_library import catalog_order
if __name__ == '__main__':
import sys
from pprint import pprint
from argparse import ArgumentParser, FileType
p = ArgumentParser()
p.add_argument('catalog', # Name stored in namespace
metavar = 'UCSD Catalog', # Arguement name displayed to user
help = 'The UCSD Catalog to order',
type = str
)
p.add_argument('-v', '--vdc', # Name stored in namespace
metavar = 'UCSD VDC', # Arguement name displayed to user
help = 'The UCSD VDC to place the cVM in',
type = str
)
p.add_argument('-c', '--comment', # Name stored in namespace
metavar = 'UCSD Comment', # Arguement name displayed to user
help = 'The comment to record - default blank',
type = str, default=""
)
p.add_argument('-g', '--group', # Name stored in namespace
metavar = 'UCSD Group', # Arguement name displayed to user
help = 'The group to order on behalf of',
type = str, default=""
)
p.add_argument('-n', '--vmname', # Name stored in namespace
metavar = 'UCSD VMname', # Arguement name displayed to user
help = 'The VM Name or prefix',
type = str, default=""
)
p.add_argument('--vcpus', # Name stored in namespace
metavar = 'vCPU Count', # Arguement name displayed to user
help = 'The number of vCPUs. Only used if vDC allows',
type = str, default="0"
)
p.add_argument('--vram', # Name stored in namespace
metavar = 'vRAM Count', # Arguement name displayed to user
help = 'The amount of vRAM. Only used if vDC allows',
type = str, default="0"
)
p.add_argument('--datastores', # Name stored in namespace
metavar = 'Datastore details', # Arguement name displayed to user
help = 'The datastore details. Only used if vDC allows.',
type = str, default=""
)
p.add_argument('--vnics', # Name stored in namespace
metavar = 'vNIC Details', # Arguement name displayed to user
help = 'The details for vNICS. Only used if vDC allows',
type = str, default=""
)
ns = p.parse_args()
result = catalog_order(ns.catalog, ns.vdc, ns.group, ns.comment, ns.vmname, ns.vcpus, ns.vram, ns.datastores, ns.vnics)
pprint (result)
|
[
"hank.preston@gmail.com"
] |
hank.preston@gmail.com
|
c8bea8e9e2f916ff8d8abe5acd8693635d3a3f4f
|
f2bd2a3c4d8d48341cc96e7842020dd5caddff8e
|
/archive/DUCS-MCA-Batch-2017-2020/DU-PG-2018-2nd-sem/PGmca.py
|
fa2ab42fe2316ce7c0a48373a06c343fb8a0bde8
|
[
"MIT"
] |
permissive
|
jatin69/du-result-fetcher
|
ab51684bfa9c52ffcd45edf0d9d6784f1e6fd28e
|
4106810cc06b662ba53acd5853b56c865f39f1a4
|
refs/heads/master
| 2022-12-09T07:08:25.614765
| 2022-12-01T12:56:02
| 2022-12-01T12:56:02
| 118,005,826
| 7
| 0
|
MIT
| 2022-12-01T12:56:03
| 2018-01-18T16:08:03
|
Python
|
UTF-8
|
Python
| false
| false
| 9,043
|
py
|
"""
DU MCA 2018 2nd sem
"""
import sys
import requests
from bs4 import BeautifulSoup
CONST_VIEWSTATE = """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"""
CONST_EVENTVALIDATION = """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"""
college_sgpa_list = []
dduc= []
# s = 1
# e = 48
# for i in range(1,2):
# if(i<10):
# i = '0' + str(i)
# el = '17245' + str(i)
# dduc.append(el)
# print(dduc)
r= requests.get('http://duexam.du.ac.in/RSLT_MJ2018/Students/List_Of_Students.aspx?StdType=REG&ExamFlag=PG_SEMESTER_2Y&CourseCode=823&CourseName=(P.G)-%20MASTER%20OF%20COMPUTER%20APPLICATION%20(M.C.A.)&Part=I&Sem=II')
soup = BeautifulSoup(r.text, 'html.parser')
students_table = soup.find("table", {"rules": "all"})
data = []
all_students = students_table.find_all('tr')
for student in all_students:
cols = student.find_all('td')
cols = [ele.text.strip() for ele in cols]
data.append([ele for ele in cols if ele]) # Get rid of empty values
data[0] = ['sno','srollno','sname','sfathername']
data.pop(0)
dduc = data
#print(*dduc,sep="\n")
for VAR_stud in dduc:
VAR_rollno = VAR_stud[1]
payload = {
'ddlcollege' : '234',
'txtrollno' : VAR_rollno,
'btnsearch': 'Print+Score+Card',
'__EVENTTARGET' : '',
'__EVENTARGUMENT' : '',
'__LASTFOCUS':'',
'__VIEWSTATE': CONST_VIEWSTATE,
'__EVENTVALIDATION': CONST_EVENTVALIDATION
}
soup = None
while(soup == None):
# print('trying')
r = requests.post("http://duexam.du.ac.in/RSLT_MJ2018/Students/Combine_GradeCard.aspx", data=payload)
# print(r.text)
soup = BeautifulSoup(r.text, 'html.parser')
if(soup==None):
continue
# print(soup.title.string)
if(soup.title.string == "Runtime Error"):
soup = None
continue
# writing result to html file
for img in soup.find_all('img'):
img.decompose()
VAR_filename = "htmlsavemca/" + VAR_rollno + '.html'
with open(VAR_filename, "w") as file:
file.write(str(soup))
sgpa_table = soup.find("table", {"id": "gvrslt"})
# print(sgpa_table)
if(sgpa_table == None ):
continue
xrows = sgpa_table.findAll('tr')
sgpa_row = xrows[2].find_all('td')
m = sgpa_row[1].text
# print([VAR_rollno, int(m) ])
name = VAR_stud[2]
college_sgpa_list.append([VAR_rollno, name, int(m) ])
college_sgpa_list.sort(key = lambda x : x[2], reverse=True)
#print(college_sgpa_list)
with open('DU-PG-MCA-2nd-sem-Result.txt','w') as f:
print('{0:<5} {1:10} {2:21} {3:5} {4:7}'.format("S.No","Roll No.","Name","Marks","Percentage"), file=f)
for i,marks in enumerate(college_sgpa_list):
print('{0:<5} {1:10} {2:21} {3:5} {4:7}'.format(i+1, marks[0], marks[1], marks[2], float(marks[2]/5)),file=f)
|
[
"jatinrohilla69@gmail.com"
] |
jatinrohilla69@gmail.com
|
5616b42ddb8bebe817060b5cb8acfdce3c667372
|
7776fce3e9ee1da84ea299a757905c3cc6f2ada7
|
/stockindex/admin.py
|
83ef09b6f16532c4aad99c45dbfcf29213bfd46c
|
[] |
no_license
|
krystian-warzocha/PythonZaliczenie
|
c0852bfdd30456c66ea431a20f5d8969cca493af
|
e2b551fd53e559f3ca36826b169775257d2ff756
|
refs/heads/master
| 2021-01-10T07:59:31.918144
| 2016-03-28T19:42:11
| 2016-03-28T19:42:11
| 54,917,864
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 133
|
py
|
from django.contrib import admin
from .models import StockIndex, Equity
admin.site.register(StockIndex)
admin.site.register(Equity)
|
[
"kwarzocha@sigma.ug.edu.pl"
] |
kwarzocha@sigma.ug.edu.pl
|
78dafda26133ed996d721c0ceffcb533ef977b3b
|
afdd3c8bb99a6351f958c62eb7b8d7dbe0c8fe48
|
/TextCNN/loader.py
|
75e50b85dbad566b44a5945f2e5cdf4d603ddd82
|
[] |
no_license
|
JingfengYang/PTEexperiments
|
9be5aead7f7e9652f3d990816e30e4f7fd23d4c7
|
0265638a34c238850dd52b96b5452e9633b0ce43
|
refs/heads/master
| 2020-09-05T10:40:40.263354
| 2019-11-18T04:15:24
| 2019-11-18T04:15:24
| 220,074,779
| 3
| 5
| null | 2019-11-18T02:21:25
| 2019-11-06T19:34:04
|
JavaScript
|
UTF-8
|
Python
| false
| false
| 3,318
|
py
|
import os
import re
import random
import numpy as np
import pickle
import sys
import torch
from utils import read_word_embeds
from torch.utils.data import Dataset, DataLoader
class TextDataset(Dataset):
def __init__(self, dataset, prc='', test=False, wo_unlabel=False):
_extend = '.without_unlabel' if wo_unlabel else ''
if len(prc) > 0:
prc = '.' + prc
else:
assert(not wo_unlabel)
# Train files
train_label_file = 'data/%s/label_train%s.txt' % (dataset, prc)
train_label_file = os.path.join('..', train_label_file)
train_text_file = 'data/%s/text_train.txt' % (dataset)
train_text_file = os.path.join('..', train_text_file)
# Test files
test_label_file = 'data/%s/label_test.txt' % (dataset)
test_label_file = os.path.join('..', test_label_file)
test_text_file = 'data/%s/text_test.txt' % (dataset)
test_text_file = os.path.join('..', test_text_file)
# Word embedings
emb_file = '%s_workspace%s/word.emb' % (dataset, prc+_extend)
emb_file = os.path.join('..', emb_file)
# Unused directories
sent_ebd_file = '%s_workspace%s/text.emb' % (dataset, prc)
sent_ebd_file = os.path.join('..', sent_ebd_file)
all_text_file = 'data/%s/text_all.txt' % (dataset)
all_text_file = os.path.join('..', all_text_file)
self.voc, self.emb = read_word_embeds(emb_file)
_temp = np.zeros((1,self.emb.shape[1]),dtype=self.emb.dtype)
# Add two more embeddings at the front and tail of
# word embedding for padding and UNK respectively.
self.emb = np.concatenate((_temp, self.emb, _temp.copy()))
self.dicts = {self.voc[i]:i+1 for i in range(len(self.voc))}
self.text_data = []
self.label_data = []
self.num_class = 1
# Switch between train dataset and test dataset
text_file = test_text_file if test else train_text_file
label_file = test_label_file if test else train_label_file
with open(text_file,'r',encoding='utf-8') as reader1, open(label_file) as reader2:
for line1, line2 in zip(reader1, reader2):
words = line1.strip().split()
_data = [self.dicts.get(word) for word in words]
line_data = [self.emb.shape[0]-1 if v is None else v for v in _data]
self.text_data.append(np.array(line_data,dtype=np.int64))
self.label_data.append(int(line2.strip()))
self.label_data = np.array(self.label_data, dtype=np.int64)
# Make labels start from 0
if np.min(self.label_data) != 0:
self.label_data -= np.min(self.label_data)
self.num_class = np.max(self.label_data)+1
text_len = map(lambda x:len(x), self.text_data)
sent_len = min(max(text_len), 300)
for v in self.text_data:
v.resize(sent_len, refcheck=False)
self.text_data = np.array(self.text_data)
def __len__(self):
return len(self.text_data)
def __getitem__(self, idx):
if torch.is_tensor(idx):
idx = idx.tolist()
return self.text_data[idx], self.label_data[idx]
def get_dict(self):
return self.dicts
def get_emb(self):
return self.emb
|
[
"zoxtang@gmail.com"
] |
zoxtang@gmail.com
|
78c07603a7231513247c90a35a64d892b27da22e
|
6bb47d64abcc131781b702495e690efeba59b988
|
/Hello/home/urls.py
|
882036078de5dcb609bffa8dc8fbd5b55e0902ee
|
[] |
no_license
|
jewells07/Django-Startup
|
acd349cef056569f815317f92ffcbd06ed807991
|
8cb2de607e0a19e70181689ebcec7fa72eb44396
|
refs/heads/master
| 2022-06-20T12:05:36.388950
| 2020-05-08T14:02:02
| 2020-05-08T14:02:02
| 262,338,233
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 355
|
py
|
from django.contrib import admin
from django.urls import path
from home import views
urlpatterns = [
path("",views.index, name = 'home'),
path("about",views.about, name = 'about'),
path("services",views.services, name = 'services'),
path("contact",views.contact, name = 'contact'),
path("contact",views.contact, name = 'contact'),
]
|
[
"jewellsjoshi437@gmail.com"
] |
jewellsjoshi437@gmail.com
|
673ab9861bcae85a1a55c3ed742550710ec90195
|
99d7a6448a15e7770e3b6f3859da043300097136
|
/src/hardware/core/i_core_device.py
|
653c0e71ab0666d2da9b754da7fe944a400daac1
|
[] |
no_license
|
softtrainee/arlab
|
125c5943f83b37bc7431ae985ac7b936e08a8fe4
|
b691b6be8214dcb56921c55daed4d009b0b62027
|
refs/heads/master
| 2020-12-31T07:54:48.447800
| 2013-05-06T02:49:12
| 2013-05-06T02:49:12
| 53,566,313
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,211
|
py
|
#===============================================================================
# Copyright 2011 Jake Ross
#
# 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.
#===============================================================================
#============= enthought library imports =======================
from traits.api import Interface
#============= standard library imports ========================
#============= local library imports ==========================
class ICoreDevice(Interface):
def get(self):
'''
'''
def set(self, *args, **kw):
'''
'''
#============= views ===================================
#============= EOF ====================================
|
[
"jirhiker@localhost"
] |
jirhiker@localhost
|
ba92d4f9f437fcf74daf2e0b5f28089408f310c4
|
aaa06c63f0fba6c5aad5121d83715d0be828ce4e
|
/OpenStreetMap/models.py
|
6746038957e195d82202ad40ba008a0f5667564b
|
[] |
no_license
|
scotm/Comrade
|
b023b338f0daf5d083ae37e2e3a73d3d424f8a7c
|
c7186f00cd20916a78cc2282ea201f440102ebb7
|
refs/heads/master
| 2020-05-18T06:49:01.411310
| 2014-07-25T08:13:10
| 2014-07-25T08:13:10
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,658
|
py
|
from django.contrib.gis.db import models
class BaseOsmModel(models.Model):
access = models.TextField(blank=True)
addr_housename = models.TextField(db_column='addr:housename', blank=True)
addr_housenumber = models.TextField(db_column='addr:housenumber', blank=True)
addr_interpolation = models.TextField(db_column='addr:interpolation', blank=True)
admin_level = models.TextField(blank=True)
aerialway = models.TextField(blank=True)
aeroway = models.TextField(blank=True)
amenity = models.TextField(blank=True)
area = models.TextField(blank=True)
barrier = models.TextField(blank=True)
bicycle = models.TextField(blank=True)
boundary = models.TextField(blank=True)
brand = models.TextField(blank=True)
bridge = models.TextField(blank=True)
building = models.TextField(blank=True)
construction = models.TextField(blank=True)
covered = models.TextField(blank=True)
culvert = models.TextField(blank=True)
cutting = models.TextField(blank=True)
denomination = models.TextField(blank=True)
disused = models.TextField(blank=True)
embankment = models.TextField(blank=True)
foot = models.TextField(blank=True)
generator_source = models.TextField(db_column='generator:source', blank=True)
harbour = models.TextField(blank=True)
highway = models.TextField(blank=True)
historic = models.TextField(blank=True)
horse = models.TextField(blank=True)
intermittent = models.TextField(blank=True)
junction = models.TextField(blank=True)
landuse = models.TextField(blank=True)
layer = models.TextField(blank=True)
leisure = models.TextField(blank=True)
lock = models.TextField(blank=True)
man_made = models.TextField(blank=True)
military = models.TextField(blank=True)
motorcar = models.TextField(blank=True)
name = models.TextField(blank=True)
natural = models.TextField(blank=True)
office = models.TextField(blank=True)
oneway = models.TextField(blank=True)
operator = models.TextField(blank=True)
place = models.TextField(blank=True)
population = models.TextField(blank=True)
power = models.TextField(blank=True)
power_source = models.TextField(blank=True)
public_transport = models.TextField(blank=True)
railway = models.TextField(blank=True)
ref = models.TextField(blank=True)
religion = models.TextField(blank=True)
route = models.TextField(blank=True)
service = models.TextField(blank=True)
shop = models.TextField(blank=True)
sport = models.TextField(blank=True)
surface = models.TextField(blank=True)
toll = models.TextField(blank=True)
tourism = models.TextField(blank=True)
tower_type = models.TextField(db_column='tower:type', blank=True)
tunnel = models.TextField(blank=True)
water = models.TextField(blank=True)
waterway = models.TextField(blank=True)
wetland = models.TextField(blank=True)
width = models.TextField(blank=True)
wood = models.TextField(blank=True)
z_order = models.IntegerField(blank=True, null=True)
class Meta:
abstract = True
# Create your models here.
class PlanetOsmLine(BaseOsmModel):
osm_id = models.BigIntegerField(blank=True, primary_key=True)
way_area = models.FloatField(blank=True, null=True)
way = models.LineStringField(srid=900913, blank=True, null=True)
objects = models.GeoManager()
class Meta:
managed = False
db_table = 'planet_osm_line'
class PlanetOsmPoint(BaseOsmModel):
osm_id = models.BigIntegerField(blank=True, primary_key=True)
capital = models.TextField(blank=True)
ele = models.TextField(blank=True)
poi = models.TextField(blank=True)
way = models.PointField(srid=900913, blank=True, null=True)
objects = models.GeoManager()
class Meta:
managed = False
db_table = 'planet_osm_point'
class PlanetOsmPolygon(BaseOsmModel):
osm_id = models.BigIntegerField(blank=True, primary_key=True)
tracktype = models.TextField(blank=True)
way_area = models.FloatField(blank=True, null=True)
way = models.GeometryField(srid=900913, blank=True, null=True)
objects = models.GeoManager()
class Meta:
managed = False
db_table = 'planet_osm_polygon'
class PlanetOsmRoads(BaseOsmModel):
osm_id = models.BigIntegerField(blank=True, primary_key=True)
tracktype = models.TextField(blank=True)
way_area = models.FloatField(blank=True, null=True)
way = models.LineStringField(srid=900913, blank=True, null=True)
objects = models.GeoManager()
class Meta:
managed = False
db_table = 'planet_osm_roads'
|
[
"scott.scotm@gmail.com"
] |
scott.scotm@gmail.com
|
b086729dbab27bed113d6c9a6300cbe79200e959
|
481e3dd1953ab4444e37cee8892f6b8dfb567a98
|
/app/models/example_todo.py
|
40cedf6926ec8ab3de0eb9998a69c92915793f28
|
[] |
no_license
|
JeongHoJeong/react-flask-boilerplate
|
b34262fa895ee28c2366dbd50183024eeadec2dc
|
bd36ddc41cbcbbb5ae3101ba7d1947584e66b06a
|
refs/heads/master
| 2020-03-30T01:33:25.677581
| 2018-11-08T08:02:27
| 2018-11-08T08:02:27
| 150,581,781
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 227
|
py
|
from sqlalchemy import Column, BigInteger, String
from app.models import OrmBase
class ExampleTodo(OrmBase):
__tablename__ = 'example_todo'
id = Column(BigInteger, primary_key=True)
description = Column(String)
|
[
"fiil12@hotmail.com"
] |
fiil12@hotmail.com
|
362cdc331020a5268fd371e1eac03259c7a14bba
|
f3d01659c2a4465cdf7a5903d18058da008f1aac
|
/src/sentry/models/groupbookmark.py
|
f6cee4369c180e59d520ca7fe8093daee2869739
|
[
"BSD-2-Clause"
] |
permissive
|
Mattlk13/sentry-1
|
f81a1e5dc5d02a07e5c6bbcdb5e1ce53f24f53c1
|
19b0870916b80250f3cb69277641bfdd03320415
|
refs/heads/master
| 2023-08-30T21:49:49.319791
| 2019-07-30T19:23:07
| 2019-07-30T19:23:07
| 81,418,058
| 0
| 1
|
BSD-3-Clause
| 2023-04-04T00:22:49
| 2017-02-09T06:36:41
|
Python
|
UTF-8
|
Python
| false
| false
| 1,064
|
py
|
from __future__ import absolute_import
from django.conf import settings
from django.db import models
from django.utils import timezone
from sentry.db.models import FlexibleForeignKey, Model, BaseManager, sane_repr
class GroupBookmark(Model):
"""
Identifies a bookmark relationship between a user and an
aggregated event (Group).
"""
__core__ = False
project = FlexibleForeignKey('sentry.Project', related_name="bookmark_set")
group = FlexibleForeignKey('sentry.Group', related_name="bookmark_set")
# namespace related_name on User since we don't own the model
user = FlexibleForeignKey(settings.AUTH_USER_MODEL, related_name="sentry_bookmark_set")
date_added = models.DateTimeField(default=timezone.now, null=True)
objects = BaseManager()
class Meta:
app_label = 'sentry'
db_table = 'sentry_groupbookmark'
# composite index includes project for efficient queries
unique_together = (('project', 'user', 'group'), )
__repr__ = sane_repr('project_id', 'group_id', 'user_id')
|
[
"dcramer@gmail.com"
] |
dcramer@gmail.com
|
b55fd799bada92e8f1cd6d17a26da62618bdf02a
|
f6a8d93c0b764f84b9e90eaf4415ab09d8060ec8
|
/Lists Advanced/the_office.py
|
de39a3b8b66d23417344eae1ded709f3c883b3b7
|
[] |
no_license
|
DimoDimchev/SoftUni-Python-Fundamentals
|
90c92f6e8128b62954c4f9c32b01ff4fbb405a02
|
970360dd6ffd54b852946a37d81b5b16248871ec
|
refs/heads/main
| 2023-03-18T17:44:11.856197
| 2021-03-06T12:00:32
| 2021-03-06T12:00:32
| 329,729,960
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 656
|
py
|
employees_list = [int(x) for x in (input().split(" "))]
HIF = int(input()) # happiness improvement factor
happy_count = 0
increased_happiness_list = list(map(lambda employee: employee * HIF, employees_list))
average_happiness = sum(increased_happiness_list) / len(increased_happiness_list)
happy_list = list(filter(lambda employee: employee >= average_happiness, increased_happiness_list))
for i in range(len(happy_list)):
happy_count += 1
if happy_count >= len(employees_list)/2:
print(f"Score: {happy_count}/{len(employees_list)}. Employees are happy!")
else:
print(f"Score: {happy_count}/{len(employees_list)}. Employees are not happy!")
|
[
"noreply@github.com"
] |
DimoDimchev.noreply@github.com
|
3cb225f72576655ceb256774a37ab22d8364393f
|
6a25171b9f0a6b47f844aa6f22538917c25c2a45
|
/REST API - Tensorflow/server.py
|
c63739a4aeb3685b5a5fdd163b769146a99b8be0
|
[
"MIT"
] |
permissive
|
mauryas/DataScienceTasks
|
c37d52f88a03d7c15d7cbc7dff33084b24098138
|
78cd4c47067101128de668a641b999d6fb406ab8
|
refs/heads/master
| 2020-04-01T13:59:02.947765
| 2018-10-16T13:39:58
| 2018-10-16T13:39:58
| 153,275,401
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,715
|
py
|
#%% Import Libraries
import flask
from model.model import ImageClassifier
import io
import numpy as np
import os
from sklearn.preprocessing import OneHotEncoder
import zipfile
from PIL import Image
import psutil
import logging
from config.config import IMG_COLS, IMG_ROWS, TO_TRAIN
# Setting logging file path
try:
log_path = os.stat(os.path.join(os.getcwd(), 'log'))
except:
log_path = os.mkdir(os.path.join(os.getcwd(), 'log'))
# Logging object configrations
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)s %(message)s',
filename='server.log',
filemode='w')
#%% Initializa the application and model
app = flask.Flask(__name__)
cls = None
#%% Methods
def init_model():
'''
Initialize the model and train it for
'''
global cls
cls = ImageClassifier()
if TO_TRAIN:
cls.train()
logging.info("Train Variable Value: {}". format(TO_TRAIN))
logging.info("Straining to train model")
else:
cls.load_model()
logging.info("Train Variable Value: {}". format(TO_TRAIN))
logging.info("Loaded Trained Model")
#%% Post Methods
@app.route("/predict", methods=["POST"])
def predict():
'''
Read the input images from input and return the predicted class.
'''
result = {'success':False}
#Fetch the file
# ensure an image was properly uploaded to our endpoint
if flask.request.method == "POST":
if flask.request.files.get("image"):
# read the image in PIL format
image = flask.request.files["image"].read()
image = Image.open(io.BytesIO(image))
image = np.reshape(image,(1,IMG_ROWS,IMG_COLS,1))
y_pred = cls.predict(image)
result['success'] = True
result['prediction'] = (np.argmax(y_pred[0])).tolist()
return flask.jsonify(result)
@app.route("/batch_train", methods=["POST"])
def batch_train():
'''
Take an input batch of images and train the classifier
'''
result = {'success':False}
#Fetch the file
if flask.request.method == "POST":
"""
Validate the zip file which we will receive. If the available memory is
more than request file size + DNN model, then train the model.
"""
avl_mem = (psutil.virtual_memory().free)*1024
cls_mem = cls.get_model_memory_usage()
content_length = flask.request.content_length
logging.info('Mem: {}'.format(avl_mem - cls_mem -content_length))
if (avl_mem - cls_mem -content_length) < 0.05*(avl_mem):
result = {'success':False, 'Error': 'large file'}
return flask.jsonify(result)
if flask.request.files.get("zip"):
zip_read = flask.request.files["zip"]
logging.info('Zip read Sucess')
# if the file uploaded is a zip, open the file and save create a numpy array
zip_ref = zipfile.ZipFile(zip_read, 'r')
# before extracting create a temp dir where we will save those files
try:
os.stat('tmp')
except:
os.mkdir('tmp')
zip_ref.extractall(os.path.join(os.getcwd(), 'tmp'))
zip_ref.close()
new_train = []
new_label = []
# Now open the tmp dir and one by one extract the images
for root, dirs, files in os.walk(os.path.join(os.getcwd(), 'tmp')):
# we will get the labels from the file name
for file in files:
file_name = os.path.splitext(file)[0]
_label = file_name.split('_')[1]
# read the image and convert it into numpy array
image = Image.open(os.path.join(root,file))
image = np.reshape(image,(IMG_ROWS,IMG_COLS,1))
# append the labels and image array to the list
new_train.append(image)
new_label.append(int(_label))
# One hot encoding
enc = OneHotEncoder()
new_labels = enc.fit_transform(np.reshape(new_label, (-1, 1))).toarray()
# Now send this to the training
logging.info(np.shape(new_train))
cls.batch_train_online(np.array(new_train), new_labels)
logging.info('Batch Training is done.')
result = {'success':True}
return flask.jsonify(result)
if __name__ == "__main__":
init_model()
print('Model Loaded')
app.run()
|
[
"shivammaurya@outlook.com"
] |
shivammaurya@outlook.com
|
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