blob_id stringlengths 40 40 | directory_id stringlengths 40 40 | path stringlengths 3 281 | content_id stringlengths 40 40 | detected_licenses listlengths 0 57 | license_type stringclasses 2 values | repo_name stringlengths 6 116 | snapshot_id stringlengths 40 40 | revision_id stringlengths 40 40 | branch_name stringclasses 313 values | visit_date timestamp[us] | revision_date timestamp[us] | committer_date timestamp[us] | github_id int64 18.2k 668M ⌀ | star_events_count int64 0 102k | fork_events_count int64 0 38.2k | gha_license_id stringclasses 17 values | gha_event_created_at timestamp[us] | gha_created_at timestamp[us] | gha_language stringclasses 107 values | src_encoding stringclasses 20 values | language stringclasses 1 value | is_vendor bool 2 classes | is_generated bool 2 classes | length_bytes int64 4 6.02M | extension stringclasses 78 values | content stringlengths 2 6.02M | authors listlengths 1 1 | author stringlengths 0 175 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b588f2c1ecc3daa6991eab8af144bceb73afd1cb | 7d75f44a9486b6e2bb0e58c72d22be436cc308af | /EventSelector/scripts/wq2-ls | 4d93419f50c4dcd2e7f4cd550c4c53f5c8220804 | [] | no_license | zinon/RawData | f95dbef4c12eb9db73adbae8e94c031781bc3bef | 38743ed4d52f532a03e53dfee774abfa49e82988 | refs/heads/master | 2021-01-19T20:18:15.971916 | 2015-02-25T11:30:18 | 2015-02-25T11:30:18 | 31,310,618 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,520 | #! /usr/bin/env python
"""
Module createContainer
improved dq2-ls splits up unique and duplicated datasets
"""
import optparse
import subprocess
import os
import re
from DQ2Tool import DQ2Tool
## Configuration
############################################################
def main():
# Load Parser
usage = "usage: %prog [options] SEARCH_STRING"
parser = optparse.OptionParser(usage=usage)
# Set Options
parser.add_option("-c", "--contents", dest="contents", action="store_true", default=False,
help="display the contents of any container" )
# Set Defaults
#parser.set_defaults( checking = False )
# Parse Args
(options,args) = parser.parse_args()
# Check for search string
if len(args) < 1 :
print "ERROR - Must provide search string"
parser.print_help()
exit(1)
## Load dq2 tool
dq2 = DQ2Tool()
## Run
########################################################
input_containers = dq2.lsArray( args )
overlap, unique, junk = dq2.getOverlappingDatasets( input_containers )
if options.contents: unique = dq2.getContainerArrayContents(unique)
# Summaries datasets
print
print '# Unique datasets:'
for dataset_name in unique:
print dataset_name
print
print '# Overlapping datasets:'
for entry in overlap:
print '#%s:'%entry
for dataset_name in overlap[entry]:
print ' ',dataset_name
print
print '# Junk datasets:'
for dataset_name in junk:
print dataset_name
if __name__ == '__main__': main()
| [
"zinon123@gmail.com"
] | zinon123@gmail.com | |
d1456bb6326f302fbb94ad3ef15d4303f90f97cc | 9f6691c51f5ee58d19caa5c9e4cb82ddbd917ec0 | /V2RaycSpider1225/src/BusinessLogicLayer/utils/staff_mining/support/staff_collector.py | 51704a1ff91c67c352648a349fe62e6638fb4d65 | [
"MIT"
] | permissive | TOBICHI-Origami/V2RSS | 2bef6e1e48942cf21023a3c91eefeecb42ddfe3e | a5dc1478b0229d87881c53095366f692ddeac04a | refs/heads/master | 2023-09-05T07:55:45.082232 | 2021-10-19T15:35:25 | 2021-10-19T15:35:25 | 420,401,126 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 8,741 | py | __all__ = ["StaffCollector"]
import random
import sys
import time
from selenium.common.exceptions import NoSuchElementException, WebDriverException
from selenium.webdriver import Chrome, ChromeOptions
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.common.keys import Keys
from tqdm import tqdm
from ..common.exceptions import CollectorSwitchError
class StaffCollector:
def __init__(
self,
cache_path: str,
chromedriver_path: str,
silence: bool = True,
debug: bool = False,
):
"""
:param cache_path:
:param silence:
:param debug:
:param chromedriver_path:
"""
self.GOOGLE_SEARCH_API = "https://www.google.com.hk"
# self.SEARCH_QUERY = '"特此免费授予任何获得副本的人这个软件和相关的文档文件"'
self.SEARCH_QUERY = '"由 @editXY 修改适配。"'
self.CHROMEDRIVER_PATH = chromedriver_path
self.cache_path = cache_path
self.debug = debug
self.silence = silence
@staticmethod
def _down_to_api(api: Chrome, search_query: str):
"""键入并跳转至相关页面"""
while True:
try:
input_tag = api.find_element_by_xpath("//input[@name='q']")
input_tag.click()
input_tag.clear()
input_tag.send_keys(search_query)
input_tag.send_keys(Keys.ENTER)
break
except NoSuchElementException:
time.sleep(0.5)
continue
@staticmethod
def _page_switcher(api: Chrome, is_home_page: bool = False):
start_time = time.time()
# 首页 -> 第二页
if is_home_page:
while True:
try:
ActionChains(api).send_keys(Keys.END).perform()
time.sleep(0.5)
api.find_element_by_xpath("//a[@id='pnnext']").click()
break
except NoSuchElementException:
# 检测到到流量拦截 主动抛出异常并采取备用方案
if "sorry" in api.current_url:
raise CollectorSwitchError
time.sleep(0.5)
api.refresh()
continue
# 第二页 -> 第N页
else:
while True:
try:
ActionChains(api).send_keys(Keys.END).perform()
time.sleep(0.5)
page_switchers = api.find_elements_by_xpath("//a[@id='pnnext']")
next_page_bottom = page_switchers[-1]
next_page_bottom.click()
break
except (NoSuchElementException, IndexError):
time.sleep(0.5)
# 检测到到流量拦截 主动抛出异常并采取备用方案
if "sorry" in api.current_url:
raise CollectorSwitchError
# 最后一页
if time.time() - start_time > 5:
break
continue
def _capture_host(self, api: Chrome):
time.sleep(1)
# hosts = api.find_elements_by_xpath("//span[@class='qXLe6d dXDvrc']//span[@class='fYyStc']")
hosts = api.find_elements_by_xpath(
"//div[contains(@class,'NJjxre')]//cite[@class='iUh30 Zu0yb qLRx3b tjvcx']"
)
with open(self.cache_path, "a", encoding="utf8") as f:
for host in hosts:
f.write(f"{host.text.split(' ')[0].strip()}/auth/register\n")
def set_spider_options(self) -> Chrome:
# 实例化Chrome可选参数
options = ChromeOptions()
# 最高权限运行
options.add_argument("--no-sandbox")
# 隐身模式
options.add_argument("-incognito")
# 无缓存加载
options.add_argument("--disk-cache-")
# 设置中文
options.add_argument("lang=zh_CN.UTF-8")
# 禁用 DevTools listening
options.add_experimental_option("excludeSwitches", ["enable-logging"])
options.add_argument("--log-level=3")
# 更换头部
options.add_argument(
"user-agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/92.0.4515.159 Safari/537.36 Edg/92.0.902.78'"
)
# 静默启动
if self.silence is True:
options.add_argument("--headless")
options.add_argument("--disable-gpu")
options.add_argument("--disable-software-rasterizer")
# 抑制自动化控制特征
options.add_argument("--disable-blink-features=AutomationControlled")
options.add_experimental_option("useAutomationExtension", False)
options.add_experimental_option("excludeSwitches", ["enable-automation"])
try:
_api = Chrome(options=options, executable_path=self.CHROMEDRIVER_PATH)
_api.execute_cdp_cmd(
"Page.addScriptToEvaluateOnNewDocument",
{
"source": """
Object.defineProperty(navigator, 'webdriver', {
get: () => undefined
})
"""
},
)
return _api
except WebDriverException as e:
if "chromedriver" in str(e):
print(f">>> 指定目录下缺少chromedriver {self.CHROMEDRIVER_PATH}")
sys.exit()
@staticmethod
def get_page_num(api: Chrome):
try:
result = api.find_element_by_xpath("//div[@id='result-stats']")
tag_num = result.text.strip().split(" ")[1]
print(tag_num)
except NoSuchElementException:
return None
def run(self, page_num: int = 26, sleep_node: int = 5):
# API 实例化
api = self.set_spider_options()
# 进度条 初始化
loop_progress = tqdm(
total=page_num,
desc="STAFF COLLECTOR",
ncols=150,
unit="piece",
dynamic_ncols=False,
leave=True,
)
loop_progress.set_postfix({"status": "__initialize__"})
try:
# 根据关键词 去首页
api.get(self.GOOGLE_SEARCH_API)
self._down_to_api(api=api, search_query=self.SEARCH_QUERY)
self.get_page_num(api)
# 获取page_num页的注册链接
# 正常情况一页10个链接 既共获取page_num * 10个链接
for x in range(page_num):
# ==============================================================
# 采集器
# ==============================================================
# 萃取注册链接并保存
self._capture_host(api=api)
loop_progress.set_postfix({"status": "__collect__"})
loop_progress.update(1)
# self._debugger(message=f"Successfully collected the staff-hosts from page {x + 1}", level="info")
# print(f"<StaffCollector> Successfully collected the staff-hosts [{x + 1}/{page_num}]")
# ==============================================================
# 翻页控制器
# ==============================================================
# 第1页 -> 第2页
if x == 0:
self._page_switcher(api=api, is_home_page=True)
# 第2页-> 第N页
self._page_switcher(api=api, is_home_page=False)
# ==============================================================
# 休眠控制器
# ==============================================================
# 每sleep_node页进行一次随机时长的休眠
if x % sleep_node == 0:
tax_ = random.uniform(3, 5)
# self._debugger(message=f"Tactical sleep! The mission will continue in {round(tax_, 3)} seconds",
# level="debug")
# print(f"<StaffCollector> Tactical sleep! The mission will continue in {round(tax_, 3)} seconds")
loop_progress.set_postfix({"status": "__sleep__"})
time.sleep(tax_)
finally:
api.quit()
# self._debugger(message="Mission completed", level="info")
# self._debugger(message=f"the cache file address is {self.cache_path}", level="info")
| [
"62018067+QIN2DIM@users.noreply.github.com"
] | 62018067+QIN2DIM@users.noreply.github.com |
dc27dc63f6a3b9d4bd00afcbc7b4639d4e1533d0 | 993f7b85a9c4d69d91c100b22aba2f14b638fc81 | /swea-5656.py | b3c3a1d27380c90f74ffdb1dc8c05350b1e22d44 | [] | no_license | bearics/coding-test | 2a5eca9d12eb6051e5fd14646fee719ba328f962 | ffe7a602e088245cd931f0d078dbd2e8dad83254 | refs/heads/master | 2020-07-20T18:33:23.187916 | 2019-09-06T02:24:35 | 2019-09-06T02:24:35 | 206,692,398 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,533 | py | dirs = [[1, 0], [0, -1], [-1, 0], [0, 1]] # R D L U, [X, Y]
def sol(n):
# global debugggg
# debugggg += 1
# print(debugggg)
global base_map
# if debugggg == 28:
# print("stop")
if len(n) >= N:
count = 0
global min_count
for rr in range(H):
for cc in range(W):
if base_map[rr][cc] != 0:
count += 1
min_count = min(min_count, count)
# if n[0] == 2 and n[1] ==2 and n[2] == 6:
# print("here!!")
# print(n)
# for _r in base_map:
# print(*_r)
return
# print(n, end=" ")
for c in range(W):
# 부술 벽돌이 있는지 확인
have_brick = False
broken_bricks = []
for r in range(H):
if base_map[r][c] != 0:
broken_bricks.append([r, c])
break
prev_map = [row[:] for row in base_map]
# c열에는 벽돌이 없어서 끝
if len(broken_bricks) == 0:
continue
# c열에 깰 벽돌이 있음
broken_map = [[0] * W for _ in range(H)]
while broken_bricks:
br, bc = broken_bricks.pop(0)
count = base_map[br][bc]
for dx, dy in dirs:
broken_map[br][bc] = 1
base_map[br][bc] = -1
if count == 1:
break
for idx in range(1, count):
if ((br + (idx * dy)) < 0 or (br + (idx * dy)) >= H) or ((bc + (idx * dx)) < 0 or (bc + (idx * dx)) >= W):
continue
else:
if base_map[br + (idx * dy)][bc + (idx * dx)] > 0 and broken_map[br + (idx * dy)][bc + (idx * dx)] == 0:
broken_bricks.append([br + (idx * dy), bc + (idx * dx)])
broken_map[br + (idx * dy)][bc + (idx * dx)] = 1
# 벽돌 제거
for rr in range(H):
for cc in range(W):
if broken_map[rr][cc] == 1:
base_map[rr][cc] = 0
# 벽돌 정리
for cc in range(W):
temp = []
for rr in range(H):
if base_map[rr][cc] != 0:
temp.append(base_map[rr][cc])
base_map[rr][cc] = 0
for r_idx in range(len(temp)):
base_map[H - r_idx - 1][cc] = temp[len(temp) - r_idx - 1]
# print("n:{} c:{}".format(n, c), end=' ')
n.append(c)
sol(n)
n.pop()
base_map = [_[:] for _ in prev_map]
T = int(input())
for case_idx in range(T):
N, W, H = map(int, input().split())
# print(N, W, H)
base_map = []
for row in range(H):
base_map.append(list(map(int, input().split())))
min_count = 999999
debugggg = 0
sol([])
if min_count is 999999:
min_count = 0
print("#{} {}".format(case_idx + 1, min_count))
| [
"bearics@gmail.com"
] | bearics@gmail.com |
39a6558bfc2c2ddd777939bce2b4f90f80b198ee | 8901d53969eb840338fb3b66895d199e4c82aad7 | /vantage_media_player/bin/django-admin | 66b2baa559b0508aad95a980ef2638ff3144b892 | [] | no_license | SaundersB/web-media-player | 26438614685ba6d065d5d64c61468862cf4535cd | 3b3690a6860a4d815542f0fdfa524b3ba0222fcc | refs/heads/master | 2021-05-31T22:27:28.969328 | 2016-07-19T20:29:27 | 2016-07-19T20:29:27 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 317 | #!/home/brandons/src/Web_Media_Player/vantage_media_player/bin/python
# -*- coding: utf-8 -*-
import re
import sys
from django.core.management import execute_from_command_line
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
sys.exit(execute_from_command_line())
| [
"speakeasys@gmail.com"
] | speakeasys@gmail.com | |
7b1d8bb258a7103c7da00088999d4559fef09750 | ec8d24cab32a821338055654e51589307d363d86 | /linked/linked/pipelines.py | f065f97abef8391e9b5328856dadafb106afd6e1 | [] | no_license | caiprozect/crawl | ce64c765469baf64e09dae4229d9387512302a45 | 43b75aca258830c44628e3efc33aabce9d4957e7 | refs/heads/master | 2021-01-24T09:45:33.061037 | 2016-10-05T12:00:08 | 2016-10-05T12:00:08 | 69,521,875 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 286 | py | # -*- coding: utf-8 -*-
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html
class LinkedPipeline(object):
def process_item(self, item, spider):
return item
| [
"caiprozect@gmail.com"
] | caiprozect@gmail.com |
e6963b1f1c20af3ad100d73cbd2a60ebafed797b | afe177633a6af170d6a2f56660aafb7cef388daa | /sprites/ground.py | 87e71d59839583697b126e1acb0ab513302bd842 | [
"MIT"
] | permissive | sdcpku/FlappyBirdAI | 5f25c61bcbf7c6b68c82be653946b24dfda0b42d | 945f42a6a5f83facf69f314f40af9612638467e9 | refs/heads/master | 2021-01-12T14:19:42.875747 | 2014-06-20T06:02:42 | 2014-06-20T06:02:42 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 860 | py | import cocos
import cocos.euclid
import cocos.collision_model
import setting
class Ground(cocos.sprite.Sprite):
def __init__(self, y):
super(Ground, self).__init__(image="resources/ground.png")
position = (setting.GAME_WIDTH - self.width / 2, y)
self.position = position
self.cshape = cocos.collision_model.AARectShape(cocos.euclid.Vector2(*position),
self.width / 2, self.height / 2)
ground_action = cocos.actions.Repeat(
cocos.actions.MoveTo((setting.GAME_WIDTH / 2, y),
duration=(self.width - setting.GAME_WIDTH) / 2.0 / setting.SPEED)
+
cocos.actions.Place((setting.GAME_WIDTH - self.width / 2, y))
)
self.do(ground_action)
def update_cshape(self):
pass
| [
"xianyubo@qq.com"
] | xianyubo@qq.com |
aca671cbd29112f2e6668647ab92fe0be17afbb2 | 60c6f68000fe9440948f91b493d15e96c2159373 | /python/index-gsoc-searcher-data.py | 21b0674d84288efb1850321cec4495f20140c197 | [] | no_license | dbpedia-spotlight/gsoc-searcher | a0a288686089c0bb89c05d4d5b55a7f16925b25c | a75c4c3177e30273995e38c9a924ae835e2247ad | HEAD | 2016-09-01T23:08:53.629598 | 2013-06-11T10:08:44 | 2013-06-11T10:08:44 | 9,697,566 | 3 | 1 | null | null | null | null | UTF-8 | Python | false | false | 3,490 | py | """
Requires an ElasticSearch server to be running.
python index-gsoc-search-data.py <dataDir> <elasticSearchUrl>
"""
import sys
import os
import urllib2
import re
INDEX_ID = "gsoc2013"
TYPE_ID = "d"
MAPPING = """{
"d" : {
"properties" : {
"ideas" : {
"type" : "string",
"store" : "yes"
},
"linkId" : {
"type" : "string",
"store" : "yes"
},
"name" : {
"type" : "string",
"store" : "yes"
},
"tagged" : {
"type" : "string",
"store" : "yes"
},
"taggedString" : {
"type" : "string",
"store" : "yes"
},
"textTagged" : {
"type" : "string",
"store" : "yes"
}
}
}
}"""
class RequestWithMethod(urllib2.Request):
"""Hack for forcing the method in a request - allows PUT and DELETE
Ack: Eric S. Raymond
http://benjamin.smedbergs.us/blog/2008-10-21/putting-and-deleteing-in-python-urllib2/#comment-430392
"""
def __init__(self, method, *args, **kwargs):
# This assignment works directly in older Python versions
self._method = method
urllib2.Request.__init__(self, *args, **kwargs)
def get_method(self):
# This method works in newer Pythons (2.6.5, possibly earlier).
if self._method:
return self._method
elif self.has_data():
return 'POST'
else:
return 'GET'
def analyzeKey(k):
return k.replace("/", "_")
def iterOrgData(dataDir):
d = {} # group org data
for fileName in [fn for fn in os.listdir(dataDir) if not fn.endswith(".text")]:
fullPath = os.path.join(dataDir, fileName)
with open(fullPath) as f:
for line in f:
key, prop, val = line.strip().split("\t")
d.setdefault(key, []).append((prop, val))
for k, vals in d.iteritems():
yield k, vals
def wipeIndex(elasticSearchUrl):
print "Wiping index %s" % elasticSearchUrl
url = "%s/%s" % (elasticSearchUrl, INDEX_ID)
try:
print urllib2.urlopen(RequestWithMethod('DELETE', url)).read()
except urllib2.HTTPError, err:
if err.code != 404:
raise # none existed
urllib2.urlopen(RequestWithMethod('PUT', url)).read()
def setMapping(elasticSearchUrl):
url = "%s/%s/%s/_mapping" % (elasticSearchUrl, INDEX_ID, TYPE_ID)
print urllib2.urlopen(RequestWithMethod('PUT', url, data=MAPPING)).read()
def indexOrgData(elasticSearchUrl, orgData):
key, vals = orgData
print "Indexing in %s: %s" % (elasticSearchUrl, key)
url = "%s/%s/%s/%s" % (elasticSearchUrl, INDEX_ID, TYPE_ID, analyzeKey(key))
data = '{' + ",".join(['"%s":"%s"' % (prop, val) for prop, val in vals]) + '}'
answerJson = urllib2.urlopen(RequestWithMethod('PUT', url, data=data)).read()
if not '"ok":true' in answerJson:
print url, data
print orgData, "failed indexation"
sys.exit(1)
def flushIndex(elasticSearchUrl):
url = "%s/_flush" % (elasticSearchUrl)
print urllib2.urlopen(RequestWithMethod('POST', url)).read()
if __name__ == "__main__":
dataDir = sys.argv[1]
elasticSearchUrl = "http://localhost:9200"
if len(sys.argv) == 3:
elasticSearchUrl = re.sub("/$", "", sys.argv[2])
wipeIndex(elasticSearchUrl)
setMapping(elasticSearchUrl)
for orgData in iterOrgData(dataDir):
indexOrgData(elasticSearchUrl, orgData)
flushIndex(elasticSearchUrl)
| [
"max.jakob@gmail.com"
] | max.jakob@gmail.com |
876a4e19c8e2c703b622a9bd2a112eb53263922f | cca746947ed7779c48dbca2bdd6398755445f801 | /chapter13/decorate_demo.py | 530e3e7f50f686fcd6730def079ee16e9c8d6ff5 | [] | no_license | TangBean/AdvancePython | 0081ce5afc434dd8ee10d3539df952d1845c8cff | 6b29c3c271104fdc947522f26c9884c011147c86 | refs/heads/master | 2020-05-19T21:10:37.330795 | 2019-05-13T15:19:21 | 2019-05-13T15:19:21 | 185,217,792 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 649 | py | def log(func):
def wrapper(*args, **kwargs):
print("call %s():" % func.__name__)
func(*args, **kwargs)
print("call finish")
return "returning"
return wrapper
# 在这里用 log 装饰 now 函数，相当于调用了 now = log(now)，也就是说，now 函数现在是 wrapper 函数
# 然后调用 now("hello") == wrapper("hello")
# 在 wrapper 中调用 func(*args, **kwargs) 相当于调用 now("hello") 本身，我们可以在这个函数调用前后加逻辑装饰它
@log
def now(msg):
print(msg)
res = now("hello")
print(res)
print(now) # <function log.<locals>.wrapper at 0x000001E5CAD73598>
| [
"984354469@qq.com"
] | 984354469@qq.com |
cc253dd395f7b5886f218c25e5d30b74c5670852 | 91afa6d9e893b6b6586226acaca684ab8bbfb5e9 | /plaining/migrations/0003_person_sexe.py | 9f72632904fd8a0ac8a753d9b054704119a77521 | [] | no_license | elmehdiLAM/frontend | 4a71604d9cb75511d98d17acebb44bcf9db8ad4c | e469cf7d01665065309d620bc55867949020d2ab | refs/heads/master | 2023-03-08T12:33:10.055991 | 2021-02-21T17:02:49 | 2021-02-21T17:02:49 | 340,951,522 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 446 | py | # Generated by Django 3.1.4 on 2021-01-02 22:32
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('plaining', '0002_auto_20210102_1516'),
]
operations = [
migrations.AddField(
model_name='person',
name='sexe',
field=models.CharField(choices=[('MAS', 'Masculin'), ('FEM', 'Feminin')], default='', max_length=10),
),
]
| [
"elmehdi.lamsyah@fsr.ac.ma"
] | elmehdi.lamsyah@fsr.ac.ma |
126797cd83a42c98ec04cdb75a1bd48f2f88afc4 | ea3063b9559046fdd53e9ceff8839adcb04671d5 | /nn/data/augmentation_preprocessing.py | 3a227a3c7e986d64a1a3eeccd882202b57fe6302 | [] | no_license | Juravlik/diploma_1 | a4f2631c588841139a13db917326f137e741ea08 | 07d95db3b0df529d3bce37de81b96aa75ad5a3e4 | refs/heads/main | 2023-05-04T07:08:23.746603 | 2021-05-27T01:40:25 | 2021-05-27T01:40:25 | 370,557,047 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,116 | py | import albumentations as A
import torch
import random
import numpy as np
import cv2
IMAGE_SIZE = 256
def lock_deterministic(seed=42):
np.random.seed(seed)
random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
torch.backends.cudnn.benchmark = False
torch.backends.cudnn.deterministic = True
def add_padding_to_square(x, **kwargs):
max_side = max(x.shape)
return A.PadIfNeeded(
min_height=max_side, min_width=max_side, always_apply=True, border_mode=cv2.BORDER_CONSTANT
)(image=x)['image']
def _get_validation_augmentation():
transforms = [
A.Lambda(image=add_padding_to_square, mask=add_padding_to_square, always_apply=True),
A.Resize(height=IMAGE_SIZE, width=IMAGE_SIZE, always_apply=True),
]
return A.Compose(transforms)
def _get_training_augmentation():
transforms = [
A.Blur(blur_limit=(3, 3), p=0.05),
A.Cutout(num_holes=6, max_h_size=12, max_w_size=12, fill_value=0, p=0.07),
A.OneOf(
[
A.ISONoise(color_shift=(0.05, 0.01), intensity=(0.1, 0.5), p=0.1),
A.IAAAdditiveGaussianNoise(p=0.1),
A.IAAPerspective(p=0.1),
], p=0.3
),
A.RandomBrightnessContrast(p=0.1),
A.RandomShadow(num_shadows_upper=3, p=0.05),
A.Flip(p=0.25),
A.ShiftScaleRotate(border_mode=cv2.BORDER_CONSTANT, p=0.2),
_get_validation_augmentation(),
]
return A.Compose(transforms)
def get_train_aug_preproc(preprocessing_fn):
return A.Compose([*_get_training_augmentation()] + [*_get_preprocessing(preprocessing_fn)])
def get_valid_aug_preproc(preprocessing_fn):
return A.Compose([*_get_validation_augmentation()] + [*_get_preprocessing(preprocessing_fn)])
def to_tensor(x, **kwargs):
return torch.from_numpy(x.transpose(2, 0, 1).astype('float32'))
def _get_preprocessing(preprocessing_fn):
_transform = [
A.Lambda(image=preprocessing_fn),
A.Lambda(image=to_tensor),
]
return A.Compose(_transform)
| [
"temelyanov@griddynamics.com"
] | temelyanov@griddynamics.com |
2a99b3bb613dba1885dc7a069898c4d69a501f7e | 833b43575815ce6c5fa8cbac2628cb774331eda7 | /chap20_p371_code3.py | dcda8aea075beb81ff7c9027d10c117c90dfe210 | [] | no_license | ai-times/infinitybook_python | d9529dfe7d486bf5c713d52b530915a23cbf1812 | 1c011c31994d07fe959bba9b519c4365f5f40e7f | refs/heads/main | 2023-03-01T12:18:20.695888 | 2021-02-14T04:22:40 | 2021-02-14T04:22:40 | 338,578,047 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 124 | py | from datetime import datetime
birth = datetime(2002, 6, 30, 10, 15, 3, 56765)
now = datetime.now( )
print( now - birth )
| [
"wskim092@gmail.com"
] | wskim092@gmail.com |
d2f174d698d8c02ec6ecce24ca62979fbca72999 | 0397efdc80bae46a9057b80d98f281dfad421abf | /monitorize/wsgi.py | 0bddf78b1d1db059f733bb50f77e5fc47114029b | [] | no_license | sungpia/Monitorize | 4751b608d4284cc148cc6b106ae31033b1117761 | b472a74c0145995f4bc51e2cc271ee86dd9ce9a9 | refs/heads/master | 2020-05-26T15:48:39.961287 | 2019-05-24T21:35:35 | 2019-05-24T21:35:35 | 188,293,260 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 397 | py | """
WSGI config for monitorize project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.10/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "monitorize.settings")
application = get_wsgi_application()
| [
"sungpia@me.com"
] | sungpia@me.com |
89e36ad6da49de830237eae3d65f2168dc4709bc | bd23d83683c9b6ef9e440b751b0b9f3a6daab126 | /src/djangodbu/sql.py | e545e4d65a26b9a77491e38dccee5f6168bad92b | [
"MIT"
] | permissive | mulderns/djangodbu | 08cf83a3edccc84bc9b9fd8517b876b4bb595fdc | 25c212986776a1bac63efed2040fd555f1d20f40 | refs/heads/master | 2023-03-11T20:38:39.870146 | 2023-03-02T11:31:10 | 2023-03-02T11:31:10 | 95,750,999 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,332 | py | # -*- coding: utf-8 -*-
''' For debugging SQL queries, (SOME ASSEMBLY REQUIRED!)
You need to:
- add a line to django.db.backends.utils.py, see details in stack_position
- configure excluded paths for stack traces to get cleaner output
'''
import logging
import re
import os
import traceback
from math import log as ln
from collections import defaultdict
import sqlparse
from sqlparse import keywords
# SQL keywords for colorization
KEYS = list(keywords.KEYWORDS.keys())
KEYS.extend(list(keywords.KEYWORDS_COMMON.keys()))
log = logging.getLogger(__name__)
_MINIBARS = [
'\033[1;32m|',
'\033[0;32m|',
'\033[0;33m|',
'\033[1;33m|',
'\033[1;31m|',
'\033[0;31m|',
]
_RESET = '\033[0m'
def _minilogbars(time):
bars = max(0, min(5, int(round(ln(time*100)))) if time != 0 else 0)
pad = ' ' * max(0, 5 - bars)
return '{bars}{reset}{pad}'.format(bars=''.join(_MINIBARS[:bars]), reset=_RESET, pad=pad)
#colorize_sql_regexp = re.compile(r"([^.])`([^`]*)`\.", re.IGNORECASE) # `(table)`.`...`
#colorize_sql_regexp_2 = re.compile(r"\.`([^`]*)`", re.IGNORECASE) # `table.`(field)`
colorize_sql_regexp_1_2 = re.compile(r"`([^`]*)`\.`([^`]*)`", re.IGNORECASE) # `(table)`.`(field)`
colorize_sql_regexp_3 = re.compile(r" `([^`]*)`[^.]", re.IGNORECASE) # `(table)`
colorize_sql_regexp_4 = re.compile(r'('+'[^A-Z]|'.join(KEYS)+r')') # KEYWORDS
colorize_sql_regexp_5 = re.compile(r'( [=<>] )') # comparators
def colorize_sql(sql):
#sql = colorize_sql_regexp.sub(r'\1\033[1;30m\2\033[0m.', sql)
#sql = colorize_sql_regexp_2.sub(r'.\033[0;34m\1\033[0m', sql)
sql = colorize_sql_regexp_1_2.sub(r'\033[1;30m\1\033[0m.\033[0;34m\2\033[0m', sql)
sql = colorize_sql_regexp_3.sub(r' \033[0;35m\1\033[0m ', sql)
sql = colorize_sql_regexp_4.sub(r'\033[0;33m\1\033[0m', sql)
sql = colorize_sql_regexp_5.sub(r'\033[0;31m\1\033[0m', sql)
return sql
def format_sql(sql):
return sqlparse.format(sql, reindent=True)
def print_query(query):
from .utils import uni
sqlstring = uni(query.__str__())
print(colorize_sql(format_sql(sqlstring)))
def sqlprint(data, filtering=True, tb=False):
'''
"Print SQL queries": {
"prefix": "dbusql",
"body": [
"from django.db import connection; # TODO: remove this debug\nfrom dbu import sql; sql.sqlprint(connection.queries) # TODO: remove this debug"
],
"description": "list sql queries"
}
also
"Reset SQL queries": {
"prefix": "dbusqlr",
"body": [
"from django.db import reset_queries; reset_queries() # TODO: remove this debug"
],
"description": "reset sql queries list"
}
'''
for row in data:
#row['sql'] = colorize_sql(row['sql'])
if filtering and float(row['time']) < 0.0001:
log.info("{} :".format(row['time']))
continue
location = '-'
if 'tb' in row:
location = _get_location(row['tb'])
sql = format_sql(row['sql'])
sql = colorize_sql(sql)
log.info("{time} {loc}\n{sql}\n".format(time=row['time'], loc=location, sql=sql))
new_line_replace = re.compile(r'(\n)')
def _indent_newlines(data, indentation=4):
sub_space = '\n' + (' ' * indentation)
return new_line_replace.sub(sub_space, data)
trace_exclude_paths = re.compile(r'/System|site-packages|wsgi\.py')
def __format_traceback_debug(tb):
for frame in tb:
if trace_exclude_paths.search(frame[0]):
continue
simple_file = os.path.basename(frame[0])
#print "<{f}:{l}:{m}> {t}".format(f=simple_file, l=frame[1], m=frame[2], t=frame[3])
print("{f}:{m}:{l:<4} > {t} \t ".format(f=frame[0], fs=simple_file, l=frame[1], m=frame[2], t=frame[3]))
print("")
def _format_traceback(tb):
#return '\n \033[0;35m>\033[0m '.join("\033[0;34m{file}\033[1;30m:\033[0;36m{module}\033[1;30m:\033[0;37m{linenum:<3}\033[0;35m :\033[0m {text}".format(file=os.path.basename(frame[0]), linenum=frame[1], module=frame[2], text=frame[3]) for frame in tb if not trace_exclude_paths.search(frame[0]))
#return '\n \033[0;35m>\033[0m '.join("\033[0;34m{file}\033[1;30m:\033[0;37m{linenum:<3}\033[1;30m:\033[0;36m{module}\033[0;35m :\033[0m {text}".format(file=os.path.basename(frame[0]), linenum=frame[1], module=frame[2], text=frame[3]) for frame in tb if not trace_exclude_paths.search(frame[0]))
#return '\n \033[0;35m>\033[0m '.join("\033[0;34m{file}\033[1;30m:\033[0;37m{linenum:<3} \033[0;36m{module}\033[0;35m:\033[0m {text}".format(file=os.path.basename(frame[0]), linenum=frame[1], module=frame[2], text=frame[3]) for frame in tb if not trace_exclude_paths.search(frame[0]))
return '\n \033[0;35m>\033[0m '.join("\033[0;34m{file}\033[1;30m:\033[0;37m{linenum:<3} \033[0;36m{module}\033[0m {text}".format(file=os.path.basename(frame[0]), linenum=frame[1], module=frame[2], text=frame[3]) for frame in tb if not trace_exclude_paths.search(frame[0]))
def _format_traceback2(tb, exclude=True):
# filea:123 ...
# filea:123 > 223 > fileb:323 ....
# filec:123 > filed:232 ...
# frame > frame > frame
# filter frames
if exclude:
filtered_tb = [frame for frame in tb if not trace_exclude_paths.search(frame[0])]
else:
filtered_tb = tb
last_index = len(filtered_tb) - 1
output_frames = []
prev_file = None
for i, frame in enumerate(filtered_tb):
output = ''
simple_file = os.path.basename(frame[0])
if simple_file != prev_file:
output = "\033[0;34m{file}\033[1;30m:\033[0;37m{linenum:<3}".format(file=os.path.basename(frame[0]), linenum=frame[1])
prev_file = simple_file
else:
output = "\033[0;37m{linenum:<3}".format(linenum=frame[1])
if i == last_index:
output += " \033[0;36m{module}\033[0m {text}".format(module=frame[2], text=frame[3])
output_frames.append(output)
return ' \033[0;35m>\033[0m '.join(output_frames)
def _get_location(tb):
relevant_frames = [frame for frame in tb if not trace_exclude_paths.search(frame[0])]
if len(relevant_frames) == 0:
return "."
frame = relevant_frames[-1]
return "\033[0;36m{module}(\033[1;30m…\033[0;36m) \033[1;30m[\033[0;34m{file}\033[1;30m:\033[0;37m{linenum:<3}\033[1;30m] \033[0m{text}".format(file=os.path.basename(frame[0]), linenum=frame[1], module=frame[2], text=frame[3])
_SQL_ID_PATTERN = re.compile(r'=\s*\d+')
def sqlcount(data, filtersmall=False, include_sql=False):
'''
"Count SQL queries": {
"prefix": "dbusqlcount",
"body": [
"from django.db import connection; # TODO: remove this debug\nfrom dbu import sql; sql.sqlcount(connection.queries) # TODO: remove this debug"
],
"description": "count number and total time of sql queries, show originating lines"
}
'''
counts = defaultdict(lambda: {'count':0.0, 'time':0.0, 'location': set()})
for row in data:
key = _SQL_ID_PATTERN.sub('= ?', row['sql'])
counts[key]['count'] += 1.0
time = float(row['time'])
if time == 0.001:
time = 0.0007
elif time == 0.000:
time = 0.0004
counts[key]['time'] += time
if 'trace' in row:
counts[key]['location'].add(_format_traceback2(row['trace']))
elif 'tb' in row:
counts[key]['location'].add(_format_traceback2(row['tb']))
results = [(val['count'], val['time'], val['location'], key) for key, val in list(counts.items()) if val['time'] > 0.01 or not filtersmall]
results.sort(key=lambda x: (x[0], x[1]), reverse=True)
total_count = 0
total_time = 0
out = ''
for count, time, location, sql in results:
if '' in location:
location.remove('')
out += "{: 4} / {:05.3f} [{}]: {}\n".format(int(count), time, _minilogbars(time), _indent_newlines('\n'.join(location), 22))
total_count += int(count)
total_time += time
if include_sql:
out += "{}\n\n".format(colorize_sql(sql))
out += "{: 4} / {:05.3f} [{}] Total".format(total_count, total_time, _minilogbars(total_time))
log.info('counts: \n{}'.format(out))
def stack_position():
return ' > '.join([f[2] for f in traceback.extract_stack()])
# ADD THIS TO django > db > backends > utils.py > CursorDebugWrapper
# self.db.queries_log.append({
# 'sql': sql,
# 'time': "%.3f" % duration,
# 'trace': stack_position(), # <-- THIS
# })
#
# def stack_position():
# import traceback
# return traceback.extract_stack()# ' > '.join([f[2] for f in traceback.extract_stack()])
# STACK
def format_stack():
# file, ln, function, text
for frame in traceback.extract_stack():
simple_file = os.path.basename(frame[0])
print("{m:>20.20}:{l:<4} > {t}".format(f=frame[0], fs=simple_file, l=frame[1], m=frame[2], t=frame[3]))
def format_stack2():
# file, ln, function, text
prev_file = None
for frame in traceback.extract_stack():
simple_file = os.path.basename(frame[0])
if simple_file == prev_file:
print("{l:<4} > {t}".format(f=frame[0], fs=simple_file, l=frame[1], m=frame[2], t=frame[3]))
else:
print("{m:>20.20}:{l:<4} > {t}".format(f=frame[0], fs=simple_file, l=frame[1], m=frame[2], t=frame[3]))
prev_file = simple_file
| [
"mulderns@iki.fi"
] | mulderns@iki.fi |
d018dae1106391a3d078188de5671e9268624e32 | 7dd3f071766dbac0fccaffa68644d86a1831e764 | /chapter_1/p1_7.py | 033399a950c867cd50ac57483f0f5d046e9cafd5 | [] | no_license | gaokang9009/CTCI_python | 22eb223d698e33b306bb21e16095d408363c3b2f | e28399c3b133af9913d0228c400aa67e4b113150 | refs/heads/master | 2023-01-04T13:44:51.936748 | 2020-09-23T21:09:57 | 2020-09-23T21:09:57 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 972 | py | from typing import List
def rotate(arr: List[List[int]]) -> List[List[int]]:
rot_help(arr, 0, len(arr[0])-1, 0, len(arr)-1)
return arr
def rot_help(arr, xl, xh, yl, yh):
if xl >= xh and yl >= yh:
print(f"Shorting 0 or 1 wide at {xl} to {xh}")
return
else:
rot_help(arr, xl+1, xh-1, yl+1, yh-1)
side = xh-xl
for i in range(side):
print(f"{i} of {side} side, w/ x:{xl}-{xh} y:{yl}-{yh}")
temp = arr[yl][xl+i] # Top left segment
arr[yl][xl+i] = arr[yh-i][xl] # Trasition 1
arr[yh-i][xl] = arr[yh][xh-i] # Transition 2
arr[yh][xh-i] = arr[yl+i][xh] # Transition 3
arr[yl+i][xh] = temp # Top right end
if __name__ == "__main__":
ex1 = [[1, 2, 3],
[8, 0, 4],
[7, 6, 5]]
rotate(ex1)
for line in ex1:
print(line)
ex2 = [[1, 2], [3, 4]]
rotate(ex2)
for line in ex2:
print(line)
| [
"bogdan.stoicescu17@imperial.ac.uk"
] | bogdan.stoicescu17@imperial.ac.uk |
812740cc28468da5b0b2168e7b0073a2145eca87 | fb8c088fb460fdb31f766044883c752b6315c93e | /daily14/test_ratings_key.py | 125bd7a5199bc706348c00b292f215c0ab33f117 | [] | no_license | gjakubik/paradigmsCollaboration | 9a3797e8dc73cef62995f7bb0677856be699f180 | 0e75c006e71e37c5f7e287d9d43e8f246f79857e | refs/heads/master | 2023-01-02T17:25:46.272412 | 2020-10-26T18:32:56 | 2020-10-26T18:32:56 | 300,013,084 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,082 | py | import unittest
import requests
import json
class TestRatings(unittest.TestCase):
SITE_URL = 'http://localhost:51068' # replace with your port id
print("Testing for server: " + SITE_URL)
RATINGS_URL = SITE_URL + '/ratings/'
RESET_URL = SITE_URL + '/reset/'
def reset_data(self):
m = {}
r = requests.put(self.RESET_URL)
def is_json(self, resp):
try:
json.loads(resp)
return True
except ValueError:
return False
def test_ratings_get_key(self):
self.reset_data()
movie_id = 32
r = requests.get(self.RATINGS_URL + str(movie_id))
#print("response is " + str(r.content.decode())) #debug
self.assertTrue(self.is_json(r.content.decode()))
resp = json.loads(r.content.decode())
self.assertEqual(resp['rating'], 3.945731303772336) # this is the value when user data is also considered
#self.assertEqual(resp['rating'], 0.0)
self.assertEqual(resp['movie_id'], movie_id)
if __name__ == "__main__":
unittest.main()
| [
"gjakubik@nd.edu"
] | gjakubik@nd.edu |
8df8770f43395ac195c0de00375b8098830b1db6 | 7670598360cdd28a75c17cbdc74eedcd2bcd916c | /driver/world.py | 80934c961a8e764d2d7b47851cda81b2b2fc0046 | [] | no_license | jordan-schneider/driver-env | d5663edffebd1acb4b53b81bff43a8a416152fa0 | 45a1c3ef478826ed33298f53bfa6d57d825b9e43 | refs/heads/main | 2023-06-05T01:06:34.891257 | 2021-06-17T01:40:42 | 2021-06-17T01:40:42 | 342,935,967 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,876 | py | """Base class for driving scenarios."""
from typing import Any, Dict, Iterable, List, Optional, Tuple
import numpy as np
import tensorflow as tf
from car.fixed_plan_car import FixedPlanCar, LegacyPlanCar # type: ignore
from driver.car import Car
class CarWorld:
"""
Contains the objects in a driving scenario - cars, lanes, obstacles, etc.
In addition, contains a step() function that increments the state of the
environment over time.
Finally, this class provides visualizations for the environment.
"""
def __init__(
self,
dt: float = 0.1,
lanes: Optional[List] = None,
obstacles: Optional[List] = None,
visualizer_args: Optional[Dict] = None,
**kwargs
):
"""
Initializes this CarWorld. Note: the visualizer is *not* initialized
until the first render() call.
Args:
dt: the time increment per tick of simulation.
lanes: a list of lanes this world should contain.
obstacles: a list of obstacles this world should contain.
visualizer_args: a dict of arguments for the visualizer.
**kwargs:
"""
self.cars: List[Car] = []
self.dt = dt
if lanes is None:
self.lanes = []
else:
self.lanes = lanes
if obstacles is None:
self.obstacles = []
else:
self.obstacles = obstacles
if visualizer_args is None:
self.visualizer_args = dict()
else:
self.visualizer_args = visualizer_args
self.visualizer: Optional[Any] = None
def add_car(self, car):
car.index = len(self.cars)
self.cars.append(car)
def add_cars(self, cars: Iterable):
for car in cars:
self.add_car(car)
@property
def state(self):
return [c.state for c in self.cars]
@state.setter
def state(self, new_state: Iterable):
for c, x in zip(self.cars, new_state):
c.state = x
def reset(self):
for car in self.cars:
car.reset()
if self.visualizer is not None:
self.visualizer.reset()
def step(
self, dt: Optional[float] = None
) -> Tuple[List[tf.Tensor], List[tf.Tensor], List[tf.Tensor]]:
"""
Asks all cars to generate plans, and then updates the world state based
on those plans
We need to split the plan generation and car state updating because
all the cars act at once (in the simulation)
Args:
dt: the amount of time to increment the simulation forward by.
Returns:
past_state: the previous state of the world, before this tick.
controls: the controls applied to all the cars in this timestep.
state: the current state of the world.
"""
past_state = self.state
if dt is None:
dt = self.dt
for car in self.cars:
if not car.control_already_determined_for_current_step:
car.set_next_control()
for car in self.cars:
car.step(dt)
return past_state, [c.control for c in self.cars], self.state
def render(self, mode: str = "human", heatmap_show=False) -> Optional[np.ndarray]:
"""
Renders the state of this car world. If mode="human", we display
it using the visualizer. If mode="rgb_array", we return a np.array
with shape (x, y, 3) representing RGB values, useful for making gifs
and videos.
Note: we currently assume that the main car is the first car in
self.cars.
Args:
mode: One of ["human", "rgb_array"].
Returns:
rgb_representation: if str="rgb_array", we return an np.array of
shape (x, y, 3), representing the rendered image.
TODO(chanlaw): add support for terminal visualization
"""
if self.visualizer is None:
from driver.visualizer import CarVisualizer
self.visualizer = CarVisualizer(world=self, **self.visualizer_args)
self.visualizer.set_main_car(index=0)
if mode == "human":
self.visualizer.render(display=True, return_rgb=False, heatmap_show=heatmap_show)
return None
elif mode == "rgb_array":
return self.visualizer.render(display=False, return_rgb=True, heatmap_show=heatmap_show)
else:
raise ValueError("Mode must be either `human` or `rgb_array`.")
class ThreeLaneCarWorld(CarWorld):
"""
A car world initialized with three straight lanes that extend for
a long while in either direction.
"""
def __init__(self, dt=0.1, **kwargs):
self.lane_width = 0.17
lane = StraightLane((0.0, -5.0), (0.0, 10.0), self.lane_width)
lanes = [lane.shifted(1), lane, lane.shifted(-1)]
super().__init__(dt=dt, lanes=lanes, **kwargs)
class TwoTrajectoryWorld(ThreeLaneCarWorld):
def __init__(self, dt, good_plan, bad_plan, **kwargs):
super().__init__(
dt=dt, visualizer_args={"legacy_state": True, "follow_main_car": True}, **kwargs
)
# state = [x, y, angel, vel]
self.good_car = FixedPlanCar(
env=self,
init_state=[0.0, -0.3, np.pi / 2.0, 0.4],
plan=good_plan,
color="blue",
legacy_state=True,
)
self.bad_car = FixedPlanCar(
env=self,
init_state=[0.0, -0.3, np.pi / 2.0, 0.4],
plan=bad_plan,
color="red",
legacy_state=True,
)
self.other_car = LegacyPlanCar(env=self)
self.add_cars([self.good_car, self.bad_car, self.other_car])
class TwoLaneCarWorld(CarWorld):
def __init__(self, dt=0.1, **kwargs):
lane = StraightLane((-0.05, -5.0), (-0.05, 10.0), 0.1)
lanes = [lane, lane.shifted(-1)]
super().__init__(dt=dt, lanes=lanes, **kwargs)
class StraightLane(object):
"""
Defines a lane with median defined by the line segment between points
p and q, and width w.
TODO(chanlaw): need to implement roads that aren't line segments
"""
def __init__(self, p: Tuple[float, float], q: Tuple[float, float], w: float):
"""
Initializes the straight lane.
Args:
p: the x,y coordinates of the start point for the center of the lane
q: the x,y coordinates of the end point for the center of the lane
w: the width of the lane
"""
self.p = np.asarray(p)
self.q = np.asarray(q)
self.w = w
self.m = (self.q - self.p) / np.linalg.norm(
self.q - self.p
) # unit vector in direction of lane
self.n = np.asarray([-self.m[1], self.m[0]]) # normal vector to the lane
def shifted(self, n_lanes: int):
"""
Returns a lane that is shifted n_lanes in the direction of self.n.
When n_lanes < 0, this is shifted in the other direction instead.
Args:
n_lanes: number of lanes to shift
Returns:
(StraightLane): a straight lane shifted in the appropriate way.
"""
return StraightLane(
self.p + self.n * self.w * n_lanes, self.q + self.n * self.w * n_lanes, self.w
)
def dist2median(self, point: Tuple[float, float]):
"""
Returns the squared distance of a point to the median of the lane.
Args:
point: the x,y coordinates of the point.
Returns:
(float): the distance to the median of this lane
"""
r = (point[0] - self.p[0]) * self.n[0] + (point[1] - self.p[1]) * self.n[1]
return r ** 2
def on_road(self, point):
raise NotImplementedError
| [
"jordan.jack.schneider@gmail.com"
] | jordan.jack.schneider@gmail.com |
895889f61a87b66537421257604f1a6e97cb00b0 | 91ff50a612aaa081ed89dc6ce529ddcac3a054cb | /scripts/cluster_init.py | 4e9c3384aca2a6ada678726a1fd31535f34b4539 | [] | no_license | wgantt/event_type_induction | 85f13715a39683015670d290196cedd0e46dd394 | 52959012756efb5a1bd328e35ff4094a2722a555 | refs/heads/master | 2023-08-04T06:51:19.273433 | 2021-09-12T19:36:37 | 2021-09-12T19:52:42 | 286,784,794 | 7 | 0 | null | null | null | null | UTF-8 | Python | false | false | 38,703 | py | # Package external imports
import argparse
from decomp import UDSCorpus
import numpy as np
import random
from sklearn.mixture import GaussianMixture
import torch
from torch.nn import Parameter, ParameterDict, Module
from typing import List
# Package internal imports
from event_type_induction.constants import *
from event_type_induction.modules.vectorized_likelihood import *
from scripts.setup_logging import setup_logging
from event_type_induction.utils import *
LOG = setup_logging()
class GMM:
def __init__(
self,
uds: UDSCorpus,
random_seed: int = 42,
use_ordinal: bool = False,
device: str = "cpu",
):
"""Gaussian mixture model over UDS properties
Parameters
----------
uds
the UDSCorpus
random_seed
optional random seed to use for the mixture model
use_ordinal
determines whether ordinal properties should actually be
represented as scalar interval values or as categorical ones
device
the device on which data tensors are to be created
"""
self.uds = uds
self.s_metadata = self.uds.metadata.sentence_metadata
self.d_metadata = self.uds.metadata.document_metadata
self.random_seed = random_seed
self.use_ordinal = use_ordinal
self.device = device
self.str_to_category = {
cat: idx
for idx, cat in enumerate(
self.uds.metadata.sentence_metadata["time"]["duration"].value.categories
)
}
self.annotation_func_by_type = {
Type.EVENT: self.get_event_annotations,
Type.PARTICIPANT: self.get_participant_annotations,
Type.ROLE: self.get_role_annotations,
Type.RELATION: self.get_relation_annotations,
}
def get_annotations(
self,
t: Type,
data: List[str],
confidences: Dict[str, Dict[int, float]],
property_means: Dict[str, np.ndarray],
device: str = "cpu",
):
"""Retrieves annotations from a UDSCorpus for a specified type
Should definitely be factored out into utils or something; I just
haven't taken the time yet.
Parameters
----------
t
the type for which annotations should be retrieved
data
a list of identifiers for UDSSentenceGraphs, for which
the annotations are to be retrieved
confidences
ridit-scored confidence values for each annotator, keyed on
annotator name. Nested dict
property_means
pre-computed mean values for each property; these are used to
impute missing annotations for each item
device
the device on which all the tensors are to be created
"""
# Averaged annotations for each item
all_annotations = []
# Maps properties to a range of indices in the annotation vector
# for each item
properties_to_indices = {}
# All (raw) annotations, grouped by property
annotations_by_property = DefaultOrderedDict(list)
# Annotators corresponding to each annotation in annotations_by_property
annotators_by_property = DefaultOrderedDict(list)
# Confidence scores for each annotation in annotations_by_property
confidences_by_property = DefaultOrderedDict(list)
# Item IDs corresponding to each annotation in annotations_by_property
items_by_property = DefaultOrderedDict(list)
# Maps integer IDs to UDS node/edge names
idx_to_item = DefaultOrderedDict(str)
# Unique annotators for each property
unique_annotators_by_property = DefaultOrderedDict(set)
# The length of a full annotation vector
anno_vec_len = 0
# Counts total nodes or edges
item_ctr = 0
for name in data:
graph = self.uds[name]
for item, anno in get_item_iter(graph, t):
anno_vec = []
annotation_found = False
if t == Type.ROLE and (
("protoroles" not in anno) or ("distributivity" not in anno)
):
# We subset to only those edges annotated for both
# protoroles and distributivity to avoid having to
# do heavy imputation
continue
for subspace in sorted(SUBSPACES_BY_TYPE[t]):
for p in sorted(self.s_metadata.properties(subspace)):
prop_dim = get_prop_dim(
self.s_metadata, subspace, p, use_ordinal=self.use_ordinal
)
vec = np.zeros(prop_dim)
# The genericity subspace includes properties associated
# with both events and participants. We need to mask the
# ones that aren't relevant in each case
if (t == Type.EVENT and "arg" in p) or (
t == Type.PARTICIPANT and "pred" in p
):
continue
# The distributive property is listed under the event_structure
# subspace, but is not relevant to event types
if t == Type.EVENT and p == "distributive":
continue
# Associate the current property with a range of indices
# in the annotation vector
if p not in properties_to_indices:
properties_to_indices[p] = np.array(
[anno_vec_len, anno_vec_len + prop_dim]
)
anno_vec_len += prop_dim
# Process annotations for this item only if they actually exist
n_annos = 0 # number of annotations for this item
if subspace in anno and p in anno[subspace]:
annotation_found = True
for a, value in anno[subspace][p]["value"].items():
# Confidence for current annotation
# ---------------------------------
conf = anno[subspace][p]["confidence"][a]
ridit_conf = confidences[a]
if (
ridit_conf is None
or ridit_conf.get(conf) is None
or ridit_conf[conf] < 0
): # invalid confidence values; default to 1
ridit_conf = 1
else:
ridit_conf = ridit_conf.get(conf, 1)
# Value for current annotation
# ----------------------------
# Special case 1: None values (i.e. property was annotated as "doesn't apply")
if value is None:
# This should only be true of conditional properties
assert (
p in CONDITIONAL_PROPERTIES
), f"unexpected None value for property {p}"
# If this is an ordinal property, and we're treating ordinal variables
# as such, we set the "does not apply" value to the mean ordinal value
if (
self.use_ordinal
and self.s_metadata[subspace][
p
].value.is_ordered_categorical
):
val = np.nan
# Otherwise, the "does not apply" case corresponds to the last category
# when treating ordinal variables nominally.
else:
val = prop_dim - 1
# Special case 2: String values (should only be duration annotations)
elif isinstance(value, str):
assert (
p == "duration"
), f"unexpected string value for property {p}"
val = self.str_to_category[value]
# Special case 3: Protoroles properties
elif subspace == "protoroles":
if conf == 0:
if self.use_ordinal:
val = np.nan
ridit_conf = conf
else:
val = prop_dim - 1
ridit_conf = 1
else:
val = value
ridit_conf = 1
# Default case: all other properties
else:
val = value
if prop_dim == 1: # binary or ordinal
if not self.s_metadata[subspace][
p
].value.is_ordered_categorical:
assert (
val == 0 or val == 1
), f"non-binary value for binary property {p}"
if not np.isnan(val):
vec[0] += val
else: # categorical
vec[val] += 1
# Raw annotations and confidences by property
annotations_by_property[p].append(val)
items_by_property[p].append(item_ctr)
idx_to_item[item_ctr] = item
annotator_num = int(a.split("-")[-1])
annotators_by_property[p].append(annotator_num)
unique_annotators_by_property[p].add(annotator_num)
confidences_by_property[p].append(ridit_conf)
if not np.isnan(val):
n_annos += 1
else:
# No annotation for this property, so just use the mean
vec = property_means[p]
# Compute average annotation for this item; for all
# train data, there will be only one annotation
"""
assert (
n_annos <= 3
), f"{n_annos} annotations found for property {p} on item {item}"
"""
anno_vec.append(vec / max(n_annos, 1))
# Append current annotation vector to list of all
# annotation vectors (but only if we actually found
# relevant annotations)
if annotation_found:
all_annotations.append(np.concatenate(anno_vec))
item_ctr += 1
return (
np.stack(all_annotations),
properties_to_indices,
{
p: torch.FloatTensor(np.stack(v)).to(device)
for p, v in annotations_by_property.items()
},
{
p: torch.LongTensor(np.array(v)).to(device)
for p, v in items_by_property.items()
},
idx_to_item,
{
p: torch.FloatTensor(np.array(v)).to(device)
for p, v in confidences_by_property.items()
},
{
p: torch.LongTensor(np.array(v)).to(device)
for p, v in annotators_by_property.items()
},
unique_annotators_by_property,
)
def get_event_annotations(
self,
data: List[str],
confidences: Dict[str, Dict[int, float]],
property_means: Dict[str, np.ndarray],
device: str = "cpu",
):
return self.get_annotations(
Type.EVENT, data, confidences, property_means, device
)
def get_participant_annotations(
self,
data: List[str],
confidences: Dict[str, Dict[int, float]],
property_means: Dict[str, np.ndarray],
device: str = "cpu",
):
return self.get_annotations(
Type.PARTICIPANT, data, confidences, property_means, device
)
def get_role_annotations(
self,
data: List[str],
confidences: Dict[str, Dict[int, float]],
property_means: Dict[str, np.ndarray],
device: str = "cpu",
):
return self.get_annotations(
Type.ROLE, data, confidences, property_means, device
)
def get_relation_annotations(
self,
data: List[str],
confidences: Dict[str, Dict[int, float]],
property_means: Dict[str, np.ndarray],
device: str = "cpu",
):
all_annotations = []
annotations_by_property = DefaultOrderedDict(list)
items_by_property = DefaultOrderedDict(list)
idx_to_item = DefaultOrderedDict(str)
annotators_by_property = DefaultOrderedDict(list)
unique_annotators_by_property = DefaultOrderedDict(set)
confidences_by_property = DefaultOrderedDict(list)
properties_to_indices = {}
anno_vec_len = 0
item_ctr = 0
for dname in data:
graph = self.uds.documents[dname].document_graph
for edge, anno in sorted(graph.edges.items()):
anno_vec = []
if "mereology" in anno and "time" not in anno:
continue
for subspace in sorted(SUBSPACES_BY_TYPE[Type.RELATION]):
for p in sorted(self.d_metadata.properties(subspace)):
vec = np.zeros(1)
n_annos = 0
# Associate this property with a range of indices in the type vector
if p not in properties_to_indices:
properties_to_indices[p] = np.array(
[anno_vec_len, anno_vec_len + 1]
)
anno_vec_len += 1
# Collect annotation and confidence
if subspace in anno and p in anno[subspace]:
for a, value in sorted(anno[subspace][p]["value"].items()):
# Get confidence for this annotation
conf = anno[subspace][p]["confidence"][a]
ridit_conf = confidences[a].get(conf, 1)
# Get value
vec += value
# Bookkeeping
n_annos += 1
annotations_by_property[p].append(value)
items_by_property[p].append(item_ctr)
idx_to_item[item_ctr] = edge
annotator_num = int(a.split("-")[-1])
annotators_by_property[p].append(annotator_num)
unique_annotators_by_property[p].add(annotator_num)
confidences_by_property[p].append(ridit_conf)
else:
# Since mereology annotations were conditioned on
# temporal containment, if they don't occur in a
# given annotation, there cannot be mereological
# containment, so we default to zero.
assert subspace == "mereology"
vec = torch.zeros(1)
# Average annotation for this item
anno_vec.append(vec / max(n_annos, 1))
all_annotations.append(np.concatenate(anno_vec))
item_ctr += 1
return (
np.stack(all_annotations),
properties_to_indices,
{
p: torch.FloatTensor(np.stack(v)).to(device)
for p, v in annotations_by_property.items()
},
{
p: torch.LongTensor(np.array(v)).to(device)
for p, v in items_by_property.items()
},
idx_to_item,
{
p: torch.FloatTensor(np.array(v)).to(device)
for p, v in confidences_by_property.items()
},
{
p: torch.LongTensor(np.array(v)).to(device)
for p, v in annotators_by_property.items()
},
unique_annotators_by_property,
)
def fit(
self,
data: List[str],
t: Type,
n_components: int,
confidences: Dict[str, Dict[int, float]],
) -> GaussianMixture:
gmm = GaussianMixture(n_components, random_state=self.random_seed)
if t == Type.RELATION:
property_means = None
else:
property_means = get_sentence_property_means(
self.uds, data, t, use_ordinal=self.use_ordinal
)
(
average_annotations,
properties_to_indices,
annotations_by_property,
items_by_property,
idx_to_item,
confidences_by_property,
annotators_by_property,
unique_annotators_by_property,
) = self.annotation_func_by_type[t](
data, confidences, property_means, self.device
)
gmm = gmm.fit(average_annotations)
LOG.info(
f"GMM average train LL for {n_components} components: {gmm.score(average_annotations)}"
)
# Probably shouldn't be returning all these things from a call to
# "fit", but didn't want to have to separately call the annotation
# getter function again
return (
gmm,
average_annotations,
properties_to_indices,
annotations_by_property,
items_by_property,
idx_to_item,
confidences_by_property,
annotators_by_property,
unique_annotators_by_property,
)
class MultiviewMixtureModel(Module):
def __init__(
self,
uds: UDSCorpus,
random_seed: int = 42,
use_ordinal: bool = False,
device: str = "cpu",
):
super(MultiviewMixtureModel, self).__init__()
self.uds = uds
self.random_seed = random_seed
self.s_metadata = self.uds.metadata.sentence_metadata
self.d_metadata = self.uds.metadata.document_metadata
self.type_to_likelihood = {
Type.EVENT: PredicateNodeAnnotationLikelihood,
Type.PARTICIPANT: ArgumentNodeAnnotationLikelihood,
Type.ROLE: SemanticsEdgeAnnotationLikelihood,
Type.RELATION: DocumentEdgeAnnotationLikelihood,
}
self.type_to_annotator_ids = {
Type.EVENT: load_pred_node_annotator_ids,
Type.PARTICIPANT: load_arg_node_annotator_ids,
Type.ROLE: load_sem_edge_annotator_ids,
Type.RELATION: load_doc_edge_annotator_ids,
}
self.mus = None
self.component_weights = None
self.random_effects = None
self.final_train_posteriors = None
self.final_dev_posteriors = None
self.train_idx_to_item = None
self.dev_idx_to_item = None
self.use_ordinal = use_ordinal
self.device = device
def _init_mus(
self,
t: Type,
gmm_means: np.ndarray,
props_to_indices: Dict[str, np.ndarray],
n_components: int,
) -> None:
mu_dict = {}
if t == Type.RELATION:
metadata = self.d_metadata
else:
metadata = self.s_metadata
for subspace in SUBSPACES_BY_TYPE[t]:
for p in metadata.properties(subspace):
# Random effects for relation types handled below
if "rel-" in p:
continue
# Restrict genericity to either argument or predicate
# depending on the type we're clustering on
if (t == Type.EVENT and "arg" in p) or (
t == Type.PARTICIPANT and "pred" in p
):
continue
# Most means for the mixture model are set based on
# the GMM means
start, end = props_to_indices[p]
mu = torch.FloatTensor(gmm_means[:, start:end])
min_mean = torch.ones(mu.shape) * MIN_MEAN
mu = torch.where(mu > MIN_MEAN, mu, min_mean)
# We apply different mean initialization strategies based on
# property type
is_ordinal = metadata[subspace][p].value.is_ordered_categorical
if self.use_ordinal and is_ordinal:
# Ordinal conditional properties are modeled using a hurdle
# model, so we initialize a mean for the Bernoullis that
# indicate whether the property applies or not.
if p in CONDITIONAL_PROPERTIES:
mu_applies = Parameter(logit(torch.ones(n_components) * 0.5))
mu_dict[p.replace(".", "-") + "-applies"] = mu_applies
# For all ordinal properties, we subtract off the median
# of the ordinal scale (this is 2 for protoroles)
if subspace == "protoroles":
median = 2
else:
median = len(metadata[subspace][p].value.categories) // 2
mu -= median
# For binary properties, we apply a logit to the GMM mean
elif mu.shape[-1] == 1:
mu = logit(mu)
# All other means are stored in log form
else:
mu = torch.log(mu)
mu_dict[p.replace(".", "-")] = Parameter(mu)
if t == Type.RELATION:
# Randomly initialize probabilities that
# 1. The events' start points are locked to 0.
# 2. The events' end points are locked to 100.
# 3. The events' midpoints are locked to each other.
# Note: I tried an initialization based on the GMM clusters,
# but this led to radical overfitting.
# The three dimensions of these distributions correspond
# to the probabilities that 1) both points are locked; 2) only
# e1's point is locked; 3) only e2's point is locked
mu_dict["time-lock_start_mu"] = Parameter(
torch.log(torch.softmax(torch.randn((n_components, 3)), -1))
)
mu_dict["time-lock_end_mu"] = Parameter(
torch.log(torch.softmax(torch.randn((n_components, 3)), -1))
)
# The three dimensions of these distributions correspond to
# the probabailities that 1) e1's midpoint equals e2's midpoint;
# 2) e1's midpoint comes before e2's; 3) e2's comes before e1's.
mu_dict["time-lock_mid_mu"] = Parameter(
torch.log(torch.softmax(torch.randn((n_components, 3)), -1))
)
self.mus = ParameterDict(mu_dict).to(self.device)
def _get_annotator_ridits(
self, data: List[str], t: Type
) -> Dict[str, Dict[int, float]]:
annotator_ids = self.type_to_annotator_ids[t](self.uds)
if t == Type.RELATION:
ridits = ridit_score_confidence(self.uds, sents=data)
else:
ridits = ridit_score_confidence(self.uds, docs=data)
return {a: ridits.get(a) for a in annotator_ids}
def fit(
self,
data: Dict[str, List[str]],
t: Type,
n_components: int,
iterations: int = 10000,
lr: float = 0.001,
clip_min_ll=False,
confidence_weighting=False,
patience: int = 1,
verbosity: int = 10,
) -> "MultiviewMixtureModel":
random.seed(self.random_seed)
torch.manual_seed(self.random_seed)
LOG.info(
f"Fitting model on type {t.name} using {n_components} components on device {self.device}"
)
LOG.info("Fitting GMM...")
train_confidences = self._get_annotator_ridits(data["train"], t)
train_gmm = GMM(self.uds, use_ordinal=self.use_ordinal, device=self.device)
(
gmm,
train_avg_annotations,
train_properties_to_indices,
train_annotations_by_property,
train_items_by_property,
self.train_idx_to_item,
train_confidences_by_property,
train_annotators_by_property,
train_unique_annotators_by_property,
) = train_gmm.fit(data["train"], t, n_components, train_confidences)
LOG.info("...GMM fitting complete")
LOG.info("Loading dev data...")
dev_confidences = self._get_annotator_ridits(data["dev"], t)
# Determine the total number of train items annotated across all properties
train_items = set()
for train_item in train_items_by_property.values():
train_items |= set(train_item.tolist())
total_train_items = len(train_items)
train_items = torch.LongTensor(list(train_items)).to(self.device)
if t == Type.RELATION:
dev_property_means = None
else:
dev_property_means = get_sentence_property_means(
self.uds, data["dev"], t, self.use_ordinal
)
(
dev_avg_annotations,
dev_properties_to_indices,
dev_annotations_by_property,
dev_items_by_property,
self.dev_idx_to_item,
dev_confidences_by_property,
dev_annotators_by_property,
dev_unique_annotators_by_property,
) = train_gmm.annotation_func_by_type[t](
data["dev"], dev_confidences, dev_property_means, device=self.device
)
# Determine the total number of dev items annotated across all properties
dev_items = set()
for dev_item in dev_items_by_property.values():
dev_items |= set(dev_item.tolist())
total_dev_items = len(dev_items)
dev_items = torch.LongTensor(list(dev_items)).to(self.device)
LOG.info("...Complete.")
LOG.info(f"total train items: {total_train_items}")
LOG.info(f"total dev items: {total_dev_items}")
# verify that annotations and confidence values are as expected
assert (
train_annotations_by_property.keys() == train_confidences_by_property.keys()
)
for p in train_annotations_by_property:
anno_len = len(train_annotations_by_property[p])
conf_len = len(train_confidences_by_property[p])
num_annotators = len(train_annotators_by_property[p])
assert (
anno_len == conf_len
), f"mismatched annotation and confidence lengths ({anno_len} and {conf_len}) for property {p}"
assert (
num_annotators == anno_len
), f"mismatched annotation and annotator lengths ({anno_len} and {num_annotators})"
# Determine which annotators in dev are also in train
# This is necessary for determining the appropriate random
# effects for each annotator
dev_annotators_in_train = {}
for p, dev_annos in dev_annotators_by_property.items():
new_dev = len(
dev_unique_annotators_by_property[p]
- train_unique_annotators_by_property[p]
)
train_annos = train_unique_annotators_by_property[p]
dev_annotators_in_train[p] = torch.BoolTensor(
[a.item() in train_annos for a in dev_annos]
)
train_unique_annotators_by_property[p] = torch.LongTensor(
list(train_unique_annotators_by_property[p])
)
# Get the right type of property metadata (document metadata for
# relation types; sentence metadata for everything else)
if t == Type.RELATION:
metadata = self.d_metadata
else:
metadata = self.s_metadata
# Initialize Likelihood module, property means,
# annotator random effects, and component weights
ll = self.type_to_likelihood[t](
train_confidences,
metadata,
n_components,
use_ordinal=self.use_ordinal,
clip_min_ll=clip_min_ll,
confidence_weighting=confidence_weighting,
device=self.device,
)
self._init_mus(t, gmm.means_, train_properties_to_indices, n_components)
self.random_effects = ll.random_effects
self.component_weights = Parameter(
torch.log(torch.FloatTensor(gmm.weights_)).to(self.device)
)
optimizer = torch.optim.Adam(self.parameters(), lr=lr)
min_train_fixed_loss = float("inf")
min_dev_fixed_loss = float("inf")
iters_without_improvement = 0
LOG.info(f"Beginning training for {iterations} epochs")
for i in range(iterations):
# training
_, train_ll = ll(
self.mus,
train_annotations_by_property,
train_items_by_property,
train_annotators_by_property,
train_confidences_by_property,
)
# per-type likelihoods for all items
train_fixed_loss = train_ll
# add in prior over components
prior = exp_normalize(self.component_weights)[:, None]
train_posteriors = train_fixed_loss[:, train_items] + prior
# logsumexp over all components to get log-evidence for each item
train_fixed_loss = (
-torch.logsumexp(train_posteriors, 0).sum() / total_train_items
)
# add in random loss, backprop, and take gradient step
train_random_loss = ll.random_loss()
train_loss = train_fixed_loss + train_random_loss
train_loss.backward()
optimizer.step()
# train logging
if i % verbosity == 0:
LOG.info(
f"component weights: {torch.exp(exp_normalize(self.component_weights))}"
)
LOG.info(f"Epoch {i} train log prior: {self.component_weights.data}")
LOG.info(f"Epoch {i} train log likelihood: {train_ll.mean(-1)}")
LOG.info(
f"Epoch {i} train fixed loss: {np.round(train_fixed_loss.item(), 5)}"
)
LOG.info(
f"Epoch {i} train random loss: {np.round(train_random_loss.item(), 5)}"
)
# eval
with torch.no_grad():
_, dev_ll = ll(
self.mus,
dev_annotations_by_property,
dev_items_by_property,
dev_annotators_by_property,
dev_confidences_by_property,
train_unique_annotators_by_property,
dev_annotators_in_train,
)
# dev fixed loss computed the same way as train
dev_fixed_loss = dev_ll
dev_posteriors = dev_fixed_loss[:, dev_items] + prior
dev_fixed_loss = (
-torch.logsumexp(dev_posteriors, 0).sum() / total_dev_items
)
if i % verbosity == 0:
LOG.info(
f"Epoch {i} dev fixed loss: {np.round(dev_fixed_loss.item(), 5)}"
)
# stop early if no improvement in dev
if dev_fixed_loss < min_dev_fixed_loss:
min_dev_fixed_loss = dev_fixed_loss
iters_without_improvement = 0
else:
iters_without_improvement += 1
# since we're doing full GD, there's no real sense in setting
# patience to anything other than 1
if iters_without_improvement == patience:
self.final_train_posteriors = train_posteriors
self.final_dev_posteriors = dev_posteriors
LOG.info(
f"No improvement in dev LL for model with {n_components} components after {patience} iterations. Stopping early."
)
LOG.info(
f"Final component weights (epoch {i}): {torch.exp(exp_normalize(self.component_weights))}"
)
LOG.info(
f"Final train fixed loss (epoch {i}): {np.round(train_fixed_loss.item(), 5)}"
)
LOG.info(
f"Final dev fixed loss (epoch {i}): {np.round(dev_fixed_loss.item(), 5)}"
)
return self.eval()
LOG.info(f"Max iterations reached")
LOG.info(
f"Final component weights (epoch {i}): {torch.exp(exp_normalize(self.component_weights))}"
)
LOG.info(
f"Final train fixed loss (epoch {i}): {np.round(train_fixed_loss.item(), 5)}"
)
LOG.info(
f"Final dev fixed loss (epoch {i}): {np.round(dev_fixed_loss.item(), 5)}"
)
self.final_train_posteriors = train_posteriors
self.final_dev_posteriors = dev_posteriors
return self.eval()
def main(args):
assert (
args.min_types <= args.max_types
), f"min types must be less than or equal to max!"
# Load UDS and initialize the mixture model
uds = UDSCorpus(version="2.0", annotation_format="raw")
load_event_structure_annotations(uds)
# Define train and dev splits
t = STR_TO_TYPE[args.type.upper()]
if t == Type.RELATION:
train = sorted(
set([graph.document_id for name, graph in uds.items() if "train" in name])
)
dev = sorted(
set([graph.document_id for name, graph in uds.items() if "dev" in name])
)
else:
train = [s for s in uds if "train" in s]
dev = [s for s in uds if "dev" in s]
data = {"train": train, "dev": dev}
LOG.info(
f"Fitting mixture model with all types in range {args.min_types} to {args.max_types}, inclusive"
)
model_root = args.model_name if args.model_name is not None else t.name
for n_components in range(args.min_types, args.max_types + 1):
# Initialize and fit the model
mmm = MultiviewMixtureModel(uds, use_ordinal=True, device=args.device)
model_name = model_root + "-" + str(n_components) + ".pt"
mmm = mmm.fit(
data,
t,
n_components,
clip_min_ll=args.clip_min_ll,
confidence_weighting=args.weight_by_confidence,
patience=args.patience,
)
# Save it
save_model(mmm.state_dict(), args.model_dir, model_name)
# Dump property means to file
if args.dump_means:
means_file = "-".join([model_root, str(n_components), "means"]) + ".csv"
means_file = os.path.join(args.model_dir, means_file)
dump_params(means_file, mmm.mus)
# Dump per-item posteriors to file
if args.dump_posteriors:
posteriors_file = (
"-".join([model_root, str(n_components), "posteriors"]) + ".csv"
)
posteriors_file = os.path.join(args.model_dir, posteriors_file)
dump_mmm_posteriors(
posteriors_file,
mmm.final_train_posteriors,
mmm.train_idx_to_item,
mmm.final_dev_posteriors,
mmm.dev_idx_to_item,
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("type", type=str, help="the type to cluster on")
parser.add_argument(
"min_types", type=int, help="minimum of range of numbers of types to try"
)
parser.add_argument(
"max_types", type=int, help="maximum of range of numbers of types to try"
)
parser.add_argument(
"--model_name", type=str, help="name for model checkpoint files"
)
parser.add_argument(
"--model_dir",
type=str,
default="/data/wgantt/event_type_induction/checkpoints/",
help="path to directory where checkpoint files are to be saved",
)
parser.add_argument(
"--dump_means", action="store_true", help="dump MMM property means to file",
)
parser.add_argument(
"--dump_posteriors",
action="store_true",
help="dump per-item MMM (log) posteriors to file",
)
parser.add_argument(
"--clip_min_ll",
action="store_true",
help="clip all likelihoods to a minimum value",
)
parser.add_argument(
"--weight_by_confidence",
action="store_true",
help="weight likelihoods by annotator confidence",
)
parser.add_argument(
"--patience",
type=int,
default=1,
help="number of epochs tolerated without dev improvement",
)
parser.add_argument("--device", type=str, default="cpu")
args = parser.parse_args()
main(args)
| [
"wgantt.iv@gmail.com"
] | wgantt.iv@gmail.com |
e47e26a1d21f99e42e90ad7c55badcdb1476659d | cbfb8897956669c1b3d12df21b98e32b4eedb74a | /api/app/models/base_model.py | 533e43772754174f31143bd563a16122deea19b5 | [] | no_license | jorgi710/PruebaAndres | 1c449b61079b7a4239b66a19a3a66479561518cd | 849d80a231ca210df3c7740a90180656d31fefb9 | refs/heads/master | 2023-08-24T04:50:40.374300 | 2021-10-30T17:08:15 | 2021-10-30T17:08:15 | 422,941,450 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,449 | py | # -*- coding: utf-8 -*-
#########################################################
from datetime import datetime
from app import db
from app.exception import InternalServerError
class BaseModel(db.Model):
__abstract__ = True
id = db.Column(db.Integer, primary_key=True, nullable=False)
create_date = db.Column(db.DateTime, default=db.func.now(), comment='Fecha de creación')
update_date = db.Column(db.DateTime, default=db.func.now(), onupdate=db.func.now(), comment='Fecha de Actualización')
def delete(self):
try:
db.session.delete(self)
db.session.commit()
except Exception as e:
print(e)
db.session.rollback()
raise InternalServerError(e)
def save(self):
try:
self.create_date = datetime.now()
self.update_date = datetime.now()
db.session.add(self)
db.session.flush()
db.session.commit()
return self
except Exception as e:
print(e)
db.session.rollback()
raise InternalServerError(e)
def update(self):
try:
self.update_date = datetime.now()
db.session.add(self)
db.session.flush()
db.session.commit()
return self
except Exception as e:
print(e)
db.session.rollback()
raise InternalServerError(e)
| [
"jorgi710@hotmail.com"
] | jorgi710@hotmail.com |
6a58e63d91a21db344180ef94deea98046c9a6e6 | b27e4c2f80f306fe758d77a03a9d626e5eea77cc | /zuri_one.py | ec60691af1f5a6acdbc6ace6b21860a76a05b56c | [] | no_license | Fredricknjeri/zuri_atm | 8e4919c2580486f661531620b46ec1d3f9098582 | fc6da81986083cfae33330e4ac3bf786248c9169 | refs/heads/main | 2023-04-18T16:07:05.404796 | 2021-04-24T13:25:09 | 2021-04-24T13:25:09 | 361,167,429 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,287 | py | from datetime import datetime
import time
import sys
username = input('What is your name?\n')
allowed_users = ['Fred', 'Monic', 'Tony','Mary']
passwords = ['fredpass','monicpass','tonypass','marypass']
amount = [50000,40000,100000,80000]
#progressbar
def update_progress(progress):
print('Processing...')
for i in range(progress +1):
time.sleep(0.01)
sys.stdout.write("\r%d%%" % i)
sys.stdout.flush()
print('')
def goodbye():
print('Thank you for your time, Goodbye!')
if(username in allowed_users):
auth = input('Please enter your password:\n')
userId = allowed_users.index(username)
if( auth == passwords[userId]):
print('Welcome', username)
print('These are the available of options:')
print('1. Withdraw')
print('2. Deposit')
print('3. Complaint')
#task 1
timenow = datetime.now()
now = timenow.strftime("%d/%m/%Y %H:%M:%S")
print(now)
selectedOption = int(input('Please select an option:\n'))
if(selectedOption == 1) :
print('You selected %s' %selectedOption)
withdraw_amount= int(input('How much do you want to withdraw:\n'))
update_progress(100)
print('take your cash')
currentbalance = amount[userId] - withdraw_amount
print('Your current balance:%d' %currentbalance)
time.sleep(1)
goodbye()
elif(selectedOption == 2):
print('You selected %s' %selectedOption)
deposit_amount = int(input('How much would you like to deposit?\n'))
update_progress(100)
time.sleep(1)
currentbalance = amount[userId] + deposit_amount
print('Current balance: %d' %currentbalance)
goodbye()
elif(selectedOption == 3):
print('You selected %s' %selectedOption)
report = input('What issue will you like to report?\n')
time.sleep(2)
print('Thank you for contacting us')
else:
print('Invalid option, Try again')
else:
print('Enter correct password!')
else:
print("You are not allowed to user the system!")
| [
"fredricknjeri@Fredricks-MacBook-Pro.local"
] | fredricknjeri@Fredricks-MacBook-Pro.local |
786b1d757a1cff4c034b72055eedc3bf6af0e80e | 95842c10eebe5cfb3e97bbe13134517180367bea | /venv/Scripts/pip3-script.py | ac080d5977424b134355c53cd6c27f1c0f045566 | [] | no_license | linaGitHub1/PyCharmProjects | 0fd2c0ebe3a2db9a0256d492364ea5b021686494 | e3953413b97f14abeb979baf8b9b801a9ac6ccd9 | refs/heads/master | 2021-01-04T06:00:42.300307 | 2020-02-14T06:56:41 | 2020-02-14T06:56:41 | 240,420,145 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 406 | py | #!D:\PyCharm\Lina\PyCharmProjects\venv\Scripts\python.exe
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==19.0.3','console_scripts','pip3'
__requires__ = 'pip==19.0.3'
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==19.0.3', 'console_scripts', 'pip3')()
)
| [
"lina_lemon@163.com"
] | lina_lemon@163.com |
29689d82e65139fffd325b2517ea32a511041d38 | 9734c93c86c982b1ce046340bac9e53645b261b8 | /tests/formatters/yaml_formatters_file.py | f69655c1080aa94b6d70e50bbc0002921e12694b | [
"Apache-2.0"
] | permissive | log2timeline/plaso | cd72dd407d6c5627506c14f58cb8f6a6926aa808 | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | refs/heads/main | 2023-09-02T08:43:48.241198 | 2023-08-19T07:28:12 | 2023-08-19T07:28:12 | 23,812,315 | 1,506 | 421 | Apache-2.0 | 2023-09-04T08:24:53 | 2014-09-08T23:29:28 | Python | UTF-8 | Python | false | false | 3,363 | py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for the YAML-based formatters file."""
import io
import unittest
from plaso.formatters import yaml_formatters_file
from plaso.lib import errors
from tests import test_lib as shared_test_lib
class YAMLFormattersFileTest(shared_test_lib.BaseTestCase):
"""Tests for the YAML-based formatters file."""
# pylint: disable=protected-access
_FORMATTERS_YAML = {
'type': 'conditional',
'data_type': 'test:fs:stat',
'message': [
'{display_name}',
'Type: {file_entry_type}',
'({unallocated})'],
'short_message': [
'{filename}'],
'short_source': 'SOURCE',
'source': 'My Custom Log Source'}
def testReadFormatterDefinition(self):
"""Tests the _ReadFormatterDefinition function."""
test_formatters_file = yaml_formatters_file.YAMLFormattersFile()
formatter = test_formatters_file._ReadFormatterDefinition(
self._FORMATTERS_YAML)
self.assertIsNotNone(formatter)
self.assertEqual(formatter.data_type, 'test:fs:stat')
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({})
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({'type': 'bogus'})
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({'type': 'conditional'})
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({
'type': 'conditional',
'data_type': 'test:fs:stat'})
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({
'type': 'conditional',
'data_type': 'test:fs:stat',
'message': [
'{display_name}',
'Type: {file_entry_type}',
'({unallocated})']})
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({
'type': 'conditional',
'data_type': 'test:fs:stat',
'message': [
'{display_name}',
'Type: {file_entry_type}',
'({unallocated})']})
with self.assertRaises(errors.ParseError):
test_formatters_file._ReadFormatterDefinition({'bogus': 'error'})
def testReadFromFileObject(self):
"""Tests the _ReadFromFileObject function."""
test_file_path = self._GetTestFilePath(['formatters', 'format_test.yaml'])
self._SkipIfPathNotExists(test_file_path)
test_formatters_file = yaml_formatters_file.YAMLFormattersFile()
with io.open(test_file_path, 'r', encoding='utf-8') as file_object:
formatters = list(test_formatters_file._ReadFromFileObject(file_object))
self.assertEqual(len(formatters), 2)
def testReadFromFile(self):
"""Tests the ReadFromFile function."""
test_file_path = self._GetTestFilePath(['formatters', 'format_test.yaml'])
self._SkipIfPathNotExists(test_file_path)
test_formatters_file = yaml_formatters_file.YAMLFormattersFile()
formatters = list(test_formatters_file.ReadFromFile(test_file_path))
self.assertEqual(len(formatters), 2)
self.assertEqual(formatters[0].data_type, 'test:event')
self.assertEqual(formatters[1].data_type, 'test:fs:stat')
if __name__ == '__main__':
unittest.main()
| [
"noreply@github.com"
] | noreply@github.com |
08283262024ac11a678bf93a86fc13799fde7db9 | c7231df2a4740dde9e19d4db174d3fbc3d617033 | /test/build/exe.win-amd64-3.5/PyQt5/_QOpenGLFunctions_2_1.pyi | c121336e38ab0a6ab5822ff9a0159402b3f3476d | [] | no_license | wangzhibinjunhua/python_test | c05c1b250dbabe13243c3e46af13efb25f0bd298 | ddd812e81e1ba1d82fdc525aff3e8b3a935b6f70 | refs/heads/master | 2021-10-03T10:54:23.561997 | 2018-12-03T01:33:11 | 2018-12-03T01:33:11 | 103,799,043 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 43,729 | pyi | # The PEP 484 type hints stub file for the _QOpenGLFunctions_2_1 module.
#
# Generated by SIP 4.18
#
# Copyright (c) 2016 Riverbank Computing Limited <info@riverbankcomputing.com>
#
# This file is part of PyQt5.
#
# This file may be used under the terms of the GNU General Public License
# version 3.0 as published by the Free Software Foundation and appearing in
# the file LICENSE included in the packaging of this file. Please review the
# following information to ensure the GNU General Public License version 3.0
# requirements will be met: http://www.gnu.org/copyleft/gpl.html.
#
# If you do not wish to use this file under the terms of the GPL version 3.0
# then you may purchase a commercial license. For more information contact
# info@riverbankcomputing.com.
#
# This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
# WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
import typing
import sip
from PyQt5 import QtGui
# Support for QDate, QDateTime and QTime.
import datetime
# Convenient type aliases.
PYQT_SIGNAL = typing.Union[QtCore.pyqtSignal, QtCore.pyqtBoundSignal]
PYQT_SLOT = typing.Union[typing.Callable[..., None], QtCore.pyqtBoundSignal]
# Convenient aliases for complicated OpenGL types.
PYQT_OPENGL_ARRAY = typing.Union[typing.Sequence[int], typing.Sequence[float],
sip.Buffer, None]
PYQT_OPENGL_BOUND_ARRAY = typing.Union[typing.Sequence[int],
typing.Sequence[float], sip.Buffer, int, None]
class QOpenGLFunctions_2_1(QtGui.QAbstractOpenGLFunctions):
def __init__(self) -> None: ...
def glVertexAttrib1d(self, index: int, x: float) -> None: ...
def glVertexAttrib1dv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib1f(self, index: int, x: float) -> None: ...
def glVertexAttrib1fv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib1s(self, index: int, x: int) -> None: ...
def glVertexAttrib1sv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib2d(self, index: int, x: float, y: float) -> None: ...
def glVertexAttrib2dv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib2f(self, index: int, x: float, y: float) -> None: ...
def glVertexAttrib2fv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib2s(self, index: int, x: int, y: int) -> None: ...
def glVertexAttrib2sv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib3d(self, index: int, x: float, y: float, z: float) -> None: ...
def glVertexAttrib3dv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib3f(self, index: int, x: float, y: float, z: float) -> None: ...
def glVertexAttrib3fv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib3s(self, index: int, x: int, y: int, z: int) -> None: ...
def glVertexAttrib3sv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4Nbv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4Niv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4Nsv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4Nub(self, index: int, x: int, y: int, z: int, w: int) -> None: ...
def glVertexAttrib4Nubv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4Nuiv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4Nusv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4bv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4d(self, index: int, x: float, y: float, z: float, w: float) -> None: ...
def glVertexAttrib4dv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4f(self, index: int, x: float, y: float, z: float, w: float) -> None: ...
def glVertexAttrib4fv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4iv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4s(self, index: int, x: int, y: int, z: int, w: int) -> None: ...
def glVertexAttrib4sv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4ubv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4uiv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertexAttrib4usv(self, index: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glFogCoordf(self, coord: float) -> None: ...
def glFogCoordfv(self, coord: PYQT_OPENGL_ARRAY) -> None: ...
def glFogCoordd(self, coord: float) -> None: ...
def glFogCoorddv(self, coord: PYQT_OPENGL_ARRAY) -> None: ...
def glFogCoordPointer(self, type: int, stride: int, pointer: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3b(self, red: int, green: int, blue: int) -> None: ...
def glSecondaryColor3bv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3d(self, red: float, green: float, blue: float) -> None: ...
def glSecondaryColor3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3f(self, red: float, green: float, blue: float) -> None: ...
def glSecondaryColor3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3i(self, red: int, green: int, blue: int) -> None: ...
def glSecondaryColor3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3s(self, red: int, green: int, blue: int) -> None: ...
def glSecondaryColor3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3ub(self, red: int, green: int, blue: int) -> None: ...
def glSecondaryColor3ubv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3ui(self, red: int, green: int, blue: int) -> None: ...
def glSecondaryColor3uiv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColor3us(self, red: int, green: int, blue: int) -> None: ...
def glSecondaryColor3usv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glSecondaryColorPointer(self, size: int, type: int, stride: int, pointer: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos2d(self, x: float, y: float) -> None: ...
def glWindowPos2dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos2f(self, x: float, y: float) -> None: ...
def glWindowPos2fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos2i(self, x: int, y: int) -> None: ...
def glWindowPos2iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos2s(self, x: int, y: int) -> None: ...
def glWindowPos2sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos3d(self, x: float, y: float, z: float) -> None: ...
def glWindowPos3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos3f(self, x: float, y: float, z: float) -> None: ...
def glWindowPos3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos3i(self, x: int, y: int, z: int) -> None: ...
def glWindowPos3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glWindowPos3s(self, x: int, y: int, z: int) -> None: ...
def glWindowPos3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glClientActiveTexture(self, texture: int) -> None: ...
def glMultiTexCoord1d(self, target: int, s: float) -> None: ...
def glMultiTexCoord1dv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord1f(self, target: int, s: float) -> None: ...
def glMultiTexCoord1fv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord1i(self, target: int, s: int) -> None: ...
def glMultiTexCoord1iv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord1s(self, target: int, s: int) -> None: ...
def glMultiTexCoord1sv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord2d(self, target: int, s: float, t: float) -> None: ...
def glMultiTexCoord2dv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord2f(self, target: int, s: float, t: float) -> None: ...
def glMultiTexCoord2fv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord2i(self, target: int, s: int, t: int) -> None: ...
def glMultiTexCoord2iv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord2s(self, target: int, s: int, t: int) -> None: ...
def glMultiTexCoord2sv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord3d(self, target: int, s: float, t: float, r: float) -> None: ...
def glMultiTexCoord3dv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord3f(self, target: int, s: float, t: float, r: float) -> None: ...
def glMultiTexCoord3fv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord3i(self, target: int, s: int, t: int, r: int) -> None: ...
def glMultiTexCoord3iv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord3s(self, target: int, s: int, t: int, r: int) -> None: ...
def glMultiTexCoord3sv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord4d(self, target: int, s: float, t: float, r: float, q: float) -> None: ...
def glMultiTexCoord4dv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord4f(self, target: int, s: float, t: float, r: float, q: float) -> None: ...
def glMultiTexCoord4fv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord4i(self, target: int, s: int, t: int, r: int, q: int) -> None: ...
def glMultiTexCoord4iv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glMultiTexCoord4s(self, target: int, s: int, t: int, r: int, q: int) -> None: ...
def glMultiTexCoord4sv(self, target: int, v: PYQT_OPENGL_ARRAY) -> None: ...
def glLoadTransposeMatrixf(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glLoadTransposeMatrixd(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glMultTransposeMatrixf(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glMultTransposeMatrixd(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glColorTable(self, target: int, internalformat: int, width: int, format: int, type: int, table: PYQT_OPENGL_ARRAY) -> None: ...
def glColorTableParameterfv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glColorTableParameteriv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glCopyColorTable(self, target: int, internalformat: int, x: int, y: int, width: int) -> None: ...
def glGetColorTableParameterfv(self, target: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetColorTableParameteriv(self, target: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int, int]]: ...
def glColorSubTable(self, target: int, start: int, count: int, format: int, type: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glCopyColorSubTable(self, target: int, start: int, x: int, y: int, width: int) -> None: ...
def glConvolutionFilter1D(self, target: int, internalformat: int, width: int, format: int, type: int, image: PYQT_OPENGL_ARRAY) -> None: ...
def glConvolutionFilter2D(self, target: int, internalformat: int, width: int, height: int, format: int, type: int, image: PYQT_OPENGL_ARRAY) -> None: ...
def glConvolutionParameterf(self, target: int, pname: int, params: float) -> None: ...
def glConvolutionParameterfv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glConvolutionParameteri(self, target: int, pname: int, params: int) -> None: ...
def glConvolutionParameteriv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glCopyConvolutionFilter1D(self, target: int, internalformat: int, x: int, y: int, width: int) -> None: ...
def glCopyConvolutionFilter2D(self, target: int, internalformat: int, x: int, y: int, width: int, height: int) -> None: ...
def glGetConvolutionParameterfv(self, target: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetConvolutionParameteriv(self, target: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int, int]]: ...
def glHistogram(self, target: int, width: int, internalformat: int, sink: int) -> None: ...
def glMinmax(self, target: int, internalformat: int, sink: int) -> None: ...
def glResetHistogram(self, target: int) -> None: ...
def glResetMinmax(self, target: int) -> None: ...
def glArrayElement(self, i: int) -> None: ...
def glColorPointer(self, size: int, type: int, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glDisableClientState(self, array: int) -> None: ...
def glEdgeFlagPointer(self, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glEnableClientState(self, array: int) -> None: ...
def glIndexPointer(self, type: int, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glNormalPointer(self, type: int, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glTexCoordPointer(self, size: int, type: int, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glVertexPointer(self, size: int, type: int, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glPopClientAttrib(self) -> None: ...
def glPushClientAttrib(self, mask: int) -> None: ...
def glNewList(self, list: int, mode: int) -> None: ...
def glEndList(self) -> None: ...
def glCallList(self, list: int) -> None: ...
def glDeleteLists(self, list: int, range: int) -> None: ...
def glGenLists(self, range: int) -> int: ...
def glListBase(self, base: int) -> None: ...
def glBegin(self, mode: int) -> None: ...
def glBitmap(self, width: int, height: int, xorig: float, yorig: float, xmove: float, ymove: float, bitmap: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3b(self, red: int, green: int, blue: int) -> None: ...
def glColor3bv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3d(self, red: float, green: float, blue: float) -> None: ...
def glColor3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3f(self, red: float, green: float, blue: float) -> None: ...
def glColor3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3i(self, red: int, green: int, blue: int) -> None: ...
def glColor3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3s(self, red: int, green: int, blue: int) -> None: ...
def glColor3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3ub(self, red: int, green: int, blue: int) -> None: ...
def glColor3ubv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3ui(self, red: int, green: int, blue: int) -> None: ...
def glColor3uiv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor3us(self, red: int, green: int, blue: int) -> None: ...
def glColor3usv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4b(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glColor4bv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4d(self, red: float, green: float, blue: float, alpha: float) -> None: ...
def glColor4dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4f(self, red: float, green: float, blue: float, alpha: float) -> None: ...
def glColor4fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4i(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glColor4iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4s(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glColor4sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4ub(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glColor4ubv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4ui(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glColor4uiv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glColor4us(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glColor4usv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glEdgeFlag(self, flag: int) -> None: ...
def glEdgeFlagv(self, flag: PYQT_OPENGL_ARRAY) -> None: ...
def glEnd(self) -> None: ...
def glIndexd(self, c: float) -> None: ...
def glIndexdv(self, c: PYQT_OPENGL_ARRAY) -> None: ...
def glIndexf(self, c: float) -> None: ...
def glIndexfv(self, c: PYQT_OPENGL_ARRAY) -> None: ...
def glIndexi(self, c: int) -> None: ...
def glIndexiv(self, c: PYQT_OPENGL_ARRAY) -> None: ...
def glIndexs(self, c: int) -> None: ...
def glIndexsv(self, c: PYQT_OPENGL_ARRAY) -> None: ...
def glNormal3b(self, nx: int, ny: int, nz: int) -> None: ...
def glNormal3bv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glNormal3d(self, nx: float, ny: float, nz: float) -> None: ...
def glNormal3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glNormal3f(self, nx: float, ny: float, nz: float) -> None: ...
def glNormal3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glNormal3i(self, nx: int, ny: int, nz: int) -> None: ...
def glNormal3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glNormal3s(self, nx: int, ny: int, nz: int) -> None: ...
def glNormal3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos2d(self, x: float, y: float) -> None: ...
def glRasterPos2dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos2f(self, x: float, y: float) -> None: ...
def glRasterPos2fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos2i(self, x: int, y: int) -> None: ...
def glRasterPos2iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos2s(self, x: int, y: int) -> None: ...
def glRasterPos2sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos3d(self, x: float, y: float, z: float) -> None: ...
def glRasterPos3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos3f(self, x: float, y: float, z: float) -> None: ...
def glRasterPos3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos3i(self, x: int, y: int, z: int) -> None: ...
def glRasterPos3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos3s(self, x: int, y: int, z: int) -> None: ...
def glRasterPos3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos4d(self, x: float, y: float, z: float, w: float) -> None: ...
def glRasterPos4dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos4f(self, x: float, y: float, z: float, w: float) -> None: ...
def glRasterPos4fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos4i(self, x: int, y: int, z: int, w: int) -> None: ...
def glRasterPos4iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRasterPos4s(self, x: int, y: int, z: int, w: int) -> None: ...
def glRasterPos4sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glRectd(self, x1: float, y1: float, x2: float, y2: float) -> None: ...
def glRectf(self, x1: float, y1: float, x2: float, y2: float) -> None: ...
def glRecti(self, x1: int, y1: int, x2: int, y2: int) -> None: ...
def glRects(self, x1: int, y1: int, x2: int, y2: int) -> None: ...
def glTexCoord1d(self, s: float) -> None: ...
def glTexCoord1dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord1f(self, s: float) -> None: ...
def glTexCoord1fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord1i(self, s: int) -> None: ...
def glTexCoord1iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord1s(self, s: int) -> None: ...
def glTexCoord1sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord2d(self, s: float, t: float) -> None: ...
def glTexCoord2dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord2f(self, s: float, t: float) -> None: ...
def glTexCoord2fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord2i(self, s: int, t: int) -> None: ...
def glTexCoord2iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord2s(self, s: int, t: int) -> None: ...
def glTexCoord2sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord3d(self, s: float, t: float, r: float) -> None: ...
def glTexCoord3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord3f(self, s: float, t: float, r: float) -> None: ...
def glTexCoord3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord3i(self, s: int, t: int, r: int) -> None: ...
def glTexCoord3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord3s(self, s: int, t: int, r: int) -> None: ...
def glTexCoord3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord4d(self, s: float, t: float, r: float, q: float) -> None: ...
def glTexCoord4dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord4f(self, s: float, t: float, r: float, q: float) -> None: ...
def glTexCoord4fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord4i(self, s: int, t: int, r: int, q: int) -> None: ...
def glTexCoord4iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glTexCoord4s(self, s: int, t: int, r: int, q: int) -> None: ...
def glTexCoord4sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex2d(self, x: float, y: float) -> None: ...
def glVertex2dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex2f(self, x: float, y: float) -> None: ...
def glVertex2fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex2i(self, x: int, y: int) -> None: ...
def glVertex2iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex2s(self, x: int, y: int) -> None: ...
def glVertex2sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex3d(self, x: float, y: float, z: float) -> None: ...
def glVertex3dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex3f(self, x: float, y: float, z: float) -> None: ...
def glVertex3fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex3i(self, x: int, y: int, z: int) -> None: ...
def glVertex3iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex3s(self, x: int, y: int, z: int) -> None: ...
def glVertex3sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex4d(self, x: float, y: float, z: float, w: float) -> None: ...
def glVertex4dv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex4f(self, x: float, y: float, z: float, w: float) -> None: ...
def glVertex4fv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex4i(self, x: int, y: int, z: int, w: int) -> None: ...
def glVertex4iv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glVertex4s(self, x: int, y: int, z: int, w: int) -> None: ...
def glVertex4sv(self, v: PYQT_OPENGL_ARRAY) -> None: ...
def glClipPlane(self, plane: int, equation: PYQT_OPENGL_ARRAY) -> None: ...
def glColorMaterial(self, face: int, mode: int) -> None: ...
def glFogf(self, pname: int, param: float) -> None: ...
def glFogfv(self, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glFogi(self, pname: int, param: int) -> None: ...
def glFogiv(self, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glLightf(self, light: int, pname: int, param: float) -> None: ...
def glLightfv(self, light: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glLighti(self, light: int, pname: int, param: int) -> None: ...
def glLightiv(self, light: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glLightModelf(self, pname: int, param: float) -> None: ...
def glLightModelfv(self, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glLightModeli(self, pname: int, param: int) -> None: ...
def glLightModeliv(self, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glLineStipple(self, factor: int, pattern: int) -> None: ...
def glMaterialf(self, face: int, pname: int, param: float) -> None: ...
def glMaterialfv(self, face: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glMateriali(self, face: int, pname: int, param: int) -> None: ...
def glMaterialiv(self, face: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glPolygonStipple(self, mask: PYQT_OPENGL_ARRAY) -> None: ...
def glShadeModel(self, mode: int) -> None: ...
def glTexEnvf(self, target: int, pname: int, param: float) -> None: ...
def glTexEnvfv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glTexEnvi(self, target: int, pname: int, param: int) -> None: ...
def glTexEnviv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glTexGend(self, coord: int, pname: int, param: float) -> None: ...
def glTexGendv(self, coord: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glTexGenf(self, coord: int, pname: int, param: float) -> None: ...
def glTexGenfv(self, coord: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glTexGeni(self, coord: int, pname: int, param: int) -> None: ...
def glTexGeniv(self, coord: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glRenderMode(self, mode: int) -> int: ...
def glInitNames(self) -> None: ...
def glLoadName(self, name: int) -> None: ...
def glPassThrough(self, token: float) -> None: ...
def glPopName(self) -> None: ...
def glPushName(self, name: int) -> None: ...
def glClearAccum(self, red: float, green: float, blue: float, alpha: float) -> None: ...
def glClearIndex(self, c: float) -> None: ...
def glIndexMask(self, mask: int) -> None: ...
def glAccum(self, op: int, value: float) -> None: ...
def glPopAttrib(self) -> None: ...
def glPushAttrib(self, mask: int) -> None: ...
def glMap1d(self, target: int, u1: float, u2: float, stride: int, order: int, points: PYQT_OPENGL_ARRAY) -> None: ...
def glMap1f(self, target: int, u1: float, u2: float, stride: int, order: int, points: PYQT_OPENGL_ARRAY) -> None: ...
def glMap2d(self, target: int, u1: float, u2: float, ustride: int, uorder: int, v1: float, v2: float, vstride: int, vorder: int, points: PYQT_OPENGL_ARRAY) -> None: ...
def glMap2f(self, target: int, u1: float, u2: float, ustride: int, uorder: int, v1: float, v2: float, vstride: int, vorder: int, points: PYQT_OPENGL_ARRAY) -> None: ...
def glMapGrid1d(self, un: int, u1: float, u2: float) -> None: ...
def glMapGrid1f(self, un: int, u1: float, u2: float) -> None: ...
def glMapGrid2d(self, un: int, u1: float, u2: float, vn: int, v1: float, v2: float) -> None: ...
def glMapGrid2f(self, un: int, u1: float, u2: float, vn: int, v1: float, v2: float) -> None: ...
def glEvalCoord1d(self, u: float) -> None: ...
def glEvalCoord1dv(self, u: PYQT_OPENGL_ARRAY) -> None: ...
def glEvalCoord1f(self, u: float) -> None: ...
def glEvalCoord1fv(self, u: PYQT_OPENGL_ARRAY) -> None: ...
def glEvalCoord2d(self, u: float, v: float) -> None: ...
def glEvalCoord2dv(self, u: PYQT_OPENGL_ARRAY) -> None: ...
def glEvalCoord2f(self, u: float, v: float) -> None: ...
def glEvalCoord2fv(self, u: PYQT_OPENGL_ARRAY) -> None: ...
def glEvalMesh1(self, mode: int, i1: int, i2: int) -> None: ...
def glEvalPoint1(self, i: int) -> None: ...
def glEvalMesh2(self, mode: int, i1: int, i2: int, j1: int, j2: int) -> None: ...
def glEvalPoint2(self, i: int, j: int) -> None: ...
def glAlphaFunc(self, func: int, ref: float) -> None: ...
def glPixelZoom(self, xfactor: float, yfactor: float) -> None: ...
def glPixelTransferf(self, pname: int, param: float) -> None: ...
def glPixelTransferi(self, pname: int, param: int) -> None: ...
def glPixelMapfv(self, map: int, mapsize: int, values: PYQT_OPENGL_ARRAY) -> None: ...
def glPixelMapuiv(self, map: int, mapsize: int, values: PYQT_OPENGL_ARRAY) -> None: ...
def glPixelMapusv(self, map: int, mapsize: int, values: PYQT_OPENGL_ARRAY) -> None: ...
def glCopyPixels(self, x: int, y: int, width: int, height: int, type: int) -> None: ...
def glDrawPixels(self, width: int, height: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glGetClipPlane(self, plane: int) -> typing.Tuple[float, float, float, float]: ...
def glGetLightfv(self, light: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float], typing.Tuple[float, float, float, float]]: ...
def glGetLightiv(self, light: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int], typing.Tuple[int, int, int, int]]: ...
def glGetMaterialfv(self, face: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float], typing.Tuple[float, float, float, float]]: ...
def glGetMaterialiv(self, face: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int], typing.Tuple[int, int, int, int]]: ...
def glGetTexEnvfv(self, target: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetTexEnviv(self, target: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int, int]]: ...
def glGetTexGendv(self, coord: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetTexGenfv(self, coord: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetTexGeniv(self, coord: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int, int]]: ...
def glIsList(self, list: int) -> int: ...
def glFrustum(self, left: float, right: float, bottom: float, top: float, zNear: float, zFar: float) -> None: ...
def glLoadIdentity(self) -> None: ...
def glLoadMatrixf(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glLoadMatrixd(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glMatrixMode(self, mode: int) -> None: ...
def glMultMatrixf(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glMultMatrixd(self, m: PYQT_OPENGL_ARRAY) -> None: ...
def glOrtho(self, left: float, right: float, bottom: float, top: float, zNear: float, zFar: float) -> None: ...
def glPopMatrix(self) -> None: ...
def glPushMatrix(self) -> None: ...
def glRotated(self, angle: float, x: float, y: float, z: float) -> None: ...
def glRotatef(self, angle: float, x: float, y: float, z: float) -> None: ...
def glScaled(self, x: float, y: float, z: float) -> None: ...
def glScalef(self, x: float, y: float, z: float) -> None: ...
def glTranslated(self, x: float, y: float, z: float) -> None: ...
def glTranslatef(self, x: float, y: float, z: float) -> None: ...
def glBlendEquationSeparate(self, modeRGB: int, modeAlpha: int) -> None: ...
def glDrawBuffers(self, n: int, bufs: PYQT_OPENGL_ARRAY) -> None: ...
def glStencilOpSeparate(self, face: int, sfail: int, dpfail: int, dppass: int) -> None: ...
def glStencilFuncSeparate(self, face: int, func: int, ref: int, mask: int) -> None: ...
def glStencilMaskSeparate(self, face: int, mask: int) -> None: ...
def glAttachShader(self, program: int, shader: int) -> None: ...
def glBindAttribLocation(self, program: int, index: int, name: str) -> None: ...
def glCompileShader(self, shader: int) -> None: ...
def glCreateProgram(self) -> int: ...
def glCreateShader(self, type: int) -> int: ...
def glDeleteProgram(self, program: int) -> None: ...
def glDeleteShader(self, shader: int) -> None: ...
def glDetachShader(self, program: int, shader: int) -> None: ...
def glDisableVertexAttribArray(self, index: int) -> None: ...
def glEnableVertexAttribArray(self, index: int) -> None: ...
def glGetActiveAttrib(self, program: int, index: int) -> typing.Tuple[str, int, int]: ...
def glGetActiveUniform(self, program: int, index: int) -> typing.Tuple[str, int, int]: ...
def glGetAttachedShaders(self, program: int) -> typing.Tuple[int, ...]: ...
def glGetAttribLocation(self, program: int, name: str) -> int: ...
def glGetProgramiv(self, program: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int]]: ...
def glGetProgramInfoLog(self, program: int) -> bytes: ...
def glGetShaderiv(self, shader: int, pname: int) -> int: ...
def glGetShaderInfoLog(self, shader: int) -> bytes: ...
def glGetShaderSource(self, shader: int) -> bytes: ...
def glGetUniformLocation(self, program: int, name: str) -> int: ...
def glGetVertexAttribdv(self, index: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetVertexAttribfv(self, index: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetVertexAttribiv(self, index: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int, int]]: ...
def glIsProgram(self, program: int) -> int: ...
def glIsShader(self, shader: int) -> int: ...
def glLinkProgram(self, program: int) -> None: ...
def glUseProgram(self, program: int) -> None: ...
def glUniform1f(self, location: int, v0: float) -> None: ...
def glUniform2f(self, location: int, v0: float, v1: float) -> None: ...
def glUniform3f(self, location: int, v0: float, v1: float, v2: float) -> None: ...
def glUniform4f(self, location: int, v0: float, v1: float, v2: float, v3: float) -> None: ...
def glUniform1i(self, location: int, v0: int) -> None: ...
def glUniform2i(self, location: int, v0: int, v1: int) -> None: ...
def glUniform3i(self, location: int, v0: int, v1: int, v2: int) -> None: ...
def glUniform4i(self, location: int, v0: int, v1: int, v2: int, v3: int) -> None: ...
def glUniform1fv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform2fv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform3fv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform4fv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform1iv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform2iv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform3iv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniform4iv(self, location: int, count: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniformMatrix2fv(self, location: int, count: int, transpose: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniformMatrix3fv(self, location: int, count: int, transpose: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glUniformMatrix4fv(self, location: int, count: int, transpose: int, value: PYQT_OPENGL_ARRAY) -> None: ...
def glValidateProgram(self, program: int) -> None: ...
def glVertexAttribPointer(self, index: int, size: int, type: int, normalized: int, stride: int, pointer: PYQT_OPENGL_BOUND_ARRAY) -> None: ...
def glGenQueries(self, n: int) -> typing.Union[int, typing.Tuple[int, ...]]: ...
def glDeleteQueries(self, n: int, ids: PYQT_OPENGL_ARRAY) -> None: ...
def glIsQuery(self, id: int) -> int: ...
def glBeginQuery(self, target: int, id: int) -> None: ...
def glEndQuery(self, target: int) -> None: ...
def glGetQueryiv(self, target: int, pname: int) -> int: ...
def glBindBuffer(self, target: int, buffer: int) -> None: ...
def glDeleteBuffers(self, n: int, buffers: PYQT_OPENGL_ARRAY) -> None: ...
def glGenBuffers(self, n: int) -> typing.Union[int, typing.Tuple[int, ...]]: ...
def glIsBuffer(self, buffer: int) -> int: ...
def glBufferData(self, target: int, size: int, data: PYQT_OPENGL_ARRAY, usage: int) -> None: ...
def glBufferSubData(self, target: int, offset: int, size: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glUnmapBuffer(self, target: int) -> int: ...
def glGetBufferParameteriv(self, target: int, pname: int) -> int: ...
def glBlendFuncSeparate(self, sfactorRGB: int, dfactorRGB: int, sfactorAlpha: int, dfactorAlpha: int) -> None: ...
def glPointParameterf(self, pname: int, param: float) -> None: ...
def glPointParameterfv(self, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glPointParameteri(self, pname: int, param: int) -> None: ...
def glPointParameteriv(self, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glActiveTexture(self, texture: int) -> None: ...
def glSampleCoverage(self, value: float, invert: int) -> None: ...
def glCompressedTexImage3D(self, target: int, level: int, internalformat: int, width: int, height: int, depth: int, border: int, imageSize: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glCompressedTexImage2D(self, target: int, level: int, internalformat: int, width: int, height: int, border: int, imageSize: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glCompressedTexImage1D(self, target: int, level: int, internalformat: int, width: int, border: int, imageSize: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glCompressedTexSubImage3D(self, target: int, level: int, xoffset: int, yoffset: int, zoffset: int, width: int, height: int, depth: int, format: int, imageSize: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glCompressedTexSubImage2D(self, target: int, level: int, xoffset: int, yoffset: int, width: int, height: int, format: int, imageSize: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glCompressedTexSubImage1D(self, target: int, level: int, xoffset: int, width: int, format: int, imageSize: int, data: PYQT_OPENGL_ARRAY) -> None: ...
def glBlendColor(self, red: float, green: float, blue: float, alpha: float) -> None: ...
def glBlendEquation(self, mode: int) -> None: ...
def glDrawRangeElements(self, mode: int, start: int, end: int, count: int, type: int, indices: PYQT_OPENGL_ARRAY) -> None: ...
def glTexImage3D(self, target: int, level: int, internalformat: int, width: int, height: int, depth: int, border: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glTexSubImage3D(self, target: int, level: int, xoffset: int, yoffset: int, zoffset: int, width: int, height: int, depth: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glCopyTexSubImage3D(self, target: int, level: int, xoffset: int, yoffset: int, zoffset: int, x: int, y: int, width: int, height: int) -> None: ...
def glDrawArrays(self, mode: int, first: int, count: int) -> None: ...
def glDrawElements(self, mode: int, count: int, type: int, indices: PYQT_OPENGL_ARRAY) -> None: ...
def glPolygonOffset(self, factor: float, units: float) -> None: ...
def glCopyTexImage1D(self, target: int, level: int, internalformat: int, x: int, y: int, width: int, border: int) -> None: ...
def glCopyTexImage2D(self, target: int, level: int, internalformat: int, x: int, y: int, width: int, height: int, border: int) -> None: ...
def glCopyTexSubImage1D(self, target: int, level: int, xoffset: int, x: int, y: int, width: int) -> None: ...
def glCopyTexSubImage2D(self, target: int, level: int, xoffset: int, yoffset: int, x: int, y: int, width: int, height: int) -> None: ...
def glTexSubImage1D(self, target: int, level: int, xoffset: int, width: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glTexSubImage2D(self, target: int, level: int, xoffset: int, yoffset: int, width: int, height: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glBindTexture(self, target: int, texture: int) -> None: ...
def glDeleteTextures(self, n: int, textures: PYQT_OPENGL_ARRAY) -> None: ...
def glGenTextures(self, n: int) -> typing.Union[int, typing.Tuple[int, ...]]: ...
def glIsTexture(self, texture: int) -> int: ...
def glIndexub(self, c: int) -> None: ...
def glIndexubv(self, c: PYQT_OPENGL_ARRAY) -> None: ...
def glCullFace(self, mode: int) -> None: ...
def glFrontFace(self, mode: int) -> None: ...
def glHint(self, target: int, mode: int) -> None: ...
def glLineWidth(self, width: float) -> None: ...
def glPointSize(self, size: float) -> None: ...
def glPolygonMode(self, face: int, mode: int) -> None: ...
def glScissor(self, x: int, y: int, width: int, height: int) -> None: ...
def glTexParameterf(self, target: int, pname: int, param: float) -> None: ...
def glTexParameterfv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glTexParameteri(self, target: int, pname: int, param: int) -> None: ...
def glTexParameteriv(self, target: int, pname: int, params: PYQT_OPENGL_ARRAY) -> None: ...
def glTexImage1D(self, target: int, level: int, internalformat: int, width: int, border: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glTexImage2D(self, target: int, level: int, internalformat: int, width: int, height: int, border: int, format: int, type: int, pixels: PYQT_OPENGL_ARRAY) -> None: ...
def glDrawBuffer(self, mode: int) -> None: ...
def glClear(self, mask: int) -> None: ...
def glClearColor(self, red: float, green: float, blue: float, alpha: float) -> None: ...
def glClearStencil(self, s: int) -> None: ...
def glClearDepth(self, depth: float) -> None: ...
def glStencilMask(self, mask: int) -> None: ...
def glColorMask(self, red: int, green: int, blue: int, alpha: int) -> None: ...
def glDepthMask(self, flag: int) -> None: ...
def glDisable(self, cap: int) -> None: ...
def glEnable(self, cap: int) -> None: ...
def glFinish(self) -> None: ...
def glFlush(self) -> None: ...
def glBlendFunc(self, sfactor: int, dfactor: int) -> None: ...
def glLogicOp(self, opcode: int) -> None: ...
def glStencilFunc(self, func: int, ref: int, mask: int) -> None: ...
def glStencilOp(self, fail: int, zfail: int, zpass: int) -> None: ...
def glDepthFunc(self, func: int) -> None: ...
def glPixelStoref(self, pname: int, param: float) -> None: ...
def glPixelStorei(self, pname: int, param: int) -> None: ...
def glReadBuffer(self, mode: int) -> None: ...
def glGetBooleanv(self, pname: int) -> typing.Union[bool, typing.Tuple[bool, ...]]: ...
def glGetDoublev(self, pname: int) -> typing.Union[float, typing.Tuple[float, ...]]: ...
def glGetError(self) -> int: ...
def glGetFloatv(self, pname: int) -> typing.Union[float, typing.Tuple[float, ...]]: ...
def glGetIntegerv(self, pname: int) -> typing.Union[int, typing.Tuple[int, ...]]: ...
def glGetString(self, name: int) -> str: ...
def glGetTexParameterfv(self, target: int, pname: int) -> typing.Union[float, typing.Tuple[float, float, float, float]]: ...
def glGetTexParameteriv(self, target: int, pname: int) -> typing.Union[int, typing.Tuple[int, int, int, int]]: ...
def glGetTexLevelParameterfv(self, target: int, level: int, pname: int) -> float: ...
def glGetTexLevelParameteriv(self, target: int, level: int, pname: int) -> int: ...
def glIsEnabled(self, cap: int) -> int: ...
def glDepthRange(self, nearVal: float, farVal: float) -> None: ...
def glViewport(self, x: int, y: int, width: int, height: int) -> None: ...
def initializeOpenGLFunctions(self) -> bool: ...
| [
"wangzhibin_x@foxmail.com"
] | wangzhibin_x@foxmail.com |
5d54d9806081b5a4bfe7026d4711ef3642d29885 | 0bfb74494054dc9e0774618687b5d234e6db6a92 | /ch11/progress_queue.py | 400bf69717d73d7b1dbf7bc59cba559aad28aa52 | [] | no_license | FSSlc/AdvancePython | dddee32524cf1071a36eb4316efc2b53185645e3 | 61ed98f951fc877cc01e43a50488fc91b775c0f0 | refs/heads/master | 2022-11-06T10:53:07.812770 | 2020-06-25T23:43:24 | 2020-06-25T23:43:24 | 273,885,468 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,069 | py | #!/usr/bin/env python
# coding: utf-8
"""
通过 Queue 来进行进程间通信
共享全局变量不能适用于多进程编程，可以适用于多线程编程
multiprocessing 中的 Queue 不能用于 pool 线程池
pool 中的进程间通信需要使用 manager 中的 Queue
还可以使用管道 pipe 来进行进程间通信
"""
import multiprocessing
import time
from multiprocessing import Process, Queue, Manager, Pipe
def producer(queue):
queue.put('a')
time.sleep(2)
def consumer(queue):
time.sleep(2)
data = queue.get()
print(data)
def producer_pipe(pipe):
pipe.send('user')
def consumer_pipe(pipe):
print(pipe.recv())
def add_data(p_dict, key, value):
p_dict[key] = value
if __name__ == '__main__':
queue = Queue(10)
my_producer = Process(target=producer, args=(queue,))
my_consumer = Process(target=consumer, args=(queue,))
my_producer.start()
my_consumer.start()
my_producer.join()
my_consumer.join()
# 使用线程池
# 使用 Manager 实例化的 Queue 来通信
queue = Manager().Queue(10)
with multiprocessing.Pool(multiprocessing.cpu_count()) as pool:
pool.apply_async(producer, args=(queue,))
pool.apply_async(consumer, args=(queue,))
pool.join()
# 使用 Pipe 来通信
# Pipe 只能适合于 2 个进程
# Pipe 的性能比较高
receive_pipe, send_pipe = Pipe()
my_producer = Process(target=producer_pipe, args=(send_pipe,))
my_consumer = Process(target=consumer_pipe, args=(receive_pipe,))
my_producer.start()
my_consumer.start()
my_producer.join()
my_consumer.join()
# Manager 中包含了常见的通信方式和数据结构例如 dict Array Condition 等
process_dict = Manager().dict()
first_progress = Process(target=add_data, args=(process_dict, 'user1', 22))
second_progress = Process(target=add_data, args=(process_dict, 'user2', 23))
first_progress.start()
second_progress.start()
first_progress.join()
second_progress.join()
print(process_dict)
| [
"fsslc235@gmail.com"
] | fsslc235@gmail.com |
da6268d37a31875a6f3720c7b2592c435e43bc0f | 0b01f92e125c27ceaf7586645f72dd5234e6841f | /Pages/product_details_page.py | 14698824353ac81b2aa33a4eb20094f8e7cce642 | [
"MIT"
] | permissive | gykudo/sauce_demo | 40789ee7b55b36e37bd77752f5a55a00890409ca | 313b4bd956cad4807d225b0a7ed98ca0be9f3371 | refs/heads/main | 2023-01-11T16:08:37.710841 | 2020-11-14T13:26:09 | 2020-11-14T13:26:09 | 305,707,742 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,341 | py | from Objects.product import Product
from Pages.base_page_object import BasePage
from Locators.product_detail_page_locator import ProductDetailPageLocator
class ProductsDetailsPage(BasePage):
def __init__(self, driver):
super().__init__(driver)
def get_product_badge(self):
total = 0
try:
total = self.get_text(ProductDetailPageLocator.SHOPPING_CART_LABEL)
except Exception:
pass
return int(total)
def get_product_info(self):
name = self.get_text(ProductDetailPageLocator.PRODUCT_NAME_LABEL)
desc = self.get_text(ProductDetailPageLocator.PRODUCT_DESC_LABEL)
price = self.get_text(ProductDetailPageLocator.PRODUCT_PRICE_LABEL)
return Product(name, desc, price)
def add_product_to_cart(self):
self.click(ProductDetailPageLocator.PRODUCT_ADD_BUTTON)
def does_add_button_exist(self):
return self.is_visible(ProductDetailPageLocator.PRODUCT_ADD_BUTTON)
def remove_product_from_cart(self):
self.click(ProductDetailPageLocator.PRODUCT_REMOVE_BUTTON)
def does_remove_button_exist(self):
return self.is_visible(ProductDetailPageLocator.PRODUCT_REMOVE_BUTTON)
def is_product_badge_invisible(self):
return self.is_invisible(ProductDetailPageLocator.SHOPPING_CART_LABEL)
def back_to_product_page(self):
self.click(ProductDetailPageLocator.BACK_BUTTON)
| [
"tukimtuan@gmail.com"
] | tukimtuan@gmail.com |
3ebe01d084af1e6585aa032e0a4d15ab6c775bfd | 0a3eada15be160f13642afc357b74dd8c2095710 | /2017/python/14-disk-defragmentation/main.py | 3cf0e0206fedac1fc80c289314d3589ad87f2cfb | [] | no_license | cj1128/advent-of-code | af8edfa0e1479ed1221c07eb28eab193877a66d6 | 273eeaf97204ca1755006b7c4b61ac3609124f79 | refs/heads/master | 2022-11-28T18:58:32.087955 | 2020-08-09T13:57:40 | 2020-08-09T13:57:40 | 113,849,897 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,556 | py | import binascii
import numpy
import sys
sys.path.append("..")
from utils import know_hash
input = "hwlqcszp"
part1_test = ("flqrgnkx", 8108)
def solve_part1(input):
used = 0
for i in range(128):
hash = know_hash(f"{input}-{i}")
bits = format(int(hash, 16), "08b")
used += bits.count("1")
return used
# print(solve_part1(part1_test[0]) == part1_test[1])
# print(solve_part1(input))
# 8304
part2_test = ("flqrgnkx", 1242)
def get_adjacent(row, col, dimension):
result = []
# top
if row > 0:
result.append((row - 1, col))
# down
if row < dimension - 1:
result.append((row + 1, col))
# left
if col > 0:
result.append((row, col - 1))
# right
if col < dimension - 1:
result.append((row, col + 1))
return result
def mark_group(row, col, result, disk, group):
result[(row, col)] = group
for row, col in get_adjacent(row, col, 128):
if disk[row][col] == 1 and (row, col) not in result:
mark_group(row, col, result, disk, group)
def solve_part2(input):
disk = []
for i in range(128):
hash = know_hash(f"{input}-{i}")
bits = "".join([format(b, "08b") for b in binascii.unhexlify(hash)])
disk.append([int(b) for b in bits])
result = dict()
group = 1
for row in range(128):
for col in range(128):
if disk[row][col] == 0:
continue
if (row, col) in result:
continue
mark_group(row, col, result, disk, group)
group += 1
return max(result.values())
# print(solve_part2(part2_test[0]) == part2_test[1])
print(solve_part2(input))
| [
"fatelovely1128@gmail.com"
] | fatelovely1128@gmail.com |
106f45f4de87ee679c33655383f062436ab7d436 | e928be64f52609ac4be5cb0a4c2d8571d999bb2d | /JapaneseTools/Conversion/k.py | e938a9f155b61fb276531464e2f97f93460a400f | [] | no_license | youkaicountry/JapaneseTools | ac19bd6e9202f5e474b74649032cd87ad7017863 | 20fcec03c0e24bbb65a2846cdeae81f9f86ccb99 | refs/heads/master | 2021-05-26T18:45:35.305598 | 2011-12-10T04:32:38 | 2011-12-10T04:32:38 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,382 | py | # -*- coding: utf-8 -*-
def toIF(kana):
#step 1: basic processing
t = []
for x in kana:
t.append(__getRomaji(x))
t2 = []
#step 2: process special characters
t2pos = 0
for i in range(len(t)):
if i > 0 and t[i-1][0] == ">": continue
if t[i][0] == "<":
if i > 0:
t2.append(__getSpecial((t[i-1], t[i])))
t2.pop(t2pos-1)
elif t[i][0] == ">":
if i < len(t)-1:
t2.append(t[i+1][0] + t[i+1])
t2.append(__getSpecial((t[i], t[i+1])))
else:
t2.append(t[i])
t2pos += 1
return t2
def __getRomaji(kana):
try:
ret = ktor[kana]
except KeyError:
ret = ""
return ret
def __getSpecial(rom):
try:
ret = special[rom]
except KeyError:
ret = ""
return ret
ktor = {}
ktor["あ"] = "a"
ktor["ア"] = "A"
ktor["い"] = "i"
ktor["イ"] = "I"
ktor["う"] = "u"
ktor["ウ"] = "U"
ktor["え"] = "e"
ktor["エ"] = "E"
ktor["お"] = "o"
ktor["オ"] = "O"
ktor["か"] = "ka"
ktor["カ"] = "KA"
ktor["き"] = "ki"
ktor["キ"] = "KI"
ktor["く"] = "ku"
ktor["ク"] = "KU"
ktor["け"] = "ke"
ktor["ケ"] = "KE"
ktor["こ"] = "ko"
ktor["コ"] = "KO"
ktor["さ"] = "sa"
ktor["サ"] = "SA"
ktor["し"] = "shi"
ktor["シ"] = "SHI"
ktor["す"] = "su"
ktor["ス"] = "SU"
ktor["せ"] = "se"
ktor["セ"] = "SE"
ktor["そ"] = "so"
ktor["ソ"] = "SO"
ktor["た"] = "ta"
ktor["タ"] = "TA"
ktor["ち"] = "chi"
ktor["チ"] = "CHI"
ktor["つ"] = "tsu"
ktor["ツ"] = "TSU"
ktor["て"] = "te"
ktor["テ"] = "TE"
ktor["と"] = "to"
ktor["ト"] = "TO"
ktor["な"] = "na"
ktor["ナ"] = "NA"
ktor["に"] = "ni"
ktor["ニ"] = "NI"
ktor["ぬ"] = "nu"
ktor["ヌ"] = "NU"
ktor["ね"] = "ne"
ktor["ネ"] = "NE"
ktor["の"] = "no"
ktor["ノ"] = "NO"
ktor["は"] = "ha"
ktor["ハ"] = "HA"
ktor["ひ"] = "hi"
ktor["ヒ"] = "HI"
ktor["ふ"] = "fu"
ktor["フ"] = "FU"
ktor["へ"] = "he"
ktor["ヘ"] = "HE"
ktor["ほ"] = "ho"
ktor["ホ"] = "HO"
ktor["ま"] = "ma"
ktor["マ"] = "MA"
ktor["み"] = "mi"
ktor["ミ"] = "MI"
ktor["む"] = "mu"
ktor["ム"] = "MU"
ktor["め"] = "me"
ktor["メ"] = "ME"
ktor["も"] = "mo"
ktor["モ"] = "MO"
ktor["や"] = "ya"
ktor["ヤ"] = "YA"
ktor["ゆ"] = "yu"
ktor["ユ"] = "YU"
ktor["よ"] = "yo"
ktor["ヨ"] = "YO"
ktor["ら"] = "ra"
ktor["ラ"] = "RA"
ktor["り"] = "ri"
ktor["リ"] = "RI"
ktor["る"] = "ru"
ktor["ル"] = "RU"
ktor["れ"] = "re"
ktor["レ"] = "RE"
ktor["ろ"] = "ro"
ktor["ロ"] = "RO"
ktor["わ"] = "wa"
ktor["ワ"] = "WA"
ktor["を"] = "wo"
ktor["ヲ"] = "WO"
ktor["が"] = "ga"
ktor["ガ"] = "GA"
ktor["ぎ"] = "gi"
ktor["ギ"] = "GI"
ktor["ぐ"] = "gu"
ktor["グ"] = "GU"
ktor["げ"] = "ge"
ktor["ゲ"] = "GE"
ktor["ご"] = "go"
ktor["ゴ"] = "GO"
ktor["ざ"] = "za"
ktor["ザ"] = "ZA"
ktor["じ"] = "ji"
ktor["ジ"] = "JI"
ktor["ず"] = "zu"
ktor["ズ"] = "ZU"
ktor["ぜ"] = "ze"
ktor["ゼ"] = "ZE"
ktor["ぞ"] = "zo"
ktor["ゾ"] = "ZO"
ktor["だ"] = "da"
ktor["ダ"] = "DA"
ktor["ぢ"] = "di"
ktor["ヂ"] = "DI"
ktor["づ"] = "du"
ktor["ヅ"] = "DU"
ktor["で"] = "de"
ktor["デ"] = "DE"
ktor["ど"] = "do"
ktor["ド"] = "DO"
ktor["ば"] = "ba"
ktor["バ"] = "BA"
ktor["び"] = "bi"
ktor["ビ"] = "BI"
ktor["ぶ"] = "bu"
ktor["ブ"] = "BU"
ktor["べ"] = "be"
ktor["ベ"] = "BE"
ktor["ぼ"] = "bo"
ktor["ボ"] = "BO"
ktor["ぱ"] = "pa"
ktor["パ"] = "PA"
ktor["ぴ"] = "pi"
ktor["ピ"] = "PI"
ktor["ぷ"] = "pu"
ktor["プ"] = "PU"
ktor["ぺ"] = "pe"
ktor["ペ"] = "PE"
ktor["ぽ"] = "po"
ktor["ポ"] = "PO"
ktor["ー"] = "-"
ktor["。"] = "."
ktor["？"] = "?"
ktor["！"] = "!"
ktor["、"] = ","
ktor[" "] = "_"
ktor["（"] = "["
ktor["）"] = "]"
ktor["〜"] = "~"
ktor["ゃ"] = "<ya"
ktor["ャ"] = "<YA"
ktor["ゅ"] = "<yu"
ktor["ュ"] = "<YU"
ktor["ょ"] = "<yo"
ktor["ョ"] = "<YO"
ktor["ん"] = "n"
ktor["ン"] = "N"
ktor["っ"] = ">tsu"
ktor["ッ"] = ">TSU"
ktor["「"] = "'"
ktor["」"] = "'"
ktor["ゐ"] = "wi"
ktor["ヰ"] = "WI"
special = {}
special[("ni","<ya")] = "nya"
special[("NI","<YA")] = "NYA"
special[("ni","<yu")] = "nyu"
special[("NI","<YU")] = "NYU"
special[("ni","<yo")] = "nyo"
special[("NI","<YO")] = "NYO"
special[("ki","<ya")] = "kya"
special[("KI","<YA")] = "KYA"
special[("ki","<yu")] = "kyu"
special[("KI","<YU")] = "KYU"
special[("ki","<yo")] = "kyo"
special[("KI","<YO")] = "KYO"
special[("shi","<ya")] = "sha"
special[("SHI","<YA")] = "SHA"
special[("shi","<yu")] = "shu"
special[("SHI","<YU")] = "SHU"
special[("shi","<yo")] = "sho"
special[("SHI","<YO")] = "SHO"
special[("chi","<ya")] = "cha"
special[("CHI","<YA")] = "CHA"
special[("chi","<yu")] = "chu"
special[("CHI","<YU")] = "CHU"
special[("chi","<yo")] = "cho"
special[("CHI","<YO")] = "CHO"
special[("hi","<ya")] = "hya"
special[("HI","<YA")] = "HYA"
special[("hi","<yu")] = "hyu"
special[("HI","<YU")] = "HYU"
special[("hi","<yo")] = "hyo"
special[("HI","<YO")] = "HYO"
special[("mi","<ya")] = "mya"
special[("MI","<YA")] = "MYA"
special[("mi","<yu")] = "myu"
special[("MI","<YU")] = "MYU"
special[("mi","<yo")] = "myo"
special[("MI","<YO")] = "MYO"
special[("ri","<ya")] = "rya"
special[("RI","<YA")] = "RYA"
special[("ri","<yu")] = "ryu"
special[("RI","<YU")] = "RYU"
special[("ri","<yo")] = "ryo"
special[("RI","<YO")] = "RYO"
special[("gi","<ya")] = "gya"
special[("GI","<YA")] = "GYA"
special[("gi","<yu")] = "gyu"
special[("GI","<YU")] = "GYU"
special[("gi","<yo")] = "gyo"
special[("GI","<YO")] = "GYO"
special[("ji","<ya")] = "ja"
special[("JI","<YA")] = "JA"
special[("ji","<yu")] = "ju"
special[("JI","<YU")] = "JU"
special[("ji","<yo")] = "jo"
special[("JI","<YO")] = "JO"
special[("bi","<ya")] = "bya"
special[("BI","<YA")] = "BYA"
special[("bi","<yu")] = "byu"
special[("BI","<YU")] = "BYU"
special[("bi","<yo")] = "byo"
special[("BI","<YO")] = "BYO"
special[("pi","<ya")] = "pya"
special[("PI","<YA")] = "PYA"
special[("pi","<yu")] = "pyu"
special[("PI","<YU")] = "PYU"
special[("pi","<yo")] = "pyo"
special[("PI","<YO")] = "PYO"
special[("di","<ya")] = "dya"
special[("DI","<YA")] = "DYA"
special[("di","<yu")] = "dyu"
special[("DI","<YU")] = "DYU"
special[("di","<yo")] = "dyo"
special[("DI","<YO")] = "DYO"
| [
"nbcwell@gmail.com"
] | nbcwell@gmail.com |
82fe4e45ff38d5287f5bdbc7456289d0b5be9b04 | 4befe5b55c189da9e3f73e9c372ad2effec8ffcb | /tests/features/steps/models_repo/test_models_delete.py | 29db060d9337e515002fd6978d3f44a36542eec5 | [
"Apache-2.0"
] | permissive | mohamedgaliaa/dtlpy | da68abc0c03a23efb103c4a8dc50e8cfd6909800 | 502a51881bd41497c8b5d9096e8478fd13f3f174 | refs/heads/master | 2023-04-03T17:10:37.249161 | 2021-04-07T12:44:54 | 2021-04-07T12:44:54 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 706 | py | import behave
@behave.when(u'I delete the model that was created by name')
def step_impl(context):
context.project.models.delete(model_name=context.model.name)
@behave.when(u'I delete the model that was created by id')
def step_impl(context):
context.project.models.delete(model_id=context.model.id)
@behave.when(u'I try to delete a model by the name of "{model_name}"')
def step_impl(context, model_name):
try:
context.project.models.delete(model_name=model_name)
context.error = None
except Exception as e:
context.error = e
@behave.then(u'No model was deleted')
def step_impl(context):
assert len(context.project.models.list()) == context.model_count
| [
"micha@dataloop.ai"
] | micha@dataloop.ai |
cb2e1a3938df6ebe22a28a25c29f67bdea6afc60 | b44234267386b8d162bafec0a3cd2d718eb3afde | /code/simplemooc/simplemooc/courses/forms.py | e69256612c19f5811fb128f19e0799137ac59d3a | [] | no_license | PuckmanXY/Simple_MOOC | afb6efaa6d23c362d438fda004c79e94bfa11e5e | afe01970ecb131b2e517b9520b158a70728507ce | refs/heads/master | 2021-04-29T12:03:18.547459 | 2018-04-21T00:29:20 | 2018-04-21T00:29:20 | 121,720,417 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 808 | py | from django import forms
from django.core.mail import send_mail
from django.conf import settings
from simplemooc.core.mail import send_mail_template
class ContactCourse(forms.Form):
name = forms.CharField(label = 'Nome', max_length = 100)
email = forms.EmailField(label = 'E-mail')
message = forms.CharField(
label = 'Mensagem/Dúvida', widget = forms.Textarea
)
def send_mail(self, course):
subject = '[%s] Contato' % course
context = {
'name': self.cleaned_data['name'],
'email': self.cleaned_data['email'],
'message': self.cleaned_data['message'],
}
template_name = 'courses/contact_email.html'
send_mail_template(
subject, template_name, context, [settings.CONTACT_EMAIL]
) | [
"kayoanderson0403@gmail.com"
] | kayoanderson0403@gmail.com |
40c87866e4260e92c9b0ecbd0776992362a3c7fa | ed36b3f1a953545e0f4d90d3d716e07d5d1900cd | /src/ARIMA-Future.py | 81776f2324397777b963c2c5877c5bb6927c863b | [] | no_license | Sprea22/CS_Bachelor_Thesis___Python_Data_Analysis | ab0c2a840277511577e5c2d7c723a8dbe9840683 | f0a06db61809f08d491a342b976acd7202fa3a83 | refs/heads/master | 2021-06-16T18:23:36.984031 | 2017-06-01T09:44:06 | 2017-06-01T09:44:06 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,192 | py | import os
import csv
import sys
import warnings
import numpy as np
import pandas as pd
from pandas import Series
from matplotlib import pyplot
from statsmodels.tsa.arima_model import ARIMA
pyplot.style.use('ggplot')
#-------------------------------------------------------------------------------------------
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# CALCULATED MAPE BETWEEN PREDICTIONS AND REAL VALUES#
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
def mean_absolute_percentage_error(y_true, y_pred):
try:
rng = len(y_true)
diff = []
for i in range(0,rng):
diff.append(y_true[i] - y_pred[i])
diff[i] = diff[i] / y_true[i]
abs = np.abs(diff)
mn = np.mean(abs)
percentageError = mn * 100
except:
rng = 0
abs = np.abs((y_true-y_pred)/y_true)
percentageError = abs * 100
return percentageError
#-------------------------------------------------------------------------------------------
# Load current dataset input
series = pd.read_csv("Datasets/"+sys.argv[1]+".csv", usecols=[sys.argv[2]])
yearInput = pd.read_csv("Datasets/" + sys.argv[1]+".csv", usecols=[0])
# Reading the real future values
realValues = pd.read_csv("Results_Forecast/"+sys.argv[1]+"/"+sys.argv[1]+"_"+sys.argv[2]+"_2015.csv", usecols=[0,1,"feedConsumption"])
# Initial datasets configurations.
realValuesData = realValues[sys.argv[2]].values
realValuesData = realValuesData.astype('float32')
dataset = series.values
dataset = dataset.astype('float32')
# Evaluate model with order (p_values, d_values, q_values)
p_values = int(sys.argv[4])
d_values = int(sys.argv[5])
q_values = int(sys.argv[6])
order = (p_values, d_values, q_values)
warnings.filterwarnings("ignore")
##################################
# PREDICTION ABOUT FUTURE VALUES #
##################################
# Making the ARIMA Model with the current Dataset and Order previously chosen
model = ARIMA(dataset, order=order)
model_fit = model.fit(disp=0)
# Filling the list "forecast" with the predictions results values
forecast = model_fit.forecast(int(sys.argv[3]))[0]
# Preparing the data that are going to be written in the output document that contains the results.
index = []
for i in range(1,int(sys.argv[3])+1):
index.append(len(dataset) +i)
mape_list = []
for i in range(0,len(forecast)):
mape_list.append(mean_absolute_percentage_error(realValuesData[i], forecast[i]))
# Writing the predictions results values inside an output document
rows = zip(index, realValuesData, forecast, mape_list)
f = open("Results_Forecast/"+sys.argv[1]+"/"+sys.argv[1]+"_"+sys.argv[2]+"_futurePred.csv", 'w')
csv.writer(f).writerows(rows)
f.close()
# Reading the real future values from the reported document
realValues= pd.read_csv("Results_Forecast/"+sys.argv[1]+"/"+sys.argv[1]+"_"+sys.argv[2]+"_futurePred.csv", index_col=[0], usecols=[0,1])
# Reading the predicted future values from the reported document
predFuture = pd.read_csv("Results_Forecast/"+sys.argv[1]+"/"+sys.argv[1]+"_"+sys.argv[2]+"_futurePred.csv", index_col=[0], usecols=[0,2])
# Initializing output graphic
pyplot.figure()
ax = pyplot.subplot(111)
pyplot.tight_layout()
# Displaying the real future values plot, green color.
ax.plot(realValues, "g", label='Real 2015 Values', linewidth=2)
# Displaying the predicted future values plot, red color.
ax.plot(predFuture, "r", label='Predicted 2015 Values', linewidth=2)
# Displaying the historic values plot, blue color.
ax.plot(series, "b", label='Historic Values', linewidth=2)
# Graphic legend settings
ax.legend(loc='lower right', ncol=1, fancybox=True, shadow=True, fontsize=20)
# Displaying current years on the xlabel.
years = []
j = 0
for i in range(len(yearInput)):
if j==11:
years.append(yearInput.values[i][0])
j=0
else:
j=j+1
x = range(0, len(yearInput.values))
pyplot.title(sys.argv[1] + " - " + sys.argv[2] + " | ARIMA order: " + str(order), fontsize=20)
pyplot.xticks(np.arange(min(x), max(x)+1, 12.0), years)
pyplot.xlabel("Years")
pyplot.ylabel(sys.argv[2]+" in "+sys.argv[1], fontsize=20)
# Display final graphic in full screen mode
manager = pyplot.get_current_fig_manager()
manager.resize(*manager.window.maxsize())
pyplot.show()
| [
"asp005@post.uit.no"
] | asp005@post.uit.no |
541be20181d90c2f788955ed7c94c8e307b6d08e | a7da58ad91b007b3650003708eb91928f1e3684a | /bt5/erp5_banking_cash/WorkflowTemplateItem/portal_workflow/internal_money_payment_workflow/scripts/validateCounter.py | 1259c1c7a0143dad30f158e310e8328d81adaa3d | [] | no_license | jgpjuniorj/j | 042d1bd7710fa2830355d4312a6b76103e29639d | dc02bfa887ffab9841abebc3f5c16d874388cef5 | refs/heads/master | 2021-01-01T09:26:36.121339 | 2020-01-31T10:34:17 | 2020-02-07T04:39:18 | 239,214,398 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,447 | py | from Products.DCWorkflow.DCWorkflow import ValidationFailed
from Products.ERP5Type.Message import Message
transaction = state_change['object']
date = transaction.getStartDate()
source = transaction.getSource(None)
# check we are in an opened accounting day
transaction.Baobab_checkCounterDateOpen(site=source, date=transaction.getStartDate())
# check again that the counter is open
context.Baobab_checkCounterOpened(source)
if transaction.getPaymentType() in (None, ""):
msg = Message(domain="ui", message="No payment type defined.")
raise ValidationFailed, (msg,)
#test if the source or the destination is correct
transaction.Base_checkBaobabSourceAndDestination()
# Get price and total_price.
amount = transaction.getSourceTotalAssetPrice()
total_price = transaction.getTotalPrice(portal_type=('Cash Delivery Line','Cash Delivery Cell'), fast=0)
if amount != total_price:
msg = Message(domain="ui", message="Amount differ from total price.")
raise ValidationFailed, (msg,)
if source is None:
msg = Message(domain='ui', message='No counter defined.')
raise ValidationFailed, (msg,)
site = transaction.getSourceValue()
vault = transaction.getBaobabSource()
resource = transaction.CashDelivery_checkCounterInventory(source=vault, portal_type='Cash Delivery Line',same_source=1)
#context.log('resource',resource)
if resource == 2:
msg = Message(domain="ui", message="No Resource.")
raise ValidationFailed, (msg,)
| [
"georgios.dagkakis@nexedi.com"
] | georgios.dagkakis@nexedi.com |
cccfd301348060e0bbbb8535705d6e1069d6c44a | 4341fa31ee6a6f964c4545b648eedfdda4192b3a | /contentFeatures.py | 43b97a25a578d7e3f4e5a40a2db11fc6c74e705a | [] | no_license | Asmita-Ranashinge/Data-Analytics | 60715ec65b423fb0ee16e9753b52682abc31a305 | 0fadc0ad3ada90b0a641cc7c7ece0623de5a8cad | refs/heads/master | 2020-06-12T22:11:56.531414 | 2019-06-29T19:55:02 | 2019-06-29T19:55:02 | 194,443,447 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,028 | py | import string
import nltk
from collections import Counter
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from nltk.stem.porter import *
def get_tokens():
with open('Phishing_Content.txt', 'r') as shakes: #load text file
text = shakes.read()
lowers = text.lower()
tokenizer = RegexpTokenizer(r'\w\D\w+') #remove digit and punctuation
tokens = tokenizer.tokenize(lowers) #convert all the letters into lowercase
return tokens
tokens = get_tokens()
count = Counter(tokens)
filtered = [w for w in tokens if not w in stopwords.words('english')] #remove all the stopwords such as 'the', 'in', 'at' etc.
count = Counter(filtered)
print (count.most_common(50))
#stemming: to remove derived words
def stem_tokens(tokens, stemmer):
stemmed = []
for item in tokens:
stemmed.append(stemmer.stem(item))
return stemmed
stemmer = PorterStemmer()
stemmed = stem_tokens(filtered, stemmer)
count = Counter(stemmed)
print (count.most_common(50))
| [
"asmita.ranashinge@gmail.com"
] | asmita.ranashinge@gmail.com |
0e1cdca49f5eeb7315a63e0091ae55029d0eece7 | 32c56293475f49c6dd1b0f1334756b5ad8763da9 | /google-cloud-sdk/lib/third_party/kubernetes/client/models/v1_watch_event.py | eeac0514753ca0d2cfe0c9ba717f53e73fabf2aa | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | permissive | bopopescu/socialliteapp | b9041f17f8724ee86f2ecc6e2e45b8ff6a44b494 | 85bb264e273568b5a0408f733b403c56373e2508 | refs/heads/master | 2022-11-20T03:01:47.654498 | 2020-02-01T20:29:43 | 2020-02-01T20:29:43 | 282,403,750 | 0 | 0 | MIT | 2020-07-25T08:31:59 | 2020-07-25T08:31:59 | null | UTF-8 | Python | false | false | 3,880 | py | # coding: utf-8
"""
Kubernetes
No description provided (generated by Swagger Codegen
https://github.com/swagger-api/swagger-codegen)
OpenAPI spec version: v1.14.4
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from pprint import pformat
from six import iteritems
import re
class V1WatchEvent(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name and the value is attribute
type.
attribute_map (dict): The key is attribute name and the value is json key
in definition.
"""
swagger_types = {'object': 'RuntimeRawExtension', 'type': 'str'}
attribute_map = {'object': 'object', 'type': 'type'}
def __init__(self, object=None, type=None):
"""
V1WatchEvent - a model defined in Swagger
"""
self._object = None
self._type = None
self.discriminator = None
self.object = object
self.type = type
@property
def object(self):
"""
Gets the object of this V1WatchEvent.
Object is: * If Type is Added or Modified: the new state of the object.
* If Type is Deleted: the state of the object immediately before
deletion. * If Type is Error: *Status is recommended; other types may
make sense depending on context.
:return: The object of this V1WatchEvent.
:rtype: RuntimeRawExtension
"""
return self._object
@object.setter
def object(self, object):
"""
Sets the object of this V1WatchEvent.
Object is: * If Type is Added or Modified: the new state of the object.
* If Type is Deleted: the state of the object immediately before
deletion. * If Type is Error: *Status is recommended; other types may
make sense depending on context.
:param object: The object of this V1WatchEvent.
:type: RuntimeRawExtension
"""
if object is None:
raise ValueError('Invalid value for `object`, must not be `None`')
self._object = object
@property
def type(self):
"""
Gets the type of this V1WatchEvent.
:return: The type of this V1WatchEvent.
:rtype: str
"""
return self._type
@type.setter
def type(self, type):
"""
Sets the type of this V1WatchEvent.
:param type: The type of this V1WatchEvent.
:type: str
"""
if type is None:
raise ValueError('Invalid value for `type`, must not be `None`')
self._type = type
def to_dict(self):
"""
Returns the model properties as a dict
"""
result = {}
for attr, _ in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(
map(lambda x: x.to_dict() if hasattr(x, 'to_dict') else x, value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(
map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], 'to_dict') else item, value.items()))
else:
result[attr] = value
return result
def to_str(self):
"""
Returns the string representation of the model
"""
return pformat(self.to_dict())
def __repr__(self):
"""
For `print` and `pprint`
"""
return self.to_str()
def __eq__(self, other):
"""
Returns true if both objects are equal
"""
if not isinstance(other, V1WatchEvent):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""
Returns true if both objects are not equal
"""
return not self == other
| [
"jonathang132298@gmail.com"
] | jonathang132298@gmail.com |
b6329d939728790bcea89156b8375bc4669e816f | 67a7bf852f9284f59b0b3e604572524ae6f02cf2 | /mergesort.py | 30724c7c8d469fe44d7dc7741d37e51d472e5da5 | [] | no_license | sheetaljantikar/python-codes | 6745cfda23f47e387a5954e2c9bcc739164e0803 | f0a27c3159aafd97f9d66f192d8cdc48fe51bca5 | refs/heads/master | 2020-12-25T13:45:48.132779 | 2016-06-28T04:22:32 | 2016-06-28T04:22:32 | 62,109,677 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 764 | py | def merge(left,right,list):
nl=len(left)
nR=len(right)
i=0
j=0
k=0
while(i<nl and j<nR):
if (left[i]<right[j]):
list[k]=left[i]
k=k+1
i=i+1
else:
list[k]=right[j]
k=k+1
j=j+1
while (i<nl):
list[k]=left[i]
i=i+1
k=k+1
while(j<nR):
list[k]=right[j]
j=j+1
k=k+1
return list
def mergesort(list):
if len(list)<2:
return
else:
mid=len(list)//2
left=list[0:mid]
right=list[mid:]
mergesort(left)
mergesort(right)
merge(left,right,list)
return list
a=[3,7,4,1,8,2]
b=mergesort(a)
| [
"noreply@github.com"
] | noreply@github.com |
3d648307ee324055cbbbdd9c14e4bd57f785a79d | c9704cb6f799620090f0e8e3ec3fbcb720e032e6 | /grunge/tests/test_tracks.py | 6819feb99e77906a25683263e96cb52de27f31c3 | [] | no_license | LiveLike/grunge | afceb90c96bce73311e41c2f2d69091808fa84ea | 8ac296099b7e579147e7f6b2685cfd788650c0b8 | refs/heads/main | 2023-02-23T13:59:13.148883 | 2021-01-26T17:58:31 | 2021-01-26T17:58:31 | 333,166,387 | 0 | 3 | null | 2021-01-26T19:10:35 | 2021-01-26T17:43:37 | Python | UTF-8 | Python | false | false | 1,404 | py | from uuid import UUID
from furl import furl
from rest_framework import status
from rest_framework.reverse import reverse as drf_reverse
from . import BaseAPITestCase
class TrackTests(BaseAPITestCase):
def setUp(self):
self.track_name = "Last Exit"
self.track_uuid = UUID("b3083319-47a9-40ed-a4e0-a79d050d9df7")
self.album_uuid = UUID("b4fee0db-0c93-4470-96b3-cebd158033a0")
def test_list_tracks(self):
url = drf_reverse("track-list", kwargs={"version": self.version})
r = self.client.get(url)
self.assertEqual(r.status_code, status.HTTP_200_OK)
self.assertEqual(r.data["count"], 3695)
def test_search_tracks(self):
url = drf_reverse("track-list", kwargs={"version": self.version})
url = furl(url).set({"name": self.track_name}).url
r = self.client.get(url)
self.assertEqual(r.status_code, status.HTTP_200_OK)
self.assertEqual(r.data["count"], 4)
self.assertEqual(r.data["results"][0]["uuid"], self.track_uuid)
def test_get_track(self):
url = drf_reverse(
"track-detail", kwargs={"version": self.version, "uuid": self.track_uuid}
)
r = self.client.get(url)
self.assertEqual(r.status_code, status.HTTP_200_OK)
self.assertEqual(r.data["name"], self.track_name)
self.assertEqual(r.data["album"]["uuid"], self.album_uuid)
| [
"benwilber@gmail.com"
] | benwilber@gmail.com |
8cc5c311344282da37caf398197d8929dffbdf8f | a5b235e3b6d263c3ea6e820154454b703148181b | /tool/begin.py | 9d71c390e3c45732370f694e39e7bf748c0ac346 | [] | no_license | shiyuyuanyue/stat | 9ad343e97c1d29dfb795dc88cc83372afbc5edd8 | a24ed90c6b08d1e548ed7fb589b9587d1c3dfd14 | refs/heads/master | 2021-01-13T23:53:44.418934 | 2020-02-23T15:27:32 | 2020-02-23T15:27:32 | 242,534,266 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 29 | py | data = {}
print(bool([data])) | [
"776977960@qq.com"
] | 776977960@qq.com |
cd3b8b16eeef7fca013cfb2b4744d00d3610f92f | 21587c0e6c0b71cd8db7f8592b75e661388a53d3 | /run.py | b761ad01e77e0726a97e17318efe25513ad6ef17 | [] | no_license | Junwu302/ResistoMap | 63999f99fd2ae3fbfd815e993cd90ad61225eca5 | 48da878eb6927d15c14733f9eeeb155fafbe616b | refs/heads/master | 2020-06-14T00:22:09.591337 | 2017-01-16T16:38:45 | 2017-01-16T16:38:45 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 888 | py | from src.main import main
import argparse
import os
SCRIPTDIR = os.path.dirname(os.path.realpath(__file__))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('read_file', metavar='read_file', type=str, nargs='+',
help='input read files')
parser.add_argument('-n', '--n_threads', type=int,
help='number of bowtie/diamond threads (default: 1)', default=1)
parser.add_argument('-o', '--output_folder', type=str,
help='output folder path (default: current dir)', default=os.getcwd())
args = vars(parser.parse_args())
read_files_pathes = [os.path.abspath(read_file) for read_file in args['read_file']]
n_threads = args['n_threads']
output_folder = os.path.abspath(args['output_folder'])
main(read_files_pathes, n_threads, output_folder, SCRIPTDIR)
| [
"yarygin@phystech.edu"
] | yarygin@phystech.edu |
e168642194f6d7a4aef859071a5f60aaa48f573d | 327112e61d08ff89a6609d3a9e7d091c72718c44 | /tutorial/settings.py | cec40f80ab040d2a77bc4a1aff2c407a1b128742 | [] | no_license | bridgecrew-perf7/tutorial | 1149698870b619c61be7d31ec5cf3df59d9bfefa | 456a27fde546b431cb039545cc4af51fdab2a7e6 | refs/heads/master | 2023-05-08T14:29:15.907222 | 2021-05-29T19:36:05 | 2021-05-29T19:36:05 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,225 | py | """
Django settings for tutorial project.
Generated by 'django-admin startproject' using Django 3.0.3.
For more information on this file, see
https://docs.djangoproject.com/en/3.0/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.0/ref/settings/
"""
import os
import datetime
from dotenv import load_dotenv
load_dotenv()
# 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/3.0/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'imn@d&n&d-1r1uo8w5dd*x76f7jwx9o(g@#!)m@!+uq3bguo)l'
# SECURITY WARNING: don't run with debug turned on in production!
PRODUCTION = os.environ.get("PRODUCTION", False) == "true"
DEBUG = not PRODUCTION
ALLOWED_HOSTS = [
"localhost",
"127.0.0.1",
"ptibem.cs.ui.ac.id"
]
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'crispy_forms',
'django_cas_ng',
'rest_framework',
'rest_framework.authtoken',
'rest_auth',
'rest_auth.registration',
'corsheaders',
'app_auth',
'app_profile',
]
MIDDLEWARE = [
'corsheaders.middleware.CorsMiddleware',
'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',
]
AUTHENTICATION_BACKENDS = (
'django.contrib.auth.backends.ModelBackend',
'app_auth.sso_backends.SSOCASBackend', # Dari app_auth
)
ROOT_URLCONF = 'tutorial.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 = 'tutorial.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.0/ref/settings/#databases
if PRODUCTION:
DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql_psycopg2",
"NAME": os.environ.get("DATABASE_NAME"),
"USER": os.environ.get("DATABASE_USER"),
"PASSWORD": os.environ.get("DATABASE_PASSWORD"),
"HOST": os.environ.get("DATABASE_HOST"),
"PORT": os.environ.get("DATABASE_PORT"),
}
}
else:
DATABASES = {
"default": {
"ENGINE": "django.db.backends.sqlite3",
"NAME": os.path.join(BASE_DIR, "db.sqlite3"),
}
}
REST_FRAMEWORK = {
"DEFAULT_PERMISSION_CLASSES": (
'rest_framework.permissions.IsAuthenticated',
'rest_framework.permissions.IsAdminUser',
),
"DEFAULT_AUTHENTICATION_CLASSES": (
'rest_framework.authentication.TokenAuthentication',
'rest_framework_jwt.authentication.JSONWebTokenAuthentication',
'rest_framework.authentication.SessionAuthentication',
'rest_framework.authentication.BasicAuthentication',
),
}
# JWT config
JWT_AUTH = {
'JWT_SECRET_KEY': 'SECRET_KEY',
'JWT_PUBLIC_KEY': None,
'JWT_PRIVATE_KEY': None,
'JWT_ALGORITHM': 'HS256',
'JWT_VERIFY': True,
'JWT_VERIFY_EXPIRATION': True,
'JWT_LEEWAY': 0,
'JWT_EXPIRATION_DELTA': datetime.timedelta(days=1),
'JWT_REFRESH_EXPIRATION_DELTA': datetime.timedelta(days=7),
'JWT_AUTH_HEADER_PREFIX': 'Bearer',
# Handler dari app_auth
'JWT_RESPONSE_PAYLOAD_HANDLER': 'app_auth.sso_jwt.jwt_response_payload_handler',
'JWT_PAYLOAD_HANDLER': 'app_auth.sso_jwt.jwt_payload_handler',
}
# Password validation
# https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators
AUTH_USER_MODEL = 'app_auth.User'
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/3.0/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/3.0/howto/static-files/
STATIC_URL = '/static/'
CORS_ORIGIN_ALLOW_ALL = True
CORS_ALLOW_CREDENTIALS = True
CORS_ORIGIN_WHITELIST = [
"https://bemapps.cs.ui.ac.id",
"https://ptibem.cs.ui.ac.id",
"http://localhost:3000",
]
URL_PREFIX = os.environ.get("URL_PREFIX", "")
MEDIA_ROOT = os.path.join(BASE_DIR, 'media')
MEDIA_URL = f'{URL_PREFIX}/media/'
STATIC_ROOT = os.path.join(BASE_DIR, 'static')
STATICFILES_STORAGE = 'whitenoise.storage.CompressedManifestStaticFilesStorage'
# Django CAS-NG configuration
CAS_SERVER = os.environ.get("CAS_SERVER", 'CAS 2')
CAS_SERVER_URL = os.environ.get("CAS_SERVER_URL", 'https://sso.ui.ac.id/cas2/')
CAS_POPUP_LOGIN = os.environ.get("CAS_POPUP_LOGIN", False)
CAS_FORCE_CHANGE_USERNAME_CASE = 'lower'
CAS_LOGOUT_COMPLETELY = True
CAS_CREATE_USER = True
CAS_APPLY_ATTRIBUTES_TO_USER = True
# Where to send a user after logging in or out if there is no referrer and no next page set.
CAS_REDIRECT_URL = os.environ.get("CAS_REDIRECT_URL", 'https://www.google.com/')
CLIENT_HOST = os.environ.get("CLIENT_HOST", 'https://www.google.com/')
| [
"agenganugrah@gmail.com"
] | agenganugrah@gmail.com |
119662e1432ab732091a253b070a031ee6566b6d | 9490e6f64e8824f15384d8f740fe136f31cec1b5 | /venv/bin/ipython | 5262c7d3931f5ba0f150a72e2986e01884b7f486 | [] | no_license | AmoCook/GUI_pj | cc3b49d8fb6244e1c33163812cb1835b8d18b960 | 729bed91a96d7366401b82dd7cfc2cbc4ff59997 | refs/heads/master | 2020-04-16T13:23:58.449573 | 2019-01-14T09:22:11 | 2019-01-14T09:22:11 | 165,625,589 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 261 | #!/Users/amo/PycharmProjects/test_1/venv/bin/python
# -*- coding: utf-8 -*-
import re
import sys
from IPython import start_ipython
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(start_ipython())
| [
"amo9502@stumail.nwu.edu.cn"
] | amo9502@stumail.nwu.edu.cn | |
410dc874ff5b29dbc7227b95c1a8c1894533a7aa | 6113017bfaec2c2f0e5919b41bb78a5336722303 | /luminartechnolabproject/dictionary/word_count.py | e25d3bcb5e42bd4cd5f5f0acda8fe740556e45d1 | [] | no_license | prince2255/python | 2affcf998dcf1e756fe36c0e8ee5f70ccc226cb6 | b0ad2e5a62ac0d6251ceefdc1909f294e9d9ac69 | refs/heads/master | 2020-12-11T00:42:49.680357 | 2020-01-28T05:54:32 | 2020-01-28T05:54:32 | 233,756,640 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 216 | py | line="hai hello hai how"
words=line.split(" ")
dict={}
for word in words:
if(word not in dict):
dict[word]=1
else:
dict[word]+=1
for item in dict:
print(item,end=" ")
print(dict[item]) | [
"75prince76@gmail.com"
] | 75prince76@gmail.com |
c4167281b5e6283bb6cd67dd447b40152c61100c | f36fc94a1ac5ffbfb6d2a78807992347a7e9f6e2 | /assignment1/cs231n/classifiers/linear_classifier.py | 844826318d20b5e2114d43a0cfb20aa6ca31046a | [] | no_license | Dipeshtamboli/CS231n-Assignments | d2f60504410499aed96da9f988fc69c239096abe | 146b3ce885867c81dd609abdbaedabeafa23f7b7 | refs/heads/master | 2020-04-11T09:10:45.563002 | 2019-01-01T20:56:18 | 2019-01-01T20:56:18 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,966 | py | from __future__ import print_function
import numpy as np
from cs231n.classifiers.linear_svm import *
from cs231n.classifiers.softmax import *
class LinearClassifier(object):
def __init__(self):
self.W = None
def train(self, X, y, learning_rate=1e-3, reg=1e-5, num_iters=100,
batch_size=200, verbose=False):
"""
Train this linear classifier using stochastic gradient descent.
Inputs:
- X: A numpy array of shape (N, D) containing training data; there are N
training samples each of dimension D.
- y: A numpy array of shape (N,) containing training labels; y[i] = c
means that X[i] has label 0 <= c < C for C classes.
- learning_rate: (float) learning rate for optimization.
- reg: (float) regularization strength.
- num_iters: (integer) number of steps to take when optimizing
- batch_size: (integer) number of training examples to use at each step.
- verbose: (boolean) If true, print progress during optimization.
Outputs:
A list containing the value of the loss function at each training iteration.
"""
num_train, dim = X.shape
num_classes = np.max(y) + 1 # assume y takes values 0...K-1 where K is number of classes
if self.W is None:
# lazily initialize W
self.W = 0.001 * np.random.randn(dim, num_classes)
# Run stochastic gradient descent to optimize W
loss_history = []
for it in range(num_iters):
X_batch = None
y_batch = None
#########################################################################
# TODO: #
# Sample batch_size elements from the training data and their #
# corresponding labels to use in this round of gradient descent. #
# Store the data in X_batch and their corresponding labels in #
# y_batch; after sampling X_batch should have shape (dim, batch_size) # @@ X_batch should have shape (batch_size,dim)
# and y_batch should have shape (batch_size,) # @@ instead of (dim,batch_size)
# #
# Hint: Use np.random.choice to generate indices. Sampling with #
# replacement is faster than sampling without replacement. #
#########################################################################
#######
#CODE
#######
ids=np.arange(batch_size)
ids=np.random.choice(ids,batch_size,replace=True)
X_batch=X[ids]
y_batch=y[ids]
#######
pass
#########################################################################
# END OF YOUR CODE #
#########################################################################
# evaluate loss and gradient
loss, grad = self.loss(X_batch, y_batch, reg)
loss_history.append(loss)
# perform parameter update
#########################################################################
# TODO: #
# Update the weights using the gradient and the learning rate. #
#########################################################################
#######
#CODE
#######
self.W-=learning_rate*grad
#######
pass
#########################################################################
# END OF YOUR CODE #
#########################################################################
if verbose and it % 100 == 0:
print('iteration %d / %d: loss %f' % (it, num_iters, loss))
return loss_history
def predict(self, X):
"""
Use the trained weights of this linear classifier to predict labels for
data points.
Inputs:
- X: A numpy array of shape (N, D) containing training data; there are N
training samples each of dimension D.
Returns:
- y_pred: Predicted labels for the data in X. y_pred is a 1-dimensional
array of length N, and each element is an integer giving the predicted
class.
"""
y_pred = np.zeros(X.shape[0])
###########################################################################
# TODO: #
# Implement this method. Store the predicted labels in y_pred. #
###########################################################################
#######
#CODE
#######
score=X.dot(self.W)
y_pred=np.argmax(score,axis=1)
#######
pass
###########################################################################
# END OF YOUR CODE #
###########################################################################
return y_pred
def loss(self, X_batch, y_batch, reg):
"""
Compute the loss function and its derivative.
Subclasses will override this.
Inputs:
- X_batch: A numpy array of shape (N, D) containing a minibatch of N
data points; each point has dimension D.
- y_batch: A numpy array of shape (N,) containing labels for the minibatch.
- reg: (float) regularization strength.
Returns: A tuple containing:
- loss as a single float
- gradient with respect to self.W; an array of the same shape as W
"""
pass
class LinearSVM(LinearClassifier):
""" A subclass that uses the Multiclass SVM loss function """
def loss(self, X_batch, y_batch, reg):
return svm_loss_vectorized(self.W, X_batch, y_batch, reg)
class Softmax(LinearClassifier):
""" A subclass that uses the Softmax + Cross-entropy loss function """
def loss(self, X_batch, y_batch, reg):
return softmax_loss_vectorized(self.W, X_batch, y_batch, reg)
| [
"dipeshtamboli@gmail.com"
] | dipeshtamboli@gmail.com |
d243c506f63f7cc1780806923f5d78de5943116b | 08ee36e0bb1c250f7f2dfda12c1a73d1984cd2bc | /src/mnistk/networks/linearrelu_5.py | efcfbec738c0a5f4fad45d439a1de52528caf7c2 | [] | no_license | ahgamut/mnistk | 58dadffad204602d425b18549e9b3d245dbf5486 | 19a661185e6d82996624fc6fcc03de7ad9213eb0 | refs/heads/master | 2021-11-04T07:36:07.394100 | 2021-10-27T18:37:12 | 2021-10-27T18:37:12 | 227,103,881 | 2 | 1 | null | 2020-02-19T22:07:24 | 2019-12-10T11:33:09 | Python | UTF-8 | Python | false | false | 675 | py | # -*- coding: utf-8 -*-
"""
linearrelu_5.py
:copyright: (c) 2019 by Gautham Venkatasubramanian.
:license: MIT
"""
import torch
from torch import nn
class LinearReLU_5(nn.Module):
def __init__(self):
nn.Module.__init__(self)
self.f0 = nn.Linear(in_features=784, out_features=70, bias=True)
self.f1 = nn.ReLU(inplace=False)
self.f2 = nn.Linear(in_features=70, out_features=10, bias=False)
self.f3 = nn.LogSoftmax(dim=1)
def forward(self, *inputs):
x = inputs[0]
x = x.view(x.shape[0],784)
x = self.f0(x)
x = self.f1(x)
x = self.f2(x)
x = self.f3(x)
return x
| [
"41098605+ahgamut@users.noreply.github.com"
] | 41098605+ahgamut@users.noreply.github.com |
9928a8ad26f248afae38d0f90a41c40115d927dc | 3865d338db6caedff9cce9c0ca2ac4b5929ac2d1 | /nanjiang/misc/uniprottrembldat2table.py | d042cb83f1815e6a9de9844a6060620eeda49a66 | [] | no_license | vam-sin/bioinfo-toolbox | fc90b347da7d733a2e5732b7352f1e8cdbf5b164 | 79f52038b7eb20337508ee49a87d2677a8ffad9c | refs/heads/master | 2022-12-09T18:39:18.743490 | 2020-08-26T14:14:58 | 2020-08-26T14:14:58 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,325 | py | #!/usr/bin/env python
# Description: Extract data from uniprot_trembl.dat
# ChangeLog 2014-08-28
# add options
# -keep_no_genename Keep proteins without gene name
# -keep_non_refpro Keep protein not in reference proteome
# -keep_isoform Keep proteins in isoforms
# ChangeLog 2014-08-29
# taxonomic_class "Bacteria." is considered as "Bacteria", for e.g. O34002,
# P07472, Q54506
#
import os
import sys
import myfunc
usage = """
usage: uniprottrembldat2table.py -i uniprot_trembl.dat [-o OUTFILE]
Description: Extract data from uniprot_trembl.dat
and output table with the format
# AC Length GN OS OC
tab delimited
Options:
-q Quiet mode
-oc STR Restrict to taxonomic_class
-keep_no_genename Keep proteins without gene name
-keep_non_refpro Keep protein not in reference proteome
-keep_isoform Keep proteins in isoforms
-h, --help Print this help message and exit
Created 2012-06-01, updated 2014-08-29, Nanjiang Shu
"""
def PrintHelp():
print usage
def FilterRecord(recordList, restrictOCList):#{{{
# Filter records
# 1. without gene name
# 2. without keyword "reference proteome" (KW)
# 3. filter out isoforms (those with ID-names ended with -INT)
if len(recordList) <= 0:
return []
newList = []
isRestrictOC = False
if len(restrictOCList) > 0 and restrictOCList[0].lower() != "all":
isRestrictOC = True
for rd in recordList:
if g_params['filter_no_genename'] and rd['genename'] == "" :
print >> sys.stderr, "%s NO genaname, ignored" % (rd['accession'])
continue
if g_params['filter_non_refpro'] and not rd['isRefPro']:
print >> sys.stderr, "%s not reference proteome, ignored" % (rd['accession'])
continue
if g_params['filter_isoform'] and rd['accession'].find("-") != -1:
print >> sys.stderr, "%s with isoforms, ignored" % (rd['accession'])
continue
if isRestrictOC and (rd['taxonomic_class'] not in restrictOCList):
print >> sys.stderr, (rd['accession'], "not in", restrictOCList,
"ignored.")
continue
newList.append(rd)
return newList
#}}}
def WriteRecord(recordList, fpout):#{{{
for rd in recordList:
fpout.write("%s\t%d\t%s\t%s\t%s\t%s\t%d\n"%(
rd['accession'],
rd['length'],
rd['genename'],
rd['organism'],
rd['taxonomic_class'],
";".join(rd['pfamidList']),
rd['isRefPro']
))
#}}}
def ExtractFromUniprotTremblRecord(recordContent):#{{{
record = {}
lines = recordContent.split("\n")
numLine = len(lines)
i = 0
# AC can be multiple lines
str_accession = "" # AC
str_genename = "" # GN
str_organism = "" # OS
pfamidList = [] #
str_keyword = ""
length = 0 # from ID record
str_taxonomic_class = "" # OC, e.g. Archaes, Becteria
for line in lines:
if len(line) > 2:
tag = line[0:2]
if tag == "ID":
strs = line[5:].split()
nstrs = len(strs)
length = int (strs[nstrs-2])
elif tag == "AC":
str_accession += line[5:]
elif tag == "GN":
str_genename += line[5:]
elif tag == "OS":
str_organism += line[5:]
elif tag == "OC":
str_taxonomic_class += line[5:]
elif tag == "KW":
str_keyword += line[5:]
elif tag == "DR":
if line[5:].find("Pfam") == 0:
strs = line[5:].split(";")
pfamidList.append(strs[1].strip())
elif tag == "SQ":
break
#accession
accessionList = str_accession.split(";")
accessionList = filter(None, accessionList)
accessionList = [x.strip() for x in accessionList]
accession = ";".join(accessionList)
# genename:
strs = str_genename.split(";")
strs = filter(None, strs)
li = []
for ss in strs:
sp1 = ss.split("=")
if len(sp1) == 1:
ac = sp1[0].strip()
else:
ac = sp1[1].strip()
li.append(ac)
genename = ";".join(li)
# organism
organism = str_organism.rstrip(".")
# taxonomic_class
taxonomic_class = str_taxonomic_class.split(";")[0]
taxonomic_class = taxonomic_class.strip(".") # added 2014-08-29, this solved Bacteria. for P07472.
isRefPro = False
if str_keyword.find("Reference proteome") != -1:
isRefPro = True
else:
isRefPro = False
if accession != "":
record['accession'] = accession
record['length'] = length
record['genename'] = genename
record['organism'] = organism
record['taxonomic_class'] = taxonomic_class
record['isRefPro'] = isRefPro
record['pfamidList'] = pfamidList
return record
else:
return {}
#}}}
def Read_UniprotTremblData_from_buffer(buff, recordList, isEOFreached):#{{{
if not buff:
return ""
unprocessedBuffer = ""
beg = 0
end = 0
while 1:
beg=buff.find("ID ",beg)
if beg >= 0:
end=buff.find("\n//",beg+1)
if end >= 0:
recordContent = buff[beg:end]
record = ExtractFromUniprotTremblRecord(recordContent)
if record != {}:
recordList.append(record)
beg = end
else:
unprocessedBuffer = buff[beg:]
break
else:
unprocessedBuffer = buff[end:]
break
if isEOFreached and unprocessedBuffer:
recordContent = unprocessedBuffer
record = ExtractFromUniprotTremblRecord(recordContent)
if record != {}:
recordList.append(record)
unprocessedBuffer = ""
return unprocessedBuffer
#}}}
def UniprotTremblData2Table(datafile, restrictOCList, fpout):#{{{
try:
fpout.write("#AC\tLength\tGN\tOS\tOC\tPfamID\tisRefPro\n")
fpin = open(datafile, "r")
unprocessedBuffer=""
isEOFreached = False
while 1:
buff = fpin.read(BLOCK_SIZE)
if len(buff) < BLOCK_SIZE:
isEOFreached = True
buff = unprocessedBuffer + buff
recordList = []
unprocessedBuffer = Read_UniprotTremblData_from_buffer(
buff, recordList, isEOFreached)
if len(recordList) > 0:
filteredRecordList = FilterRecord(recordList, restrictOCList)
if len(filteredRecordList) > 0:
WriteRecord(filteredRecordList, fpout)
if isEOFreached == True:
break
fpin.close()
except IOError:
print >> sys.stderr, "Failed to read datafile ", datafile
return 1
#}}}
def main(g_params):#{{{
argv = sys.argv
numArgv = len(argv)
if numArgv < 2:
PrintHelp()
return 1
outfile = ""
datafile = ""
restrictOCList = []
i = 1
isNonOptionArg=False
while i < numArgv:
if isNonOptionArg == True:
datafile = argv[i]
isNonOptionArg = False
i += 1
elif argv[i] == "--":
isNonOptionArg = True
i += 1
elif argv[i][0] == "-":
if argv[i] in ["-h", "--help"]:
PrintHelp()
return 1
elif argv[i] in ["-o", "--o", "-outfile", "--outfile"]:
outfile = argv[i+1]
i += 2
elif argv[i] in ["-i", "--i"] :
datafile = argv[i+1]
i += 2
elif argv[i] in ["-keep_isoform", "--keep_isoform"] :
g_params['filter_isoform'] = False
i += 1
elif argv[i] in ["-keep_non_refpro", "--keep_non_refpro"] :
g_params['filter_non_refpro'] = False
i += 1
elif argv[i] in ["-keep_no_genename", "--keep_no_genename"] :
g_params['filter_no_genename'] = False
i += 1
elif argv[i] in ["-oc", "--oc"] :
restrictOCList.append(argv[i+1])
i += 2
elif argv[i] in ["-q"]:
g_params['isQuiet'] = True
i += 1
else:
print >> sys.stderr, "Error! Wrong argument:", argv[i]
return 1
else:
datafile = argv[i]
i += 1
if not os.path.exists(datafile):
print >> sys.stderr, "datafile %s not set or not exists. Exit" %(datafile)
return 1
fpout = myfunc.myopen(outfile, sys.stdout, "w", False)
UniprotTremblData2Table(datafile, restrictOCList, fpout)
myfunc.myclose(fpout)
return 0
#}}}
def InitGlobalParameter():#{{{
g_params = {}
g_params['isQuiet'] = True
g_params['filter_no_genename'] = True
g_params['filter_non_refpro'] = True
g_params['filter_isoform'] = True
return g_params
#}}}
if __name__ == '__main__' :
BLOCK_SIZE=100000
g_params = InitGlobalParameter()
sys.exit(main(g_params))
| [
"nanjiang.shu@bils.se"
] | nanjiang.shu@bils.se |
8e65f1218388ca45500e4bd62348647c2fbb7197 | 344e2956b4e2a30a8ef7532d951f96d995d1dd1e | /21_maskrcnn/lib/cfgs/cascade_mask_rcnn_r101_64x4d_fpn_coco.py | d43096d1dc7c09bd4ed5fbb76ee8a9fbe1c09e25 | [
"Apache-2.0",
"LGPL-3.0-only",
"MIT",
"LicenseRef-scancode-proprietary-license",
"BSD-3-Clause",
"GPL-3.0-only"
] | permissive | karndeepsingh/Monk_Object_Detection | e64199705326e4cd65e4b29946cae210a4ef9649 | 425fa50a3236cb9097389646275da06bf9185f6b | refs/heads/master | 2022-12-22T18:26:53.933397 | 2020-09-28T12:49:50 | 2020-09-28T12:49:50 | 299,307,843 | 1 | 1 | Apache-2.0 | 2020-09-28T12:52:18 | 2020-09-28T12:52:17 | null | UTF-8 | Python | false | false | 9,156 | py | # model settings
model = dict(
type='CascadeRCNN',
pretrained='torchvision://resnext101_64x4d',
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch'),
neck=dict(
type='FPN',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
num_outs=5),
rpn_head=dict(
type='RPNHead',
in_channels=256,
feat_channels=256,
anchor_generator=dict(
type='AnchorGenerator',
scales=[8],
ratios=[0.5, 1.0, 2.0],
strides=[4, 8, 16, 32, 64]),
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[.0, .0, .0, .0],
target_stds=[1.0, 1.0, 1.0, 1.0]),
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0)),
roi_head=dict(
type='CascadeRoIHead',
num_stages=3,
stage_loss_weights=[1, 0.5, 0.25],
bbox_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
out_channels=256,
featmap_strides=[4, 8, 16, 32]),
bbox_head=[
dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=80,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0., 0., 0., 0.],
target_stds=[0.1, 0.1, 0.2, 0.2]),
reg_class_agnostic=True,
loss_cls=dict(
type='CrossEntropyLoss',
use_sigmoid=False,
loss_weight=1.0),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0,
loss_weight=1.0)),
dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=80,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0., 0., 0., 0.],
target_stds=[0.05, 0.05, 0.1, 0.1]),
reg_class_agnostic=True,
loss_cls=dict(
type='CrossEntropyLoss',
use_sigmoid=False,
loss_weight=1.0),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0,
loss_weight=1.0)),
dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=80,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0., 0., 0., 0.],
target_stds=[0.033, 0.033, 0.067, 0.067]),
reg_class_agnostic=True,
loss_cls=dict(
type='CrossEntropyLoss',
use_sigmoid=False,
loss_weight=1.0),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))
],
mask_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
out_channels=256,
featmap_strides=[4, 8, 16, 32]),
mask_head=dict(
type='FCNMaskHead',
num_convs=4,
in_channels=256,
conv_out_channels=256,
num_classes=80,
loss_mask=dict(
type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))))
# model training and testing settings
train_cfg = dict(
rpn=dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7,
neg_iou_thr=0.3,
min_pos_iou=0.3,
match_low_quality=True,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=256,
pos_fraction=0.5,
neg_pos_ub=-1,
add_gt_as_proposals=False),
allowed_border=0,
pos_weight=-1,
debug=False),
rpn_proposal=dict(
nms_across_levels=False,
nms_pre=2000,
nms_post=2000,
max_num=2000,
nms_thr=0.7,
min_bbox_size=0),
rcnn=[
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.5,
min_pos_iou=0.5,
match_low_quality=False,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
mask_size=28,
pos_weight=-1,
debug=False),
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.6,
neg_iou_thr=0.6,
min_pos_iou=0.6,
match_low_quality=False,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
mask_size=28,
pos_weight=-1,
debug=False),
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7,
neg_iou_thr=0.7,
min_pos_iou=0.7,
match_low_quality=False,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
mask_size=28,
pos_weight=-1,
debug=False)
])
test_cfg = dict(
rpn=dict(
nms_across_levels=False,
nms_pre=1000,
nms_post=1000,
max_num=1000,
nms_thr=0.7,
min_bbox_size=0),
rcnn=dict(
score_thr=0.05,
nms=dict(type='nms', iou_threshold=0.5),
max_per_img=100,
mask_thr_binary=0.5))
#Dataset Settings
dataset_type = 'CocoDataset'
data_root = ''
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1333, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]
data = dict(
samples_per_gpu=, #change1
workers_per_gpu=, #change2
train=dict(
type=dataset_type,
classes=, #change3
ann_file=, #change4
img_prefix=, #change5
pipeline=train_pipeline),
val=dict(
type=dataset_type,
classes=, #change6
ann_file=, #change7
img_prefix=, #change8
pipeline=test_pipeline),
test=dict(
type=dataset_type,
classes=, #change9
ann_file=, #change10
img_prefix=, #change11
pipeline=test_pipeline))
evaluation = dict(interval=, metric='bbox') #change9
# Schedule Settings
optimizer = dict(type='SGD', lr=, momentum=, weight_decay=) #change12
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=) #change13
total_epochs = #change14
# Runtime Dataset
checkpoint_config = dict(interval=) #change15
# yapf:disable
log_config = dict(
interval=50, #change16
hooks=[
dict(type='TextLoggerHook'),
# dict(type='TensorboardLoggerHook')
])
# yapf:enable
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = #change17
resume_from = None
workflow = [('train', 1)]
gpu_ids = None #change18
| [
"abhishek4273@gmail.com"
] | abhishek4273@gmail.com |
ba5bb91ca511973700ab76b1f0f7a7bd8c5fc7f0 | d8bc78d7bf99ad456920740e93db5428093dcb45 | /usuario/models.py | 27473f1074764cbbd65d9bdb9a33d6ad0e6d8699 | [
"MIT"
] | permissive | ongame-entretenimento/cadastro | d698adce23eccf066c8da2504d25c7a93a072f46 | 8c9de028088a96ad2e761156ee597cb56456b376 | refs/heads/master | 2021-03-12T20:13:24.737376 | 2014-09-10T20:45:35 | 2014-09-10T20:45:35 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,810 | py | # -*- coding: utf-8 -*-
from django.db import models
class Estado(models.Model):
nome = models.CharField(max_length=100)
def __unicode__(self):
return self.nome
class Cidade(models.Model):
nome = models.CharField(max_length=100)
estado = models.ForeignKey(Estado)
def __unicode__(self):
return self.nome
class Usuario(models.Model):
SEXO = (
(0, 'Masculino'),
(1, 'Feminino'),
)
usuario = models.CharField(max_length=16, unique=True)
senha = models.CharField(max_length=32)
email = models.EmailField(max_length=40, unique=True)
data_nascimento = models.DateField('Data de Nascimento')
sexo = models.IntegerField(default=0, choices=SEXO)
cidade = models.ForeignKey(Cidade)
confirmado = models.BooleanField(default=0)
hash = models.CharField(max_length=32)
data_cadastro = models.DateTimeField('Data de Cadastro')
def __unicode__(self):
return self.usuario
class Meta:
verbose_name = 'Usuário'
verbose_name_plural = 'Usuários'
class UsuarioPendente(models.Model):
SEXO = (
(0, 'Masculino'),
(1, 'Feminino'),
)
usuario = models.CharField(max_length=16, unique=True)
senha = models.CharField(max_length=32)
email = models.EmailField(max_length=40, unique=True)
data_nascimento = models.DateField('Data de Nascimento')
sexo = models.IntegerField(default=0, choices=SEXO)
cidade = models.ForeignKey(Cidade)
confirmado = models.BooleanField(default=0)
hash = models.CharField(max_length=32)
data_cadastro = models.DateTimeField('Data de Cadastro')
def __unicode__(self):
return self.usuario
class Meta:
verbose_name = 'Usuário Pendente'
verbose_name_plural = 'Usuários Pendentes'
| [
"ti@ti-netbook.(none)"
] | ti@ti-netbook.(none) |
8154743effc63d1f2a7c401f9819631fb1bc162c | a20e686d8e176cd30e157bf55f219b1738b204b7 | /lambda/lambda_comprehend.py | 44030402bbbac2107844a532e3e5b17c385263fd | [
"MIT"
] | permissive | Veryinheart/aws-tutorial-code | 5e61465571f305e75f1905fa26aab0e8dadf3168 | 6b2a88340d8a94e51bf5c2935704edb9a78c4244 | refs/heads/master | 2022-07-07T14:15:35.018888 | 2020-05-13T18:32:22 | 2020-05-13T18:32:22 | 267,770,685 | 1 | 0 | MIT | 2020-05-29T05:12:37 | 2020-05-29T05:12:37 | null | UTF-8 | Python | false | false | 927 | py | """
-*- coding: utf-8 -*-
========================
AWS Lambda
========================
Contributor: Chirag Rathod (Srce Cde)
========================
"""
import boto3
from pprint import pprint
def lambda_handler(event, context):
s3 = boto3.client("s3")
bucket = "bucket-name"
key = "filename.txt"
file = s3.get_object(Bucket = bucket, Key = key)
paragraph = str(file['Body'].read())
comprehend = boto3.client("comprehend")
#Extracting sentiments using comprehend
sentiment = comprehend.detect_sentiment(Text = paragraph, LanguageCode = "en")
print(sentiment)
#Extracting entities using comprehend
entities = comprehend.detect_entities(Text = paragraph, LanguageCode = "en")
pprint(entities)
#Extracting keyphrase using comprehend
keyphrase = comprehend.detect_key_phrases(Text = paragraph, LanguageCode = "en")
pprint(keyphrase)
return 'Thanks'
| [
"chiragr83@gmail.com"
] | chiragr83@gmail.com |
3603592a43f6cb57493b90f261bc46ecb00ef171 | 1f936103af336af6bbd335f45d6baa55c426922b | /monatbx/generate_random_image_list.py | 8a9ca4dabc8f05852c8bdb56a7c99cb54b3732fe | [] | no_license | monarin/monatbx | 2ec342d67f1fbccb82656218ffd136f2eb7d96ab | 43f56974f811e5b2b0dcc428d4f9b36043ed9d04 | refs/heads/master | 2020-06-18T13:08:58.893701 | 2016-11-30T00:58:18 | 2016-11-30T00:58:18 | 75,136,381 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 510 | py | import os
import sys
import random
p = sys.argv[1]
n_images = int(sys.argv[2])
frame_files = []
if os.path.isdir(p):
for pickle_filename in os.listdir(p):
if pickle_filename.endswith('.pickle'):
frame_files.append(p+'/'+pickle_filename)
i_rand = random.sample(range(len(frame_files)),n_images)
frame_files_sel = [frame_files[i] for i in i_rand]
txt_out = ''
for frame in frame_files_sel:
txt_out += frame + '\n'
f = open('frame_rand_'+str(n_images)+'.lst', 'w')
f.write(txt_out)
f.close()
| [
"monarin@gmail.com"
] | monarin@gmail.com |
4eb2b48de24e83967dcf33b509a946a81d00451d | d03ef3eac49ccae08fe33a1ecf874d11fa86e635 | /dozo/commands/extend.py | a19374c1461cdc71c2d61c29a28cf1088143d55f | [] | no_license | johnmontero/dozo | 5ddd2801f8fc919443faffde68fad5ff3f0be8aa | abc3377e3ee32ac21735bd22a7fd41b7d9c881d3 | refs/heads/master | 2021-01-10T21:08:56.890991 | 2012-05-15T06:47:15 | 2012-05-15T06:47:15 | 2,735,707 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,931 | py | from os import path
from os import mkdir
import pystache
import envoy
from tambo import Transport
from dozo.config import db
from dozo.config import get_config_value
from dozo.commands import CommandError
TEMPLATE_OPTION_COMMAND = '''# -*- coding: utf-8-*-
from tambo import Transport
from dozo.config import db
from dozo.config import get_config_value
class Command(object):
"""
{{name}} related actions:
--h, --help, help Prints this help text and exits.
print Print description of the {{name}}
"""
help = "Commands associated with {{name}}"
def __init__(self, argv, conf=None):
self.argv = argv
self.config = conf or db.stored_config()
self.actions = {
'print' : self.{{name}}_print
}
def {{name}}_print(self):
print "Print {{name}}"
def parse_args(self):
transport = Transport(self.argv, check_help=False)
transport.catch_help = self.__doc__
if len(self.argv) <= 1:
transport.print_help()
transport.parse_args()
for action in self.actions:
if transport.has(action):
return self.actions.get(action)()
# If nothing matches, print the help
transport.print_help()
'''
class Command(object):
"""
Command Extend related actions:
-h, --help, help Prints this help text and exits.
create Create subcommand
edit Edit subcommand
path Path to extend subcommands
"""
help = "Commands associated with this commands extend's Dozo"
def __init__(self, argv, conf=None):
self.argv = argv
self.config = conf or db.stored_config()
self.actions = {
'create' : self.cmd_create,
'edit' : self.cmd_edit,
'path' : self.cmd_path_extend
}
def cmd_create(self):
"""
"""
if len(self.argv) < 3:
value = None
else:
value = self.argv[2]
if value is not None:
if value.endswith('.py'):
raise CommandError("\nNot include '.py'\n")
path_extend = get_config_value('path-extend')
if path_extend is None:
print "Path extend is not define."
print "Use:\n dozo extend path /path/to/extend"
return
path_to_file = "{0}/commands/{1}.py".format(path_extend,value)
if path.isfile(path_to_file):
print "\nOption command '{0}' exist.\n".format(value)
filename = '%s/commands/%s.py' % ( path_extend, value )
f = open(filename,'w+')
f.write(pystache.render(TEMPLATE_OPTION_COMMAND,
{'name':value}))
f.close()
def cmd_edit(self):
"""
"""
try:
extend_command = self.argv[2]
except:
extend_command = None
if extend_command is None:
#print "Please use option:"
#print " dozo %s" % self.usage
return
text_editor = get_config_value('text-editor')
if text_editor is None:
print "\n Text editor is not define.\n"
print "Use:\n dozo config add text-editor=vim\n"
return
path_extend = get_config_value('path-extend')
if path_extend is None:
print('''\n Path extend is not define.\n
Use:\n dozo config path-extend /opt/dozo/dozo_extend''')
return
filename = '{0}/commands/{1}.py'.format(path_extend, extend_command)
if not path.isfile(filename):
print('\n{0}: Extend command not exist.\n'.format(
extend_command))
return
cmd = '{0} {1}'.format(text_editor, filename)
r = envoy.run(cmd)
if r is not 0:
print('\n{0}\n'.format(r.std_err))
def cmd_values(self):
"""
"""
try:
for i in self.config.items():
print "%-15s= %-4s" % (i[0], i[1])
print ''
except Exception, error:
raise CommandError("Could not complete command: %s" % error)
def cmd_path_extend(self):
"""
"""
try:
path_extend = self.argv[2]
except:
path_extend = None
if path_extend is None:
try:
del self.config['path-extend']
except KeyError:
pass
else:
if '-' in '/'.join(path_extend.split('/')[-1:]):
raise CommandError("\nIs not character valid '-'.\n")
if not path.isdir(path_extend):
mkdir(path_extend)
path_to_file = '%s/__init__.py' % path_extend
if not path.isfile(path_to_file):
f = open(path_to_file,'w+')
f.write('__name__="path-extend"\n')
f.close()
path_command = '%s/commands' % path_extend
if not path.isdir(path_command):
mkdir(path_command)
path_to_file = '%s/__init__.py' % path_command
if not path.isfile(path_to_file):
f = open(path_to_file,'w+')
f.write('__name__="commands"\n')
f.close()
self.config['path-extend'] = path_extend
def parse_args(self):
transport = Transport(self.argv, check_help=False)
transport.catch_help = self.__doc__
if len(self.argv) <= 1:
transport.print_help()
transport.parse_args()
for action in self.actions:
if transport.has(action):
return self.actions.get(action)()
# If nothing matches, print the help
transport.print_help()
| [
"jmonteroc@gmail.com"
] | jmonteroc@gmail.com |
575a9eb27903aa702c0a9262637736f7f935d21b | 0be37def5e61f61858b9a3c9cbac55cad53224ec | /finchcollector/finchcollector/settings.py | 6949914a0d45e62392c2202a1714bbbddc5e4294 | [] | no_license | crystallynnv/finchcollector | 177b6c23db3175f9f66c0295d455bfff7dc16daa | 9937ec6d0ca6f2b53b2bb7eb5ccac1ecf2a3186a | refs/heads/master | 2021-03-31T06:03:18.088621 | 2020-03-21T16:41:10 | 2020-03-21T16:41:10 | 248,083,778 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,172 | py | """
Django settings for finchcollector project.
Generated by 'django-admin startproject' using Django 3.0.2.
For more information on this file, see
https://docs.djangoproject.com/en/3.0/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.0/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/3.0/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '6axj657e7l7gj193##i6ovpb#kbba@em-j$k4d1dd$jcgf3ou%'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'main_app',
'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 = 'finchcollector.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 = 'finchcollector.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.0/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.postgresql',
'NAME': 'finchcollector',
}
}
# Password validation
# https://docs.djangoproject.com/en/3.0/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/3.0/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/3.0/howto/static-files/
STATIC_URL = '/static/'
LOGIN_REDIRECT_URL = '/finches/'
LOGOUT_REDIRECT_URL = '/'
| [
"home@homes-mbp.lan"
] | home@homes-mbp.lan |
947dced367bd8dde73a91f39443a0f7b80bda3a8 | 86319aad3690906f614ac1af28b8843529e9e0da | /thwackbin/data/__init__.py | a156485bd18d0e80a766cdfa5aabbee5f290dab9 | [] | no_license | sohgoh/thwackbin | b5828783a6179e96784bed0bdb894b179e3bea07 | ba9fedc4bcec598f367aa6d4f2567d1840c65c51 | refs/heads/master | 2021-01-21T03:14:08.261732 | 2014-04-16T03:53:51 | 2014-04-16T04:02:28 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 410 | py | """
thwackbin.data
~~~~~~~~~~~~~~
Package which contains mock results data stored on the file system.
"""
__author__ = 'Andrew Hawker <andrew@appthwack.com>'
import json
import os
RESULTS = None
ROOT = os.path.dirname(__file__)
def init():
"""
Load and cache our results.json data on startup.
"""
global RESULTS
RESULTS = json.load(open(os.path.join(ROOT, 'results.json')))
| [
"andrew.r.hawker@gmail.com"
] | andrew.r.hawker@gmail.com |
0ebcc3529c3a8cb45cbce6983629d8612e22f559 | 4857bf63cfc7a500cfa1f476e05399a82d43a461 | /Hex/play.py | e50b5e733778ad8a59d5df88a013082728e6f692 | [] | no_license | askbk/IT3105-AI-Programming | fe862d85499be0df7a26adbddc7dc050232acc1a | b3543b21fba878f402fd932665473a7f2765cde2 | refs/heads/master | 2023-04-04T19:06:00.102865 | 2021-04-19T08:32:20 | 2021-04-19T08:32:20 | 328,206,521 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 496 | py | import json
from Hex.Game import Board
from Hex.Player import Player
if __name__ == "__main__":
with open("./config.json", mode="r") as f:
config = json.loads(f.read())
play_config = config.get("simple_playthrough")
Player.from_config(
config, game=Board(size=play_config.get("board_size"))
).play_episodes(
play_config.get("episodes"),
display_board=play_config.get("display_board"),
time_interval=play_config.get("time_interval"),
)
| [
"askbk@protonmail.com"
] | askbk@protonmail.com |
4325da0054b8ecb4e522b27b733ba8e35f54ecc8 | 0cb76eb5d69972c6da2b7fe6011d6bd5e694eee4 | /setup.py | 8cc5d30ce029ce325d8ec2e7730928559d145ac3 | [] | no_license | xfenix/django-xflatpages | 990d58e9bd3b536c6f65240ce9c4c6e7344a6ddf | 763f8898100081a9798d6b25324150a5c08f3737 | refs/heads/master | 2020-05-18T00:50:33.529864 | 2014-12-16T23:56:20 | 2014-12-16T23:56:20 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 445 | py | # -*- coding: utf-8 -*-
import os
from setuptools import setup, find_packages
from xflatpages import __version__
# readme
descr = 'Simple flatpages app'
setup(
name='django-xflatpages',
version=__version__,
description=descr,
long_description=descr,
author='Xfenix',
author_email='ad@xfenix.ru',
packages=find_packages(),
include_package_data=True,
install_requires=[
'django-cache-utils',
]
)
| [
"ad@xfenix.ru"
] | ad@xfenix.ru |
26733fb81cb6083b579420deb5cc816fb49e12d9 | c1b1967be7dde14f434703922768f4379334e2f7 | /angr_platforms/msp430/arch_msp430.py | 2b193654051a08c8bd5c73575dc91e00935e1d83 | [
"BSD-2-Clause"
] | permissive | grant-h/angr-platforms | aecd0bcc18be870416f508f3ef4f769ffc9878c7 | b0e4648d3ea00fef5c05e4bd1fa9c59c6c4440bb | refs/heads/master | 2021-07-03T19:43:39.324945 | 2017-09-08T22:43:35 | 2017-09-08T22:43:35 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,037 | py | from archinfo.arch import register_arch, Arch
class ArchMSP430(Arch):
def __init__(self, endness="Iend_LE"):
super(ArchMSP430, self).__init__(endness)
# TODO: Define function prologs
# ip_offset = 136
# sp_offset = 124
# bp_offset = 128
# ret_offset = 16
# lr_offset = 132
# syscall_num_offset = 16
# call_pushes_ret = False
# stack_change = -4
# branch_delay_slot = True
sizeof = {'short': 16, 'int': 16, 'long': 32, 'long long': 64}
function_prologs = {}
function_epilogs = {}
qemu_name = 'msp430'
bits = 16
name = "MSP430"
ida_processor = 'msp430'
max_inst_bytes = 6
ret_instruction = "\x98\x00"
nop_instruction = ""
instruction_alignment = 1
persistent_regs = []
default_register_values = [
( 'sp', Arch.initial_sp, True, 'global' ), # the stack
]
entry_register_values = {
}
default_symbolic_registers = []
class Mode:
REGISTER_MODE = 0
INDEXED_MODE = 1
INDIRECT_REGISTER_MODE = 2
INDIRECT_AUTOINCREMENT_MODE = 3
SYMBOLIC_MODE = 4
ABSOLUTE_MODE = 5
IMMEDIATE_MODE = 6
CONSTANT_MODE0 = 7
CONSTANT_MODE1 = 8
CONSTANT_MODE2 = 9
CONSTANT_MODE4 = 10
CONSTANT_MODE8 = 11
CONSTANT_MODE_NEG1 = 12
OFFSET = 13
register_index = [
'pc',
'sp',
'sr',
'cg',
'r4',
'r5',
'r6',
'r7',
'r8',
'r9',
'r10',
'r11',
'r12',
'r13',
'r14',
'r15'
]
register_names = {
0: 'pc',
2: 'sp',
4: 'sr',
6: 'zero',
8: 'r4',
10: 'r5',
12: 'r6',
14: 'r7',
16: 'r8',
18: 'r9',
20: 'r10',
22: 'r11',
24: 'r12',
26: 'r13',
28: 'r14',
39: 'r15'
}
registers = {
'r0': (0, 2),
'pc': (0, 2),
'ip': (0, 2),
'r1': (2, 2),
'sp': (2, 2),
'r2': (4, 2),
'sr': (4, 2),
'r3': (6, 2),
'zero': (6, 2),
'cg': (6, 2),
'r4': (8, 2),
'r5': (10, 2),
'r6': (12, 2),
'r7': (14, 2),
'r8': (16, 2),
'r9': (18, 2),
'r10': (20, 2),
'r11': (22, 2),
'r12': (24, 2),
'r13': (26, 2),
'r14': (28, 2),
'r15': (30, 2)
}
argument_registers = {
registers['r4'][0],
registers['r5'][0],
registers['r6'][0],
registers['r7'][0],
registers['r8'][0],
registers['r9'][0],
registers['r10'][0],
registers['r11'][0],
registers['r12'][0],
registers['r13'][0],
registers['r14'][0],
registers['r15'][0],
}
# EDG: Can you even use PIC here? I don't think so
dynamic_tag_translation = {}
register_arch([r'msp|msp430|em_msp430'], 32, 'Iend_LE' , ArchMSP430)
| [
"edg@cs.ucsb.edu"
] | edg@cs.ucsb.edu |
6f4f86844af5579493a6f13c1a0dcd95fafe0bd1 | c79e7e691c9fa5cc05bd227209762f735e6263e7 | /pyy1/.pycharm_helpers/python_stubs/-1550516950/apt_pkg/Hashes.py | 92a3d2de462fdebf1fdaf1414141fd87e81bd746 | [
"Apache-2.0"
] | permissive | pyy1988/pyy_test1 | 27fd5fbd41935ba907e26f4f4d2546ca502f29a6 | 6bea878409e658aa87441384419be51aaab061e7 | refs/heads/master | 2020-04-05T07:01:58.745653 | 2018-11-08T12:51:00 | 2018-11-08T12:51:00 | 156,660,893 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,555 | py | # encoding: utf-8
# module apt_pkg
# from /usr/lib/python3/dist-packages/apt_pkg.cpython-35m-x86_64-linux-gnu.so
# by generator 1.145
"""
Classes and functions wrapping the apt-pkg library.
The apt_pkg module provides several classes and functions for accessing
the functionality provided by the apt-pkg library. Typical uses might
include reading APT index files and configuration files and installing
or removing packages.
"""
# no imports
from .object import object
class Hashes(object):
"""
Hashes([object: (bytes, file)])
Calculate hashes for the given object. It can be used to create all
supported hashes for a file.
The parameter 'object' can be a bytestring, an object providing the
fileno() method, or an integer describing a file descriptor.
"""
def __init__(self, *args, **kwargs): # real signature unknown; NOTE: unreliably restored from __doc__
pass
@staticmethod # known case of __new__
def __new__(*args, **kwargs): # real signature unknown
""" Create and return a new object. See help(type) for accurate signature. """
pass
md5 = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
"""The MD5Sum of the file as a string."""
sha1 = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
"""The SHA1Sum of the file as a string."""
sha256 = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
"""The SHA256Sum of the file as a string."""
| [
"347003917@qq.com"
] | 347003917@qq.com |
bae0c8adce6d3a4872acaeed60d8daa4b5c24172 | 3357d08b91a61bbfb653f5506e63aa77caf60868 | /message.py | 9cf75cf1ba3b0fd0cc47c238619a77bfbaa7290e | [] | no_license | saivishwakgangam/error-detection_crc | 2f121553c6381ff790ed2f410e4f95c38d377c52 | 143b50864a741ae6b6a8e47226d632d14c841e48 | refs/heads/main | 2023-03-24T23:06:06.626384 | 2021-03-22T19:00:30 | 2021-03-22T19:00:30 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 207 | py | class Message:
def __init__(self,send_matrix,crc_code):
self.send_matrix=send_matrix
self.crc_code=crc_code
def empty(self):
self.send_matrix=[]
self.crc_code=b'' | [
"noreply@github.com"
] | noreply@github.com |
57b977f2ae53db87282b285aa878effd453face0 | 2a46ad4e83dcd903451fb5fba8d04da266dbd49e | /Algorithm/Leetcode/Codes/ConstructBinaryTreeFromInorderAndPostorderTraversal.py | 769cc7114912f93e7e81cf26965025c23ac1cdbd | [] | no_license | chloeeekim/TIL | e248801508340cb2eb9f3cfddc486b7dd7250386 | c5a94e81aa2f2dfcc626820205ca9feaad069fad | refs/heads/master | 2022-03-02T04:05:24.439271 | 2022-02-22T01:25:14 | 2022-02-22T01:25:14 | 190,150,063 | 8 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,522 | py | """
106. Construct Binary Tree from Inorder and Postorder Traversal : https://leetcode.com/problems/construct-binary-tree-from-inorder-and-postorder-traversal/
어떤 트리의 inorder, postorder traversal 결과가 리스트로 주어졌을 때, 트리를 복원하는 문제
- 트리 내에 중복된 값은 없다고 가정한다
Example:
- Input : inorder = [9,3,15,20,7], postorder = [9,15,7,20,3]
- Output : [3,9,20,null,null,15,7]
Note:
recursive하게 해결
inorder와 preorder로 트리를 복원하는 문제에서 약간만 변형
postorder 리스트의 마지막 값이 root가 되고, inorder 리스트에서 root 값을 기준으로 left children과 right children으로 구분된다
위 조건이 모든 subtree에 대해서도 만족
preorder에서는 left children을 먼저 구하고, right children을 구하는 순서였으나,
postorder에서는 반대로 right children을 먼저 구하고, left children을 구하는 순서
"""
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def buildTree(self, inorder: List[int], postorder: List[int]) -> TreeNode:
if inorder:
rootval = postorder.pop(-1)
root = TreeNode(rootval)
idx = inorder.index(rootval)
root.right = self.buildTree(inorder[idx+1:], postorder)
root.left = self.buildTree(inorder[:idx], postorder)
return root | [
"hiyaku0317@gmail.com"
] | hiyaku0317@gmail.com |
31137672e5dfb8c23d9a8d755c634681497e7e42 | 609bf65158e80d7f11dce7406b1075be83688949 | /trials.py | c9084b4ff11931e66a38e94033f658cded27492e | [] | no_license | jacquetta/js-trials1 | ac4f674b6f650514da5f3d752f13aa5cfede9af7 | 137555766561327fc3aa51e2bd9dc6a719902315 | refs/heads/main | 2023-08-19T06:17:31.200662 | 2021-10-18T21:27:27 | 2021-10-18T21:27:27 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,802 | py | """Python functions for JavaScript Trials 1."""
group = ['item1', 'item2', 'item3']
nums_all = [1, 2, 4, 5, 7, 8,]
def output_all_items(items):
pass
for item in items:
# print(item)
return items
output_all_items(group)
def get_all_evens(nums):
pass
even_nums = []
for num in nums:
if num % 2 == 0:
even_nums.append(num)
# print(even_nums)
return even_nums
get_all_evens([7, 8, 10, 1, 2, 2])
def get_odd_indices(items):
pass # TODO: replace this line with your code
result = []
for i in range(len(items)):
if i % 2 != 0:
result.append(items[i])
# print(result)
return result
get_odd_indices([1, 'hello', True, 500])
def print_as_numbered_list(items):
pass
i = 1
for item in items:
# print(f'{i}. {item}')
i += 1
print_as_numbered_list([1, 'hello', True])
def get_range(start, stop):
pass
nums = []
i = start
for i in range(stop):
nums.append(i)
# print(nums)
get_range(0, 5)
def censor_vowels(word):
pass
chars = []
for letter in word:
if letter in "aeiou":
chars.append("*")
else:
chars.append(letter)
return ''.join(chars)
censor_vowels('hello world')
def snake_to_camel(string):
pass
camel_case = []
word = string.split("_")
print(word)
# camel_case.append(upper(word))
snake_to_camel('hello_world')
def longest_word_length(words):
pass # TODO: replace this line with your code
def truncate(string):
pass # TODO: replace this line with your code
def has_balanced_parens(string):
pass # TODO: replace this line with your code
def compress(string):
pass # TODO: replace this line with your code
| [
"jacquettavb@hotmail.com"
] | jacquettavb@hotmail.com |
cd04b6a0b795d69ec92e5523eb52cd2095f05e08 | 06c9fa55c525a89c48991f699b3b14099fcefd84 | /parallax/parallax/examples/nmt/inference_test.py | 7c342f9f976885e9c242f7cec36a709a949d8aea | [
"Apache-2.0"
] | permissive | snuspl/parallax | ec21997f17b74ed16484d8fe854001c3c0540f51 | 351a913877df3ae03f1b1b52320ee4536b17a667 | refs/heads/master | 2022-03-13T20:40:08.823881 | 2022-02-21T08:12:43 | 2022-02-21T08:12:43 | 142,282,082 | 133 | 33 | Apache-2.0 | 2019-07-09T03:46:02 | 2018-07-25T10:01:57 | Python | UTF-8 | Python | false | false | 8,018 | py | # Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for model inference."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import numpy as np
import tensorflow as tf
from . import attention_model
from . import model_helper
from . import model as nmt_model
from . import gnmt_model
from . import inference
from .utils import common_test_utils
float32 = np.float32
int32 = np.int32
array = np.array
class InferenceTest(tf.test.TestCase):
def _createTestInferCheckpoint(self, hparams, out_dir):
if not hparams.attention:
model_creator = nmt_model.Model
elif hparams.attention_architecture == "standard":
model_creator = attention_model.AttentionModel
elif hparams.attention_architecture in ["gnmt", "gnmt_v2"]:
model_creator = gnmt_model.GNMTModel
else:
raise ValueError("Unknown model architecture")
infer_model = model_helper.create_infer_model(model_creator, hparams)
with self.test_session(graph=infer_model.graph) as sess:
loaded_model, global_step = model_helper.create_or_load_model(
infer_model.model, out_dir, sess, "infer_name")
ckpt = loaded_model.saver.save(
sess, os.path.join(out_dir, "translate.ckpt"),
global_step=global_step)
return ckpt
def testBasicModel(self):
hparams = common_test_utils.create_test_hparams(
encoder_type="uni",
num_layers=1,
attention="",
attention_architecture="",
use_residual=False,)
vocab_prefix = "nmt/testdata/test_infer_vocab"
hparams.src_vocab_file = vocab_prefix + "." + hparams.src
hparams.tgt_vocab_file = vocab_prefix + "." + hparams.tgt
infer_file = "nmt/testdata/test_infer_file"
out_dir = os.path.join(tf.test.get_temp_dir(), "basic_infer")
hparams.out_dir = out_dir
os.makedirs(out_dir)
output_infer = os.path.join(out_dir, "output_infer")
ckpt = self._createTestInferCheckpoint(hparams, out_dir)
inference.inference(ckpt, infer_file, output_infer, hparams)
with open(output_infer) as f:
self.assertEqual(5, len(list(f)))
def testBasicModelWithMultipleTranslations(self):
hparams = common_test_utils.create_test_hparams(
encoder_type="uni",
num_layers=1,
attention="",
attention_architecture="",
use_residual=False,
num_translations_per_input=2,
beam_width=2,
)
vocab_prefix = "nmt/testdata/test_infer_vocab"
hparams.src_vocab_file = vocab_prefix + "." + hparams.src
hparams.tgt_vocab_file = vocab_prefix + "." + hparams.tgt
infer_file = "nmt/testdata/test_infer_file"
out_dir = os.path.join(tf.test.get_temp_dir(), "multi_basic_infer")
hparams.out_dir = out_dir
os.makedirs(out_dir)
output_infer = os.path.join(out_dir, "output_infer")
ckpt = self._createTestInferCheckpoint(hparams, out_dir)
inference.inference(ckpt, infer_file, output_infer, hparams)
with open(output_infer) as f:
self.assertEqual(10, len(list(f)))
def testAttentionModel(self):
hparams = common_test_utils.create_test_hparams(
encoder_type="uni",
num_layers=1,
attention="scaled_luong",
attention_architecture="standard",
use_residual=False,)
vocab_prefix = "nmt/testdata/test_infer_vocab"
hparams.src_vocab_file = vocab_prefix + "." + hparams.src
hparams.tgt_vocab_file = vocab_prefix + "." + hparams.tgt
infer_file = "nmt/testdata/test_infer_file"
out_dir = os.path.join(tf.test.get_temp_dir(), "attention_infer")
hparams.out_dir = out_dir
os.makedirs(out_dir)
output_infer = os.path.join(out_dir, "output_infer")
ckpt = self._createTestInferCheckpoint(hparams, out_dir)
inference.inference(ckpt, infer_file, output_infer, hparams)
with open(output_infer) as f:
self.assertEqual(5, len(list(f)))
def testMultiWorkers(self):
hparams = common_test_utils.create_test_hparams(
encoder_type="uni",
num_layers=2,
attention="scaled_luong",
attention_architecture="standard",
use_residual=False,)
vocab_prefix = "nmt/testdata/test_infer_vocab"
hparams.src_vocab_file = vocab_prefix + "." + hparams.src
hparams.tgt_vocab_file = vocab_prefix + "." + hparams.tgt
infer_file = "nmt/testdata/test_infer_file"
out_dir = os.path.join(tf.test.get_temp_dir(), "multi_worker_infer")
hparams.out_dir = out_dir
os.makedirs(out_dir)
output_infer = os.path.join(out_dir, "output_infer")
num_workers = 3
# There are 5 examples, make batch_size=3 makes job0 has 3 examples, job1
# has 2 examples, and job2 has 0 example. This helps testing some edge
# cases.
hparams.batch_size = 3
ckpt = self._createTestInferCheckpoint(hparams, out_dir)
inference.inference(
ckpt, infer_file, output_infer, hparams, num_workers, jobid=1)
inference.inference(
ckpt, infer_file, output_infer, hparams, num_workers, jobid=2)
# Note: Need to start job 0 at the end; otherwise, it will block the testing
# thread.
inference.inference(
ckpt, infer_file, output_infer, hparams, num_workers, jobid=0)
with open(output_infer) as f:
self.assertEqual(5, len(list(f)))
def testBasicModelWithInferIndices(self):
hparams = common_test_utils.create_test_hparams(
encoder_type="uni",
num_layers=1,
attention="",
attention_architecture="",
use_residual=False,
inference_indices=[0])
vocab_prefix = "nmt/testdata/test_infer_vocab"
hparams.src_vocab_file = vocab_prefix + "." + hparams.src
hparams.tgt_vocab_file = vocab_prefix + "." + hparams.tgt
infer_file = "nmt/testdata/test_infer_file"
out_dir = os.path.join(tf.test.get_temp_dir(), "basic_infer_with_indices")
hparams.out_dir = out_dir
os.makedirs(out_dir)
output_infer = os.path.join(out_dir, "output_infer")
ckpt = self._createTestInferCheckpoint(hparams, out_dir)
inference.inference(ckpt, infer_file, output_infer, hparams)
with open(output_infer) as f:
self.assertEqual(1, len(list(f)))
def testAttentionModelWithInferIndices(self):
hparams = common_test_utils.create_test_hparams(
encoder_type="uni",
num_layers=1,
attention="scaled_luong",
attention_architecture="standard",
use_residual=False,
inference_indices=[1, 2])
# TODO(rzhao): Make infer indices support batch_size > 1.
hparams.infer_batch_size = 1
vocab_prefix = "nmt/testdata/test_infer_vocab"
hparams.src_vocab_file = vocab_prefix + "." + hparams.src
hparams.tgt_vocab_file = vocab_prefix + "." + hparams.tgt
infer_file = "nmt/testdata/test_infer_file"
out_dir = os.path.join(tf.test.get_temp_dir(),
"attention_infer_with_indices")
hparams.out_dir = out_dir
os.makedirs(out_dir)
output_infer = os.path.join(out_dir, "output_infer")
ckpt = self._createTestInferCheckpoint(hparams, out_dir)
inference.inference(ckpt, infer_file, output_infer, hparams)
with open(output_infer) as f:
self.assertEqual(2, len(list(f)))
self.assertTrue(os.path.exists(output_infer+str(1)+".png"))
self.assertTrue(os.path.exists(output_infer+str(2)+".png"))
if __name__ == "__main__":
tf.test.main()
| [
"pigbug419@gmail.com"
] | pigbug419@gmail.com |
892e33c12c641e469991e444dcd7b42bcc2337f4 | 3f77f05c6a664555d5a99896597ebb447be3fbe4 | /src/main/python/gui.py | 482411caa50ef232aa15c4b256af23addc0f240d | [] | no_license | JettChenT/echat-client | 9d090462580191c250a619739e5a21442b0e8094 | b1f33a30e38421832e63e3c1e3c6e0e1dc32ce1f | refs/heads/master | 2023-03-01T09:00:44.364691 | 2021-02-01T02:56:46 | 2021-02-01T02:56:46 | 334,071,457 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 13,201 | py | from executer import Executer
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from threading import Thread
from time import sleep
import json
from passwordStrength import PasswordStrengthChecker
import sys
import faulthandler
import atexit
from fbs_runtime.application_context.PyQt5 import ApplicationContext
faulthandler.enable()
class LoginForm(QWidget):
def __init__(self, server_exec):
super(LoginForm,self).__init__()
self.pwc = PasswordStrengthChecker(strict=False)
self.setWindowFlags(Qt.WindowStaysOnTopHint)
self.setFocusPolicy(Qt.StrongFocus)
self.activateWindow()
self.server_exec = server_exec
self.setStyleSheet(open("style.qss", "r").read())
self.title = "Login/Register"
self.layout = QGridLayout()
# Reused widgets
label_login_name = QLabel("<font size='4'> Username </font>")
self.username = QLineEdit()
self.username.setPlaceholderText("Please enter your username")
self.layout.addWidget(label_login_name, 0, 0)
self.layout.addWidget(self.username, 0, 1)
label_login_password = QLabel("<font size='4'> Password </font>")
self.password = QLineEdit()
self.password.setPlaceholderText('Please enter your password')
self.layout.addWidget(label_login_password, 1, 0)
self.layout.addWidget(self.password, 1, 1)
# tab 1
button_login = QPushButton('login')
button_login.pressed.connect(self.login)
button_register = QPushButton('register')
button_register.pressed.connect(self.register)
self.layout.addWidget(button_login,2,1)
self.layout.addWidget(button_register,2,0)
self.setLayout(self.layout)
def login(self):
while True:
r = self.server_exec.exec_(f"login {self.username.text()} {self.password.text()}")
if r == False:
continue
msg = QMessageBox(self)
msg.setText(r)
if r == "You're logged in!":
msg.setIcon(QMessageBox.Information)
msg.exec_()
self.close()
else:
msg.setIcon(QMessageBox.Critical)
msg.exec_()
break
def register(self):
is_secure, rsp = self.pwc.is_secure(self.password.text())
if is_secure:
r = self.server_exec.exec_(f"reg {self.username.text()} {self.password.text()}")
msg = QMessageBox(self)
msg.setText(r)
msg.exec_()
else:
msg = QMessageBox(self)
msg.setIcon(QMessageBox.Critical)
msg.setText(rsp)
msg.exec_()
class ChatWindow(QWidget):
def __init__(self, server_exec):
super(ChatWindow, self).__init__()
self.server_exec = server_exec
self.last_sender = ""
self.setWindowTitle("EncryptiiChat")
self.setMinimumWidth(600)
self.setMinimumHeight(500)
self.loginWindow = LoginForm(self.server_exec)
self.loginWindow.show()
self.MQ = []
self.text_area = QTextEdit(self)
self.text_area.setFocusPolicy(Qt.NoFocus)
self.text_area.setReadOnly(True)
self.text_area.setAcceptRichText(True)
self.text_area.setAutoFormatting(QTextEdit.AutoAll)
self.message = QLineEdit(self)
self.message.setPlaceholderText("Enter your message")
self.layout = QGridLayout(self)
self.layout.addWidget(self.text_area,0,0,1,3)
self.to_user = QComboBox(self)
self.match_button = QPushButton("Match")
self.match_button.pressed.connect(self.match)
self.layout.addWidget(self.to_user,2,0)
self.layout.addWidget(self.match_button,2,1)
self.layout.addWidget(self.message,2,2)
self.colors_layout = QHBoxLayout(self)
self.yellow_button = QPushButton("")
self.yellow_button.setStyleSheet("background-color:#FFCD48")
self.orange_button = QPushButton("")
self.orange_button.setStyleSheet("background-color:#F28437")
self.red_button = QPushButton("")
self.red_button.setStyleSheet("background-color:#DE4557")
self.purple_button = QPushButton("")
self.purple_button.setStyleSheet("background-color:#B940E5")
self.blue_button = QPushButton("")
self.blue_button.setStyleSheet("background-color:#55A5FD")
self.light_blue_button = QPushButton("")
self.light_blue_button.setStyleSheet("background-color:#1AD3FB")
self.green_button = QPushButton("")
self.green_button.setStyleSheet("background-color:#A4DB47")
self.colors_layout.addWidget(self.yellow_button)
self.colors_layout.addWidget(self.orange_button)
self.colors_layout.addWidget(self.red_button)
self.colors_layout.addWidget(self.purple_button)
self.colors_layout.addWidget(self.blue_button)
self.colors_layout.addWidget(self.light_blue_button)
self.colors_layout.addWidget(self.green_button)
self.init_colors()
self.layout.addLayout(self.colors_layout,1,0,1,3)
self.layout.setColumnStretch(2,4)
self.layout.setColumnStretch(1,1)
self.layout.setColumnStretch(0,2)
self.setLayout(self.layout)
self.message.returnPressed.connect(self.send_message_thread)
self.thread = Thread(target=self.fetch_new_messages, daemon=True)
self.thread.start()
def init_colors(self):
with open("colorsconfig.json","r") as f:
color_data = json.load(f)
self.yellow_button.setText(color_data["yellow"]["about"])
self.yellow_button.pressed.connect(lambda:self.send_color_thread("yellow"))
self.orange_button.setText(color_data["orange"]["about"])
self.orange_button.pressed.connect(lambda:self.send_color_thread("orange"))
self.red_button.setText(color_data["red"]["about"])
self.red_button.pressed.connect(lambda:self.send_color_thread("red"))
self.blue_button.setText(color_data["blue"]["about"])
self.blue_button.pressed.connect(lambda:self.send_color_thread("blue"))
self.light_blue_button.setText(color_data["light-blue"]["about"])
self.light_blue_button.pressed.connect(lambda:self.send_color_thread("light-blue"))
self.green_button.setText(color_data["green"]["about"])
self.green_button.pressed.connect(lambda:self.send_color_thread("green"))
self.purple_button.setText(color_data["purple"]["about"])
self.purple_button.pressed.connect(lambda:self.send_color_thread("purple"))
self.color_data = color_data
self.orig_color_data = color_data
def send_message_thread(self):
if self.server_exec.not_logged_in():
print("log in first!")
self.not_logged_in_popup()
self.loginWindow.show()
return
if self.to_user.count() == 0:
self.not_matched_popup()
return
sendThread = Thread(target=self.send_message)
sendThread.start()
def match(self):
while True:
res = self.server_exec.exec_("match")
if res!= False:
target_alias, my_alias = res
break
self.to_user.addItem(target_alias)
index = self.to_user.findText(target_alias,Qt.MatchFixedString)
self.to_user.setCurrentIndex(index)
def get_mg(self,color):
return f"{self.color_data[color]['details']}"
def suggest(self,msg):
msg = msg.lower()
for rsp in self.color_data['responses']:
if rsp in msg:
self.color_data['yellow']['details'] = self.color_data['responses'][rsp]['details']
self.yellow_button.setText(self.color_data['responses'][rsp]['about'])
return self.color_data['responses'][rsp]
return False
def send_color_thread(self,color):
if self.server_exec.not_logged_in():
print("log in first!")
self.not_logged_in_popup()
self.loginWindow.show()
return
if self.to_user.count() == 0:
self.not_matched_popup()
return
sendThread = Thread(target=self.send_color(color))
sendThread.start()
def send_color(self,color):
html_resp = f"<span style=\"color:#ffffff\">[to <i>{self.to_user.currentText()}</i>]:{self.get_mg(color)}</span>"
tc = self.text_area.textCursor()
form = tc.charFormat()
form.setForeground(Qt.green)
tc.setCharFormat(form)
tc.insertHtml(html_resp)
self.text_area.append("")
self.message.clear()
while True:
r = self.server_exec.exec_(f"send {self.to_user.currentText()} {self.get_mg(color)}")
if not r:
continue
print(f"{self.server_exec.username}:sent!")
sleep(0.1)
break
def send_message(self):
html_resp = f"<span style=\"color:#ffffff\">[to <i>{self.to_user.currentText()}</i>]:{self.message.text()}</span>"
tc = self.text_area.textCursor()
form = tc.charFormat()
form.setForeground(Qt.green)
tc.setCharFormat(form)
tc.insertHtml(html_resp)
self.text_area.append("")
send_msg = self.message.text()
self.message.clear()
self.message.setPlaceholderText("Sending...")
self.message.setFocusPolicy(Qt.NoFocus)
while True:
r = self.server_exec.exec_(f"send {self.to_user.currentText()} {send_msg}")
if r == False:
continue
self.message.setPlaceholderText("Enter your message")
self.message.setFocusPolicy(Qt.ClickFocus)
print(f"{self.server_exec.username}:sent:{send_msg}")
sleep(0.1)
break
def not_logged_in_popup(self):
msg = QMessageBox(self)
msg.setWindowTitle("Not logged in!")
msg.setText("Please log in to send a message")
msg.setIcon(QMessageBox.Critical)
x = msg.exec_()
def not_matched_popup(self):
msg = QMessageBox(self)
msg.setWindowTitle("Matched")
msg.setText("Please hit the match button to match with someone")
msg.setIcon(QMessageBox.Critical)
x = msg.exec_()
def get_cur_sender(self,msg):
for i in range(len(msg)):
if msg[i:i+1] == ']':
un = msg[1:i].split(":")[0]
mg = msg[i+2:]
break
return un, mg
def display_new_messages(self):
while len(self.MQ):
new_msg = self.MQ.pop(0)
self.cur_sender,cur_msg = self.get_cur_sender(new_msg)
index = self.to_user.findText(self.cur_sender)
if index == -1:
self.to_user.addItem(self.cur_sender)
new_index = self.to_user.findText(self.cur_sender)
self.to_user.setCurrentIndex(new_index)
if self.last_sender != self.cur_sender:
print(self.cur_sender)
self.text_area.textCursor().insertHtml(f"<h3 style=\"color:#ffff00\">sender: {self.cur_sender}</h3>")
self.text_area.append("")
self.text_area.textCursor().insertHtml(f"<span style=\"color:#ffffff\">{cur_msg}</span>")
self.suggest(cur_msg)
self.text_area.append("")
self.last_sender = self.cur_sender
def fetch_new_messages(self):
while True:
if self.server_exec.not_logged_in():
sleep(0.5)
continue
try:
new_message = self.server_exec.exec_("getMsg")
if type(new_message) == list:
for msg in new_message:
decoded_msg = msg.decode()
print(decoded_msg)
self.MQ.append(decoded_msg)
sleep(0.5)
except:
continue
class MainWindow(QMainWindow):
def __init__(self):
super(MainWindow, self).__init__()
self.setWindowTitle("Chat application")
with open("config.json") as f:
cfg = json.load(f)
server = cfg['server']
port = int(cfg['port'])
print(server,port)
self.server_exec = Executer((server, port))
atexit.register(self.server_exec.on_exit)
self.setStyleSheet(open("style.qss", "r").read())
self.mainWidget = ChatWindow(self.server_exec)
self.setCentralWidget(self.mainWidget)
def closeEvent(self, event):
print("close")
while True:
try:
rsp = self.server_exec.exec_("offline")
if rsp!=False:
print(rsp)
break
except:
continue
def window():
appctxt = ApplicationContext()
app = QApplication(sys.argv)
win = MainWindow()
win.show()
timer = QTimer()
timer.timeout.connect(win.mainWidget.display_new_messages)
timer.start(1000)
app.exec_()
exit_code = appctxt.app.exec_()
window()
| [
"jettchen12345@gmail.com"
] | jettchen12345@gmail.com |
2b880886119cd49ba10dd9ed027ea26772f13106 | b1fe732c6abb51d44bd965cbbf259bb2d93e4514 | /Day3/problemSet.py | 14560c6d9c0b5f77cfebb8b4be2faea25056a2f5 | [] | no_license | RahulSinghDhek/GettingStartedWithPython | 04c85c2c370e7ea93b16dade44e5eea633ec284c | c655e3376707b8e4e14ed352a8bc07b010c31e12 | refs/heads/master | 2020-05-07T17:15:38.120491 | 2019-04-11T05:39:12 | 2019-04-11T05:39:12 | 180,721,799 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 126 | py | __author__ = 'rdhek'
a=[1,3,5,7]
b=[1,2,3,4,5]
x= set(a)
y= set(b)
print list(x.intersection(y))
print x.union(y)
print x-y | [
"rdhek@qti.qualcomm.com"
] | rdhek@qti.qualcomm.com |
7379c533b289f68343bc5cd1947b5877f809fbb7 | 044bb022c77c34a92492b800fc380bdead99be52 | /Python-Codes/Test Codes/test.py | 1c94df5885c60c7434578cc3e599d8a737f2b6c3 | [] | no_license | sswisty/ROV-SIREN | 4c7190d2f45685d87ef3b601b286a647055b9c7b | 5f949d6c139eb44b636e34ba1373c397472b23d0 | refs/heads/master | 2020-04-06T07:04:16.101218 | 2016-10-05T20:44:43 | 2016-10-05T20:44:43 | 51,488,996 | 1 | 2 | null | null | null | null | UTF-8 | Python | false | false | 60 | py | # Adding this file to create a new folder
x = 5
print x+3
| [
"sswisty7@gmail.com"
] | sswisty7@gmail.com |
165146e30d5f3fdf5a47e708760346f1f979c67f | 1c0d4b9c57e3eb987cba4ba082e855b4444797a2 | /fresh_launch.py | 8ccf5cb88927ed18aed2cb80a0df5d7664992c7d | [
"MIT"
] | permissive | prasad223/CSE586 | 4b70e5aefc2254d89c343f1d0217210cbbf65ed1 | dfd3bbaa8e1732cb1ae6909cc7e75cc84a912b01 | refs/heads/master | 2021-01-21T03:21:04.699400 | 2016-05-05T12:57:19 | 2016-05-05T12:57:19 | 54,043,773 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 694 | py | #!/usr/bin/env python
import os
from environment import *
apk_path = os.path.join(WORKSPACE, PROJECT_NAME, 'app', 'build', 'outputs', 'apk', 'app-debug.apk')
app_package = PREFIX + '.' + PROJECT_EXT
for i in 5554, 5556, 5558, 5560, 5562:
print "Fresh launch on emulator", i
emu = "emulator-" + str(i)
cmd = 'adb -s ' + emu
#uninstall
full_cmd = cmd + ' uninstall ' + app_package
os.system(full_cmd)
#install
full_cmd = cmd + ' install ' + apk_path
os.system(full_cmd)
#unlock
full_cmd = cmd + ' shell input keyevent 82'
os.system(full_cmd)
#launch
full_cmd = cmd + ' shell am start -n ' + app_package + '/' + app_package + '.' + MAIN_ACTIVITY
os.system(full_cmd)
| [
"prasadsjcecs@gmail.com"
] | prasadsjcecs@gmail.com |
796dd3e7354d66e1ca0d2af453460dcea123a126 | 7f5980bcd5bd0d9e049295e7cbf1c38df04fb36d | /deprecated/Automations.py | 406838933ffbcf450754338c42de2199d32c73f7 | [] | no_license | menahishayan/Automated-Oven | 0d91f0e2b47b3656ec2822fe522ebdfcbeaa09e5 | 51470c6fceff57903f232422c342409b72d01c49 | refs/heads/main | 2023-05-31T12:17:58.785205 | 2021-07-04T13:31:36 | 2021-07-04T13:31:36 | 361,813,332 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 122 | py | import json
class Automations:
def __init__(self, dbPath='./db/AutomationsDB.json'):
self.path = dbPath
| [
"shayan1232001@yahoo.co.in"
] | shayan1232001@yahoo.co.in |
9816169c3cf62624bac7d4238f5e8c78629beb72 | 2816fe989f78240e950554b4b1fe680ec62b306a | /crawl/guba/multi.py | c333873535ef956172a687984e6e7b72f7986e17 | [] | no_license | stop1992/python-security | fb4219e4769459e07e51227ba3d47d0c9a88ee98 | b022e73f1f105179136360601c4f5122e9bc4875 | refs/heads/master | 2021-01-20T05:59:47.264360 | 2016-08-02T13:59:46 | 2016-08-02T13:59:46 | 65,118,931 | 4 | 2 | null | 2016-08-07T06:18:41 | 2016-08-07T06:18:41 | null | UTF-8 | Python | false | false | 4,298 | py | #!/usr/bin/env python
# encoding: utf-8
import multiprocessing
import os
from pymongo import MongoClient
from redis import Redis
import re
import time
from clear import drop_mongo
# process_nums = multiprocessing.cpu_count()
MONGO_SERVER = '192.168.1.108'
MONGO_PORT = 27017
MONGO_DB_IN = 'guba_data'
MONGO_DB_OUT = 'guba'
REDIS_SERVER = '192.168.1.108'
REDIS_PORT = 6379
# process_nums = cpus - 1
process_nums = multiprocessing.cpu_count()
redis_client = Redis(REDIS_SERVER, REDIS_PORT)
mongo_client = MongoClient(MONGO_SERVER, MONGO_PORT)
mongo_db_in = mongo_client[MONGO_DB_IN]
mongo_db_out = mongo_client[MONGO_DB_OUT]
# strip, then unicode, then compile
key_words = [ re.compile(unicode(key.strip(), 'utf-8')) for key in open('keywords.txt', 'r').readlines() ]
redis_client.sadd('stocks', '000002')
redis_client.sadd('stocks', '000866')
def add(x, y):
return x + y
def store2mongo(stock_num, ask_time, key_words_accouts):
post = mongo_db_out[stock_num]
# first get key words, then plus them ,then store
all_document = post.find_one({'ask_time':ask_time})
# exist ask_time data
if all_document:
key_words_accouts_before = all_document['key_words']
post_times = all_document['post_times']
# compute every day key words occur times
key_words_accouts_after = map(add, key_words_accouts, key_words_accouts_before)
# find key words, then update
post.update_one({'ask_time':ask_time}, {'$set':{'key_words':key_words_accouts_after, \
'post_times':post_times+1}})
else: # not exist ask_time data
post.insert({'ask_time':ask_time, 'post_times':1, 'key_words':key_words_accouts})
# print stock_num, ask_time, ' data process successfully....'
def handle_data(stock_num):
# stock num represent a collection
table = mongo_db_in[stock_num]
if table:
# print 'start to process data....'
for post_day in table.find():
# get post ask time
ask_time = post_day['ask_time']
# store key words occur times
key_words_accouts = []
# this day present occur 1 time
replys_data = post_day['replys_data']
for pattern in key_words:
# initial find_count is 0
key_find_count = 0
for text in replys_data:
result = pattern.findall(text)
if result:
key_find_count = len(result)
key_words_accouts.append(key_find_count)
# store2mongo(stock_num, ask_time, key_words_accouts)
post = mongo_db_out[stock_num]
# first get key words, then plus them ,then store
all_document = post.find_one({'ask_time':ask_time})
# exist ask_time data
if all_document:
key_words_accouts_before = all_document['key_words']
post_times = all_document['post_times']
# compute every day key words occur times
key_words_accouts_after = map(add, key_words_accouts, key_words_accouts_before)
# find key words, then update
post.update_one({'ask_time':ask_time}, {'$set':{'key_words':key_words_accouts_after, \
'post_times':post_times+1}})
else: # not exist ask_time data
post.insert({'ask_time':ask_time, 'post_times':1, 'key_words':key_words_accouts})
def handle(process_name):
while redis_client.scard('stocks') > 0:
# use a set to store stock nums
stock_num = redis_client.spop('stocks')
if stock_num:
stock_num = 'db' + stock_num
handle_data(stock_num)
def main():
jobs = []
pools = multiprocessing.Pool()
for i in xrange(process_nums - 1):
process_name = 'process_' + str(i)
pools.apply_async(handle, (process_name, ))
pools.close()
pools.join()
if __name__ == '__main__':
os.system('printf "\033c"')
start = time.time()
print 'start time: ', start
main()
end = time.time()
print 'used time: ', end - start
# drop_mongo()
# test()
| [
"daitaomail@gmail.com"
] | daitaomail@gmail.com |
fdba2e38a7275b27bf739668f77984e9aad554b6 | d5fd936e7346844a1b7c5ea81dfa9adf5bb647d0 | /datasets/load_data.py | c547ebd91f699327cac78ca35d0dbe0f0094489e | [] | no_license | isaachenrion/graphs | 098e7098a894a3d1d9d18cf0ce1054e5910afa15 | 2ba6d50a7f61233fa8cc92ba03256691abb889de | refs/heads/master | 2021-01-02T09:10:49.686240 | 2017-09-11T19:52:48 | 2017-09-11T19:52:48 | 99,154,954 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,013 | py | import os
import pickle
from .datasets import BatchedFixedOrderGraphDataset, FixedOrderGraphDataset, GraphDataset, BatchedGraphDataset
from .add_virtual_node import add_virtual_node, add_target_nodes
from .path import DATA_DIR
def load_from_path(data_path, args):
with open(data_path, 'rb') as f:
dataset = pickle.load(f)
if isinstance(dataset, FixedOrderGraphDataset):
dataset = BatchedFixedOrderGraphDataset(dataset, args.batch_size)
elif isinstance(dataset, GraphDataset):
dataset = BatchedGraphDataset(dataset, args.batch_size)
if args.model == 'vcn':
add_target_nodes(dataset)
dataset = dataset.preprocess()
return dataset
def load_data(args):
train_data_path = os.path.join(DATA_DIR, args.problem + '-train.pkl')
eval_data_path = os.path.join(DATA_DIR, args.problem + '-eval.pkl')
training_set = load_from_path(train_data_path, args)
validation_set = load_from_path(eval_data_path, args)
return training_set, validation_set
| [
"isaachenrion@gmail.com"
] | isaachenrion@gmail.com |
8e990b308f624c1525603f9ab92945fda7fb8ce2 | 5167f77d96d1dc5412a8a0a91c95e3086acd05dc | /test/functional/wallet_implicitsegwit.py | 553ce7367502b4851bea035523dbb7026ed2072f | [
"MIT"
] | permissive | ocvcoin/ocvcoin | 04fb0cea7c11bf52e07ea06ddf9df89631eced5f | 79c3803e330f32ed50c02ae657ff9aded6297b9d | refs/heads/master | 2023-04-30T10:42:05.457630 | 2023-04-15T11:49:40 | 2023-04-15T11:49:40 | 406,011,904 | 3 | 2 | null | null | null | null | UTF-8 | Python | false | false | 2,424 | py | #!/usr/bin/env python3
# Copyright (c) 2019 The Ocvcoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Test the wallet implicit segwit feature."""
import test_framework.address as address
from test_framework.test_framework import OcvcoinTestFramework
# TODO: Might be nice to test p2pk here too
address_types = ('legacy', 'bech32', 'p2sh-segwit')
def key_to_address(key, address_type):
if address_type == 'legacy':
return address.key_to_p2pkh(key)
elif address_type == 'p2sh-segwit':
return address.key_to_p2sh_p2wpkh(key)
elif address_type == 'bech32':
return address.key_to_p2wpkh(key)
def send_a_to_b(receive_node, send_node):
keys = {}
for a in address_types:
a_address = receive_node.getnewaddress(address_type=a)
pubkey = receive_node.getaddressinfo(a_address)['pubkey']
keys[a] = pubkey
for b in address_types:
b_address = key_to_address(pubkey, b)
send_node.sendtoaddress(address=b_address, amount=1)
return keys
def check_implicit_transactions(implicit_keys, implicit_node):
# The implicit segwit node allows conversion all possible ways
txs = implicit_node.listtransactions(None, 99999)
for a in address_types:
pubkey = implicit_keys[a]
for b in address_types:
b_address = key_to_address(pubkey, b)
assert(('receive', b_address) in tuple((tx['category'], tx['address']) for tx in txs))
class ImplicitSegwitTest(OcvcoinTestFramework):
def set_test_params(self):
self.num_nodes = 2
self.supports_cli = False
def skip_test_if_missing_module(self):
self.skip_if_no_wallet()
def run_test(self):
self.log.info("Manipulating addresses and sending transactions to all variations")
implicit_keys = send_a_to_b(self.nodes[0], self.nodes[1])
self.sync_all()
self.log.info("Checking that transactions show up correctly without a restart")
check_implicit_transactions(implicit_keys, self.nodes[0])
self.log.info("Checking that transactions still show up correctly after a restart")
self.restart_node(0)
self.restart_node(1)
check_implicit_transactions(implicit_keys, self.nodes[0])
if __name__ == '__main__':
ImplicitSegwitTest().main()
| [
"contact@ocvcoin.com"
] | contact@ocvcoin.com |
7abdb85b4f5ecf93d8696b1a86d6ce317207a57e | f71415d51b9257e4cf6562a6b3c5e7596ff76daf | /mysite/settings.py | 4b6dea8414c93ebdf4cd133733447271f0478692 | [] | no_license | myromeu/fantastic-fiesta | effabb2df4dc8db7c674142038ef6ddb6bc82270 | 46ca55d3ff03563f2786ac5b913e2f25b13cdb68 | refs/heads/master | 2021-01-10T06:56:33.130626 | 2016-01-26T20:52:46 | 2016-01-26T20:52:46 | 49,889,440 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,706 | py | """
Django settings for mysite project.
Generated by 'django-admin startproject' using Django 1.8.
For more information on this file, see
https://docs.djangoproject.com/en/1.8/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.8/ref/settings/
"""
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
import os
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/1.8/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '=-5@mq*a%x1e4e#+6nu+box+fh!3ao@jw6g=j0!xkc60w)^u_p'
# 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',
'blog',
)
MIDDLEWARE_CLASSES = (
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.auth.middleware.SessionAuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'django.middleware.security.SecurityMiddleware',
)
ROOT_URLCONF = 'mysite.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 = 'mysite.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.8/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Internationalization
# https://docs.djangoproject.com/en/1.8/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'Europe/Moscow'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.8/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, 'static')
| [
"myromeu@ya.ru"
] | myromeu@ya.ru |
955b93a0198bf45f36553fa170bdc6effb0bec4b | 765b558714acf20438ff717e57beadd9890fe1be | /galcon/galcon/migrations/0012_auto__del_group.py | deba6a67510de5e53a6da62f87851a001cc0d21d | [] | no_license | marky1991/galcon_clone | 279cf4ec6adb266f5afabc0a0a61435a52a60119 | 12923b001d593c75934e99ed201627d8767462c2 | refs/heads/master | 2020-06-06T20:24:03.684856 | 2013-09-06T15:52:45 | 2013-09-06T15:52:45 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 14,810 | py | # -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Deleting model 'Group'
db.delete_table('galcon_group')
# Removing M2M table for field admins on 'Group'
db.delete_table(db.shorten_name('galcon_group_admins'))
def backwards(self, orm):
# Adding model 'Group'
db.create_table('galcon_group', (
('description', self.gf('django.db.models.fields.TextField')(max_length=65000)),
('join_requires_approval', self.gf('django.db.models.fields.BooleanField')(default=False)),
('hidden', self.gf('django.db.models.fields.BooleanField')(default=False)),
('creation_time', self.gf('django.db.models.fields.DateTimeField')(default=datetime.datetime.now, blank=True)),
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('slug', self.gf('django.db.models.fields.SlugField')(max_length=100, blank=True)),
('name', self.gf('django.db.models.fields.CharField')(max_length=25)),
))
db.send_create_signal('galcon', ['Group'])
# Adding M2M table for field admins on 'Group'
m2m_table_name = db.shorten_name('galcon_group_admins')
db.create_table(m2m_table_name, (
('id', models.AutoField(verbose_name='ID', primary_key=True, auto_created=True)),
('group', models.ForeignKey(orm['galcon.group'], null=False)),
('player', models.ForeignKey(orm['galcon.player'], null=False))
))
db.create_unique(m2m_table_name, ['group_id', 'player_id'])
models = {
'auth.group': {
'Meta': {'object_name': 'Group'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'})
},
'auth.permission': {
'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'},
'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
'auth.user': {
'Meta': {'object_name': 'User'},
'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}),
'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}),
'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'})
},
'contenttypes.contenttype': {
'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"},
'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'})
},
'galcon.friend_request': {
'Meta': {'object_name': 'Friend_Request'},
'accepted': ('django.db.models.fields.NullBooleanField', [], {'null': 'True', 'blank': 'True'}),
'author': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'sent_friend_requests'", 'to': "orm['galcon.Player']"}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'recipient': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'friend_requests'", 'to': "orm['galcon.Player']"})
},
'galcon.join_group_request': {
'Meta': {'object_name': 'Join_Group_Request'},
'accepted': ('django.db.models.fields.NullBooleanField', [], {'null': 'True', 'blank': 'True'}),
'author': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'sent_join_group_requests'", 'to': "orm['galcon.Player']"}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'recipient': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'join_group_requests'", 'to': "orm['galcon.Player']"})
},
'galcon.note': {
'Meta': {'object_name': 'Note'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'text': ('django.db.models.fields.TextField', [], {'max_length': '100'})
},
'galcon.player': {
'Meta': {'object_name': 'Player'},
'avatar': ('django.db.models.fields.files.ImageField', [], {'max_length': '100', 'blank': 'True'}),
'friends': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'friends_rel_+'", 'blank': 'True', 'to': "orm['galcon.Player']"}),
'get_newsletter': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'groups': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'related_name': "'groups'", 'blank': 'True', 'to': "orm['groups.Group']"}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'location': ('django.db.models.fields.CharField', [], {'max_length': '50', 'blank': 'True'}),
'post_count': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}),
'rank': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['galcon.Rank']", 'unique': 'True'}),
'registration_code': ('django.db.models.fields.CharField', [], {'max_length': '16', 'blank': 'True'}),
'registration_email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}),
'slug': ('django.db.models.fields.SlugField', [], {'default': "''", 'max_length': '100'}),
'trophies': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'related_name': "'players'", 'blank': 'True', 'to': "orm['galcon.Trophy']"}),
'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True'})
},
'galcon.pm': {
'Meta': {'object_name': 'Pm'},
'author': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'written_messages'", 'to': "orm['galcon.Player']"}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'post_date': ('django.db.models.fields.DateTimeField', [], {}),
'read': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'recipient': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'recieved_messages'", 'to': "orm['galcon.Player']"}),
'sent': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'slug': ('django.db.models.fields.SlugField', [], {'max_length': '100'}),
'starred': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'text': ('django.db.models.fields.TextField', [], {'max_length': '65000'}),
'title': ('django.db.models.fields.CharField', [], {'default': "'(Blank)'", 'max_length': '100'})
},
'galcon.post': {
'Meta': {'object_name': 'Post'},
'author': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'posts'", 'to': "orm['galcon.Player']"}),
'flag_note': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['galcon.Note']", 'null': 'True', 'blank': 'True'}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'last_modification_date': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'parent': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'children'", 'to': "orm['galcon.Thread']"}),
'post_date': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'slug': ('django.db.models.fields.SlugField', [], {'default': "''", 'max_length': '100'}),
'text': ('django.db.models.fields.TextField', [], {'max_length': '65000'}),
'title': ('django.db.models.fields.TextField', [], {'max_length': '100'})
},
'galcon.rank': {
'Meta': {'object_name': 'Rank'},
'classic_rank': ('django.db.models.fields.IntegerField', [], {'default': '0'}),
'flash_rank': ('django.db.models.fields.IntegerField', [], {'default': '0'}),
'fusion_rank': ('django.db.models.fields.IntegerField', [], {'default': '0'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'iphone_rank': ('django.db.models.fields.IntegerField', [], {'default': '0'})
},
'galcon.section': {
'Meta': {'object_name': 'Section'},
'description': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'slug': ('django.db.models.fields.SlugField', [], {'default': "''", 'max_length': '100'}),
'title': ('django.db.models.fields.CharField', [], {'default': "''", 'max_length': '100'})
},
'galcon.subsection': {
'Meta': {'object_name': 'Subsection'},
'description': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'parent': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'children'", 'to': "orm['galcon.Section']"}),
'slug': ('django.db.models.fields.SlugField', [], {'default': "''", 'max_length': '100'}),
'title': ('django.db.models.fields.CharField', [], {'default': "''", 'max_length': '100'})
},
'galcon.thread': {
'Meta': {'object_name': 'Thread'},
'author': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'threads'", 'to': "orm['galcon.Player']"}),
'close_note': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['galcon.Note']", 'null': 'True', 'blank': 'True'}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'page_views': ('django.db.models.fields.IntegerField', [], {'default': '0'}),
'parent': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'children'", 'to': "orm['galcon.Subsection']"}),
'post_date': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'slug': ('django.db.models.fields.SlugField', [], {'default': "''", 'max_length': '100'}),
'sticky': ('django.db.models.fields.BooleanField', [], {'default': 'False'})
},
'galcon.trophy': {
'Meta': {'object_name': 'Trophy'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'image': ('django.db.models.fields.files.ImageField', [], {'max_length': '100'}),
'text': ('django.db.models.fields.TextField', [], {'max_length': '100'})
},
'groups.group': {
'Meta': {'object_name': 'Group'},
'admins': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'admined_groups'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['galcon.Player']"}),
'creation_time': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'blank': 'True'}),
'description': ('django.db.models.fields.TextField', [], {'max_length': '65000'}),
'hidden': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'join_requires_approval': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '25'}),
'slug': ('django.db.models.fields.SlugField', [], {'max_length': '100', 'blank': 'True'})
}
}
complete_apps = ['galcon'] | [
"marky1991@gmail.com"
] | marky1991@gmail.com |
02af9acedfd8eb63a76f63c93c109e539acb1fa4 | 0f9f8e8478017da7c8d408058f78853d69ac0171 | /python2/l0064_minimum_path_sum.py | e5eed8adafa9b21abd66ed0af9541fba57e42edd | [] | no_license | sprax/1337 | dc38f1776959ec7965c33f060f4d43d939f19302 | 33b6b68a8136109d2aaa26bb8bf9e873f995d5ab | refs/heads/master | 2022-09-06T18:43:54.850467 | 2020-06-04T17:19:51 | 2020-06-04T17:19:51 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 748 | py | class Solution(object):
def minPathSum(self, grid):
"""
:type grid: List[List[int]]
:rtype: int
"""
if not grid:
return 0
m = len(grid)
n = len(grid[0])
dp = [[0 for _ in range(n)] for _ in range(m)]
# Initialize.
dp[m-1][n-1] = grid[m-1][n-1]
for i in range(m-2, -1, -1):
dp[i][n-1] = grid[i][n-1] + dp[i+1][n-1]
for j in range(n-2, -1, -1):
dp[m-1][j] = grid[m-1][j] + dp[m-1][j+1]
# Solve.
for i in range(m-2, -1, -1):
for j in range(n-2, -1, -1):
dp[i][j] = min(dp[i+1][j], dp[i][j+1]) + grid[i][j]
return dp[0][0]
| [
"zhoulu312@gmail.com"
] | zhoulu312@gmail.com |
a41ee74e0d74a2f619205675cb265d0c888b3d01 | 9645bdfbb15742e0d94e3327f94471663f32061a | /Python/235 - Lowest Common Ancestor of a Binary Search Tree/235_lowest-common-ancestor-of-a-binary-search-tree.py | 863b29d2d3d70572b919bc045ab5e6b412efb394 | [] | no_license | aptend/leetcode-rua | f81c080b2260adb2da677612e5c437eda256781d | 80e44f4e9d3a5b592fdebe0bf16d1df54e99991e | refs/heads/master | 2023-06-22T00:40:05.533424 | 2021-03-17T13:51:28 | 2021-03-17T13:51:28 | 186,434,133 | 2 | 0 | null | 2023-06-21T22:12:51 | 2019-05-13T14:17:27 | HTML | UTF-8 | Python | false | false | 1,554 | py | from leezy import Solution, solution
from leezy.assists import TreeContext
class Q235(Solution):
@solution
def lowestCommonAncestor(self, root, p, q):
# 68ms
if p < root.val > q:
return self.lowestCommonAncestor(root.left, p, q)
if p > root.val < q:
return self.lowestCommonAncestor(root.right, p, q)
return root
@solution
def lca_iter(self, root, p, q):
# 76ms 40.62%
while root:
if root.val > p and root.val > q:
root = root.left
elif root.val < p and root.val < q:
root = root.right
else:
return root
def lca_dumb(self, root, p, q):
ppath, qpath = [], []
self.search(root, p, ppath)
self.search(root, q, qpath)
prev = x = y = None
for x, y in zip(ppath, qpath):
if x.val != y.val:
return prev
prev = x
return x
def search(self, node, v, path):
if node is None:
path.clear()
return
if v == node.val:
path.append(node)
return
path.append(node)
if v > node.val:
self.search(node.right, v, path)
else:
self.search(node.left, v, path)
def main():
q = Q235()
q.set_context(TreeContext)
t1 = [6, 2, 8, 0, 4, 7, 9, None, None, 3, 5]
q.add_args(t1, 2, 8)
q.add_args(t1, 2, 4)
q.add_args(t1, 3, 7)
q.run()
if __name__ == "__main__":
main()
| [
"crescentwhale@hotmail.com"
] | crescentwhale@hotmail.com |
dcbc15d24ae14bff864146e04855549fd69c3bd4 | 029529c28784dc73362dfb38d29d16cbbba3ac98 | /odx_crm_lead/models/insurance_premium.py | 8d33f341e78187ce5b465199992165476b8c3d84 | [] | no_license | linux8a/odoo_13 | 4a99e3ccaf7956c33501e7c1be79e84f6d763f95 | 19bbcecee21bbd8b4298df899dc4f3f47dff63ea | refs/heads/master | 2022-12-21T07:48:09.968327 | 2020-10-04T06:12:54 | 2020-10-04T06:12:54 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,007 | py | # -*- coding: utf-8 -*-
from odoo import fields, models, api
class InsurancePremium(models.Model):
_name = 'insurance.premium'
name = fields.Char('Name')
insurance_company_id = fields.Many2one('res.partner', 'Insurance Company',
domain=[('is_insurance_comapny', '=', True)],required=True)
insurence_category = fields.Selection(
[('motor_insurance', 'Motor Insurance'), ('family_medical', 'Individual / Family Medical Insurance'),
('group_medical', 'Group Medical Insurance'), ('business', 'Business Insurance'),
('travel', 'Travel Insurance'), ('bike_insurance', 'Bike Insurance'), ('yacht_insurance', 'Yacht Insurance'),
('home_insurance', 'Home Insurance')], string='Insurance Category', required=True)
insurance_premium = fields.Selection([('fullcover', 'Full Cover'), ('comprehensive', 'Comprehensive')],
string="Insurance Premium")
vehicle_type = fields.Selection([('saloon', 'Saloon'), ('4_4', '4*4'),('p_up', 'P/UP'), ('motor_cycle', 'Motor Cycle'),
('trailer_watertanker', 'Trailer & Water Tanker'), ('equipments', 'Equipments'),('bus', 'Bus'),
('van', 'Van')],
string="Vehicle Type")
brokarage = fields.Float('Brokarage %')
premium_product = fields.Many2one('product.product',"Premium Product",required=True)
premium = fields.Float('Premium')
tax_id = fields.Many2one('account.tax',String='Tax')
total = fields.Float("Total",compute="_compute_amount")
tax_amount = fields.Float('Tax Amount ',compute="_compute_amount")
car_value = fields.Float('Car value')
excess = fields.Char('Excess / Deductible')
repaire_rates = fields.Char('Repaire Rates')
driver_age = fields.Selection([('18to25', 'Between 18 years to 25 years'), ('25_above', 'Above 25 years')],
string="Driver Age ")
date_of_first_registration = fields.Selection([('1st', '1st Year'), ('2nd', '2nd Year'),('3rd', '3rd Year'), ('4th', '4th Year'),('5th', '5th Year'), ('6th', '6th Year and above')],
string="Date of first registration and use")
# benifits
loss_dammage = fields.Boolean("Loss or Damage Cover")
repaire_type = fields.Selection(
[('agency', 'Agency Repair'),('non_agency', 'Non Agency Repair')],string="Repaire Type")
third_party_liability = fields.Float("Third Party Liability")
blood_money = fields.Boolean("Blood Money")
fire_theft = fields.Boolean("Fire And Cheft Cover")
storm_flood = fields.Boolean("Storm,Flood")
natural_perils = fields.Boolean("Natural Perils")
riot_strike = fields.Boolean("Riot & Strike")
emergency_medical_expenses = fields.Boolean("Emergency Medical Expenses")
personal_belongigs = fields.Boolean("Personal Belongings")
oman_cover = fields.Selection(
[('orange_card', 'Covered with orange card'),('yes', 'Yes'),('no', 'No')],string="Oman Cover")
p_off_road = fields.Boolean("P Off-Road Cover")
road_side_assistance = fields.Boolean("Road Side Assistance")
ambulance_cover = fields.Boolean("Ambulance Cover")
aed_500 = fields.Boolean("None Up to AED 5,000")
aed_3500 = fields.Boolean("None Up to AED 3,500")
optional_cover = fields.Boolean("Optional Covers")
driver_cover = fields.Boolean("Driver Cover")
passanger_cover = fields.Boolean("Passengers Cover")
rent_a_car = fields.Char("Rent A Car")
period_of_13_months = fields.Boolean("Perod Of 13 Months")
geographical_area = fields.Char("Geographical Area")
guranteed_repairs = fields.Boolean("Guaranteed Repairs")
accident_break_down = fields.Boolean("Accident And Breakdown Recovery")
excess_for_windscreen = fields.Char("Excess For Windscreen Damage")
emergency_road_assistance = fields.Char('Emergency Road Assistance')
geographical_area_extension = fields.Char("Geographical Area Extension")
replacement_vehcle = fields.Char("Replacement Vehcle")
assist_america_for_individual = fields.Char('Assist America For Individual')
no_of_cylinder = fields.Selection(
[('4cyl', '4Cyl'),('6cyl', '6Cyl'),('8cyl', '8Cyl'),('12cyl', '12Cyl')],string="No Of Cylinder")
private_commercial = fields.Selection(
[('private', 'Private'), ('commercial', 'Commercial')], string="Private/Commercial")
weight = fields.Selection(
[('1tonne', '1 Tonne'),('2tonne', '2 Tonne'),('3tonne', '3 Tonne'),('7tonne', '7 Tonne')],string="Weight")
engin = fields.Selection(
[('upto200', 'Up To 200 CC'), ('above200', 'Above 200 CC')],
string="Engin")
gallons = fields.Selection(
[('upto200', 'Up To 2000 Gallons'), ('upto5000', 'Up To 5000 Gallons')],
string="Gallons")
water_tanker = fields.Boolean('Water Tanker')
tariler = fields.Boolean("Trailer")
water_tanker_trailer = fields.Boolean("Water Tanker Trailer")
light_equipments = fields.Selection(
[('dumber_agriculture', 'Dumber & Agriculture'), ('forklift', 'Forklift')],
string="Light Equipments")
heavy = fields.Boolean('Heavy')
no_of_passengers = fields.Selection(
[('upto14', 'Up To 14 Passengers'),('upto26', 'Up To 26 Passengers'),('upto56', 'Up To 56 Passengers')],string="No Of Passengers")
# indivisual
package_name = fields.Char("Package Name")
network = fields.Char("Network")
additional_members_ids = fields.One2many('additional.members', 'insurance_premium_id', string='Additional Members')
@api.depends('premium', 'tax_id.amount')
def _compute_amount(self):
for record in self:
if record.tax_id:
record.tax_amount = record.premium * (record.tax_id.amount/100)
else:
record.tax_amount = 0
record.total = record.premium + record.tax_amount
| [
"ashifpk1@gmail.com"
] | ashifpk1@gmail.com |
87da898bd08cdfef60ac23b93bfa4e87e4b7567d | 4587c4b6e381f0ac97a15fbf8f163d1bd9dbca8d | /codes/utils.py | 4c404d23805fd827f4b8294d3c1f5afe3e51ce5d | [] | no_license | shoukreytom/live-share-code | b514d2aadaa6716d5cbd7c6811823635102dc2f8 | 19f1b1cd1e93414a08bc47c5c141cbf34e65f8be | refs/heads/main | 2023-07-29T00:03:49.026302 | 2021-09-28T20:59:55 | 2021-09-28T20:59:55 | 368,343,352 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 141 | py | from random import randint
def generate_share_key():
code_list = [str(randint(0, 9)) for _ in range(6)]
return "".join(code_list)
| [
"shoukreytom01@gmail.com"
] | shoukreytom01@gmail.com |
ed777a2b20b0c94e0469882347bedeaacedfd55e | 876a1b7b7c898c826b94ff34f3d9a1d22ee5459b | /QUANTAXIS/QAUtil/QAWebutil.py | 8a2a75459233fd85e3744b092b8ba3babacb56ca | [
"MIT"
] | permissive | pm58/QUANTAXIS | 6db63c461d18f13f7340f7d46e42cde3bc3f40cb | 03c526f640f48f4a153e9c4e0e27f74ccd18a345 | refs/heads/master | 2020-04-27T08:17:42.227150 | 2019-03-09T05:56:05 | 2019-03-09T05:56:05 | 174,165,118 | 5 | 0 | MIT | 2019-03-09T05:56:06 | 2019-03-06T14:55:39 | Python | UTF-8 | Python | false | false | 1,967 | py | # coding:utf-8
#
# The MIT License (MIT)
#
# Copyright (c) 2016-2018 yutiansut/QUANTAXIS
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import datetime
from subprocess import PIPE, Popen
def QA_util_web_ping(url):
ms_list = []
p = Popen(["ping", url],
stdin=PIPE, stdout=PIPE, stderr=PIPE,
shell=True)
out = p.stdout.read()
list_ = str(out).split('=')
# print(list)
for item in list_:
if 'ms' in item:
ms_list.append(int(item.split('ms')[0]))
if len(ms_list) < 1:
# Bad Request:
ms_list.append(9999999)
return ms_list[-1]
class QA_Util_web_pool():
def __init__(self):
pass
def hot_update(self):
pass
def dynamic_optimics(self):
pass
def task_queue(self):
pass
if __name__ == "__main__":
print(datetime.datetime.now())
print(QA_util_web_ping('www.baidu.com'))
print(datetime.datetime.now())
| [
"yutiansut@qq.com"
] | yutiansut@qq.com |
14bff795b6ed2d74c4775d4f3bc0e738dffaa06b | 97eb29b4fbb55ca3c4b3f4ce6b5b9432eb73efdd | /DjangoEnv/bin/django-admin | 6a8820ebbc2b8895471291d8eddffd3f81122a90 | [] | no_license | Gephi-2017/ProjectDjango | ced8a5c8547b0366319b756def3ff7baa3c14226 | 33969fddf4abe2a19629ce1657d04e6cbdd82d74 | refs/heads/master | 2020-03-17T00:50:11.012635 | 2018-05-12T09:12:28 | 2018-05-12T09:12:28 | 133,131,612 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 297 | #!/home/shree/ProjectDjango/DjangoEnv/bin/python
# -*- coding: utf-8 -*-
import re
import sys
from django.core.management import execute_from_command_line
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(execute_from_command_line())
| [
"slshruthi17@gmail.com"
] | slshruthi17@gmail.com | |
bbc89e8e7645a694b405dccb4acd25b4f0cc9544 | 84cfe9b0ca7209487231e0725f7ad0d233f09544 | /smv/views.py | e0abea56ca1a13c1798a6cffabfed45f0991342d | [] | no_license | archit-dwevedi/M4Plan | 3eefc12ea447d624bae6f758c3648d7caf825c1a | d162592748ea37bc070b6217365e8601a6ccdd9a | refs/heads/master | 2021-10-26T23:22:04.456014 | 2019-04-14T20:02:17 | 2019-04-14T20:02:17 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,397 | py | from django.shortcuts import render,redirect
from django.http import HttpResponse
from django.contrib import messages
from absenteeism.models import *
from skill_matrix.models import *
from leave_calendar.models import *
from .forms import *
from .models import *
import datetime
def smv(request):
if(request.method=='POST'):
form = Smv(request.POST)
if form.is_valid():
form.save()
return HttpResponse("<h1>SMV is submitted</h1>")
else:
messages.error(request,"Error")
else:
form = Smv()
return render(request,'smv/smv.html',{'form':form})
def dashsmv(request):
a=SMV.objects.all()
return render(request,'smv/dash_smv.html',{'a':a})
def dashpfm(request):
a=SMV.objects.all()
sam=[]
mcs=[]
for i in a:
#time=((i.pick_in_sec+i.main_Process_in_sec+i.turn_in_sec+i.dispose_in_sec)*i.s_P_I.s_p_i)/12
sam.append((((((((i.pick_in_sec+i.main_Process_in_sec+i.turn_in_sec+i.dispose_in_sec)/60)/12)*i.s_P_I.s_p_i)/20)*i.stitch_Length.stitch_length)*int(i.complexity.complx))*(1+int(i.personal_Allowance+i.fatigue_Allowance+i.delay_Allowance))*0.02*0.9)
print(sam)
for i in sam:
mcs.append(560/(480/(i*0.85)))
print(mcs)
return render(request,'smv/dash_pfm.html',{'a':a,'sam':sam,'mcs':mcs})
def newdashpfm(request):
a=PFM.objects.all()
return render(request,'smv/new_dash_pfm.html',{'a':a})
def ob(request):
if(request.method=='POST'):
form=Pfm(request.POST)
if(form.is_valid()):
global a
global d
global s
s=request.POST.get('section')
a=PFM.objects.filter(sec__name=s)
d=a
return redirect('/newob')
else:
messages.error(request,"Error")
else:
form=Pfm()
return render(request,'smv/ob.html',{'form':form})
def newob(request):
if(request.method=='POST'):
global d
myself=Ob(request.POST,operation=d)
if(myself.is_valid()):
global get
cat=myself.cleaned_data['category']
sub=myself.cleaned_data['subcategory']
get=myself.cleaned_data['Add Neccessary Operation']
print(get)
print(cat,sub)
return redirect('/dashob')
else:
messages.error(request,"Error")
else:
global a
global s
form = Ob(operation=a)
return render(request,'smv/ob.html',{'form':form,'s':s})
def dashob(request):
global get
global q
q=[]
sam=[]
for i in get:
q.append(SMV.objects.get(operation=i))
for i in q:
print(i.operation)
print(i.s_P_I)
sam.append((((((((i.pick_in_sec + i.main_Process_in_sec + i.turn_in_sec + i.dispose_in_sec) / 60) / 12) * i.s_P_I.s_p_i) / 20) * i.stitch_Length.stitch_length) * int(i.complexity.complx)) * ( 1 + int(i.personal_Allowance + i.fatigue_Allowance + i.delay_Allowance)) * 0.02 * 0.9)
return render(request,'smv/dashob.html',{'a':q,'sam':sam})
def layout(request):
global s
global q
return render(request,'smv/layout.html',{'a':s,'q':q})
def dashboard(request):
global s
global q
global get
ab=[]
d=datetime.datetime.now().date()
a=LeaveApplication.objects.all()
for i in a:
if(d<=i.end_date):
ab.append(i.key.user)
print(ab)
b=Person.objects.all()
ab2=[]
for j in b:
if(j.date==d):
if(j.status=='Absent' or j.status=='Leave' or j.status==None):
ab2.append(User.objects.get(username=j.name))
print(ab2)
c=Scale.objects.all()
#e=Employee.objects.all()
ss=ab+ab2
for m in ss:
for n in c:
if(m==n.use):
c=c.exclude(use=m)
print(c)
print(get)
for i in get:
for j in c:
if(str(j.operation)==i):
print(j.use,j.operation,j.level)
## m=lambda x:x==y
## for i in c:
## y=str(i.operation)
## print(list(map(m,get)))
list=zip(c,q)
return render(request,'smv/dashboard.html',{'a':s,'q':q,'c':c,'get':get,'list':list})
def desc(request):
return render(request,'smv/desc.html')
| [
"dwevediar@gmail.com"
] | dwevediar@gmail.com |
b20b0b8aafd7085cbf29263b494a5e85bcf65b65 | 41d3442bed584a40dbff035ee808c844b0b47f3e | /scoring/evaluator_vocabulary.py | 71429f34645ac0710eafa9fe5d7ea689451b19e4 | [] | no_license | konstantinschulz/alpaca | 8e55b9b24a4c7c5db9ecfb041488ee34c9a43bb8 | baa500ebb1e7ce92fe34a7c0b7ea65479a510567 | refs/heads/main | 2023-08-25T05:26:09.271704 | 2021-10-27T13:57:39 | 2021-10-27T13:57:39 | 375,756,439 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,386 | py | import logging
import re
from collections import defaultdict
from pathlib import Path
import pandas as pd
from testing import test
from parsing.webpage_data import WebpageData
# modify profanity score gradient given this upper limit
MAX_PROFANITY = 3
# multiplier for emotion intensity per words ratio to modify final emotionality score
EMOTION_INTENSITY_MULTIPLIER = 2
# boundary checks
if MAX_PROFANITY <= 0 or EMOTION_INTENSITY_MULTIPLIER <= 0:
raise ValueError("A constant for vacabulary evaluation is set incorrectly")
logger = logging.getLogger("alpaca")
def evaluate_profanity(data: WebpageData) -> float:
"""Evaluates webpage by checking for occurrences of profanity.
Combines and checks webpage headline and text. Profanity score is linear from 0 occurrences (best score => 1) to
*MAX_PROFANITY* occurrences (worst score => 0).
:return: Value between 1 (low profanity) and 0 (high profanity).
"""
# file containing profanity/slurs, one entry per line
profanity_list_path = "files/profanity.txt"
filepath = (Path(__file__).parent / profanity_list_path).resolve()
fulltext = data.headline.lower() + " " + data.text.lower()
profanity_matches = defaultdict(int)
with open(filepath, "r") as profanity_words:
for line in profanity_words.readlines():
if match := re.findall(r"\b" + line.strip() + r"\b", fulltext):
profanity_matches[match[0]] += len(match)
if profanity_matches:
logger.info("[Vocabulary] Profanity matches: {}"
.format(["{} ({}x)".format(slur, occurrences) for slur, occurrences in profanity_matches.items()]))
test.add_result(data.url, "profanity", sum(profanity_matches.values()))
match_count = sum(profanity_matches.values())
score = match_count / MAX_PROFANITY
return 1 - min(score, 1)
def evaluate_emotional_words(data: WebpageData) -> float:
"""Evaluates the vocabulary used by the webpage for its emotionality.
Compares all words in the headline and text against a list of emotional words with specified emotion intensity
values. Sums up all intensity values for any matches, scales the total sum by word count. Final score is linear
between 0 (worst score, words have on average at least 1 / *EMOTION_INTENSITY_MULTIPLIER* emotion intensity) and 1
(best score, words have 0 emotion intensity on average).
:return: Value between 0 (high emotionality) and 1 (low emotionality).
"""
# TODO possibly limit scoring to some subset of emotions
# file containing words & their degree of association with 8 emotions, one entry per line
# using emotion intensity lexicon by Saif M. Mohammad https://saifmohammad.com/WebPages/AffectIntensity.htm
emotion_list_path = "files/emotion_intensity_list.csv"
filepath = (Path(__file__).parent / emotion_list_path).resolve()
emotional_words = pd.read_csv(filepath, sep=";")
df_size = len(emotional_words)
fulltext = data.headline.lower() + " " + data.text.lower()
word_count = 0
emotionality_results = {"anger": {"count": 0, "intensity": 0},
"anticipation": {"count": 0, "intensity": 0},
"disgust": {"count": 0, "intensity": 0},
"fear": {"count": 0, "intensity": 0},
"sadness": {"count": 0, "intensity": 0},
"joy": {"count": 0, "intensity": 0},
"surprise": {"count": 0, "intensity": 0},
"trust": {"count": 0, "intensity": 0}}
# lookup all words from article in emotional words list
for article_word in re.findall("[a-z]+", fulltext):
word_count += 1
match = emotional_words["word"].searchsorted(article_word)
if match < df_size and emotional_words.iat[match, 0] == article_word:
# get emotion intensity data for a word match
for emotion, emotion_intensity in emotional_words.iloc[match, 1:].items():
if emotion_intensity > 0:
emotionality_results[emotion]["count"] += 1
emotionality_results[emotion]["intensity"] += emotion_intensity
total_emotion_count = sum(emotion_stats["count"] for emotion_stats in emotionality_results.values())
total_emotion_intensity = sum(emotion_stats["intensity"] for emotion_stats in emotionality_results.values())
logger.debug("[Vocabulary] Emotionality results: {}".format(
["{}: {} words, {:.3f} intensity".format(emotion, emotion_stats["count"], emotion_stats["intensity"])
for emotion, emotion_stats in emotionality_results.items()]))
logger.debug("[Vocabulary] Emotionality overall: {} words | {:.3f} intensity | {:.3f} intensity per word".format(
total_emotion_count, total_emotion_intensity, total_emotion_intensity / word_count))
for emotion in emotionality_results.keys():
test.add_result(data.url, emotion + "_word_count", emotionality_results[emotion]["count"])
test.add_result(data.url, emotion + "_intensity", emotionality_results[emotion]["intensity"])
emotion_score = (total_emotion_intensity * EMOTION_INTENSITY_MULTIPLIER) / word_count
return max(1 - emotion_score, 0)
| [
"Konstantin.Schulz@dfki.de"
] | Konstantin.Schulz@dfki.de |
42cc2d6e0d7d6b565e6ce9d80f133c7f719e9115 | b05cbedbcda2efd5e3722a52f309e7987b618de0 | /Logging.py | 23054220361b751acad1e9d24757b7a8507dd4df | [
"MIT"
] | permissive | bwhetherington/Gompei-Bot | ef32100a690e1af9be94511b33373e56cf186f72 | a6c03c7a5a190fc63a96d0e4ab2529c3ba484dcb | refs/heads/master | 2023-06-30T03:11:23.221088 | 2020-07-29T05:33:08 | 2020-07-29T05:33:08 | 286,293,970 | 0 | 0 | null | 2020-08-09T18:26:09 | 2020-08-09T18:26:09 | null | UTF-8 | Python | false | false | 15,221 | py | # TODO: Implementation
# IDEA: Track which invite a user joined off of
import discord
import json
import os
from datetime import datetime
from discord.ext import commands
def module_perms(ctx):
return ctx.message.author.guild_permissions.administrator
def parse_id(arg):
"""
Parses an ID from a discord mention
:param arg: mention or ID passed
:return: ID
"""
if "<" in arg:
for i, c in enumerate(arg):
if c.isdigit():
return int(arg[i:-1])
# Using ID
else:
return int(arg)
class Logging(commands.Cog):
def __init__(self, bot):
self.bot = bot
self.embed = discord.Embed()
self.logs = None
async def update_guilds(self):
savedGuilds = []
for guildID in self.logs:
savedGuilds.append(guildID)
guilds = []
for guild in self.bot.guilds:
guilds.append(str(guild.id))
addGuilds = [x for x in guilds if x not in savedGuilds]
removeGuilds = [x for x in savedGuilds if x not in guilds]
# Add new guilds
for guildID in addGuilds:
self.logs[str(guildID)] = {"channel": None}
# Remove disconnected guilds
for guildID in removeGuilds:
self.logs.pop(str(guildID))
await self.update_state()
@commands.Cog.listener()
async def on_ready(self):
await self.load_state()
await self.update_guilds()
@commands.command(pass_context=True, name="logging")
@commands.check(module_perms)
async def change_logging(self, ctx, arg1):
"""
Changes the channel that the bot sends logging messages in
:param arg1: channel ID or mention
"""
channel = ctx.guild.get_channel(parse_id(arg1))
print(parse_id(arg1))
if self.logs[str(ctx.message.guild.id)]["channel"] != channel.id:
self.logs[str(ctx.message.guild.id)]["channel"] = channel.id
print("Updating guild " + str(ctx.message.guild.id) + " to use logging channel " + str(channel.id))
await self.update_state()
print("Finished updating logging channel")
await ctx.send("Successfully updated logging channel to <#" + str(channel.id) + ">")
@change_logging.error
async def change_logging_error(self, ctx, error):
if isinstance(error, commands.CheckFailure):
print("!ERROR! " + str(ctx.author.id) + " did not have permissions for change logging command")
elif isinstance(error, commands.MissingRequiredArgument):
await ctx.send("Command is missing arguments")
else:
print(error)
async def load_state(self):
with open(os.path.join("config", "logging.json"), "r+") as loggingFile:
logs = loggingFile.read()
self.logs = json.loads(logs)
async def update_state(self):
with open(os.path.join("config", "logging.json"), "r+") as loggingFile:
loggingFile.truncate(0)
loggingFile.seek(0)
json.dump(self.logs, loggingFile, indent=4)
@commands.Cog.listener()
async def on_message_delete(self, message):
"""
Sends a logging message containing
author, channel, content, and time of the deleted message
:param message: message object deleted
"""
if not message.author.bot:
if self.logs[str(message.guild.id)]["channel"] is not None:
loggingChannel = message.guild.get_channel(int(self.logs[str(message.guild.id)]["channel"]))
channel = message.channel
self.embed = discord.Embed()
self.embed.colour = discord.Colour(0xbe4041)
self.embed.set_author(name=message.author.name + "#" + message.author.discriminator, icon_url=message.author.avatar_url)
self.embed.title = "Message deleted in " + "#" + channel.name
self.embed.description = message.content
self.embed.set_footer(text="ID: " + str(message.author.id))
self.embed.timestamp = datetime.utcnow()
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_raw_message_delete(self, payload):
"""
Sends a logging message containing
location (channel), and ID of the message deleted
:param payload:
:return:
"""
guild = self.bot.get_guild(payload.guild_id)
if self.logs[str(guild.id)]["channel"] is not None and payload.cached_message is None:
loggingChannel = guild.get_channel(int(self.logs[str(guild.id)]["channel"]))
channel = guild.get_channel(payload.channel_id)
self.embed = discord.Embed()
self.embed.colour = discord.Colour(0xbe4041)
self.embed.title = "Message deleted in " + "#" + channel.name
self.embed.set_footer(text="Uncached message: " + str(payload.message_id))
self.embed.timestamp = datetime.utcnow()
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_raw_bulk_message_delete(self, payload):
"""
Sends a logging message containing
author, location (channel and placement), content, and time of the deleted messages
May be limited if message is not in the cache
:param payload:
"""
guild = self.bot.get_guild(payload.guild_id)
if self.logs[str(guild.id)]["channel"] is not None:
loggingChannel = guild.get_channel(int(self.logs[str(guild.id)]["channel"]))
channel = guild.get_channel(payload.channel_id)
content = ""
count = 0
for message in payload.cached_messages:
count += 1
content += "[" + message.author.name + "#" + message.author.discriminator + "]: " + message.content + "\n"
self.embed = discord.Embed()
self.embed.colour = discord.Colour(0xbe4041)
self.embed.title = str(count) + " Messages bulk deleted in " + "#" + channel.name
self.embed.description = content
self.embed.timestamp = datetime.utcnow()
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_message_edit(self, before, after):
"""
Sends a logging message containing
the content of the message before and after the edit
:param before: message object before
:param after: message object after
"""
if not before.author.bot:
if self.logs[str(before.guild.id)]["channel"] is not None:
if before.content is after.content:
return
loggingChannel = before.guild.get_channel(int(self.logs[str(before.guild.id)]["channel"]))
channel = before.channel
self.embed = discord.Embed(url=before.jump_url)
self.embed.colour = discord.Colour(0x8899d4)
self.embed.set_author(name=before.author.name + "#" + before.author.discriminator, icon_url=before.author.avatar_url)
self.embed.title = "Message edited in #" + channel.name
self.embed.description = "**Before:** " + before.content + "\n**+After:** " + after.content
self.embed.set_footer(text="ID: " + str(before.author.id))
self.embed.timestamp = datetime.utcnow()
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_raw_message_edit(self, payload):
"""
Sends a logging message containing
the content of the message after the edit
:param payload:
:return:
"""
# FIXME: Cannot get guild from payload
# guild = self.bot.get_guild(payload.guild_id)
#
# if self.logs[str(guild.id)]["channel"] is not None and payload.cached_message is None:
# loggingChannel = guild.get_channel(int(self.logs[str(guild.id)]["channel"]))
# channel = guild.get_channel(payload.channel_id)
# message = channel.fetch_message(payload.message_id)
#
# self.embed = discord.Embed()
# self.embed.colour = discord.Colour(0x8899d4)
# self.embed.set_author(name=message.author.name + "#" + message.author.discriminator, icon_url=message.author.avatar_url)
# self.embed.title = "Message edited in " + "#" + channel.name
# self.embed.description = "\n**+After:** " + message.content
# self.embed.set_footer(text="ID: " + str(message.author.id))
# self.embed.timestamp = datetime.utcnow()
#
# await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_guild_channel_create(self, channel):
"""
Sends a logging message containing
the name, category, and permissions of the channel
:param channel:
"""
if self.logs[str(channel.guild.id)]["channel"] is not None:
loggingChannel = channel.guild.get_channel(int(self.logs[str(channel.guild.id)]["channel"]))
self.embed = discord.Embed()
self.embed.colour = discord.Colour(0x43b581)
permissions = ""
# If a Category
if channel.type is discord.ChannelType.category:
self.embed.title = "Category created"
description = "**Name:** " + channel.name + "\n**Position:** " + str(channel.position)
if len(channel.overwrites) > 0:
for role in channel.overwrites:
# If you have permission to read messages
if channel.overwrites[role].pair()[0].read_messages is True:
permissions += "**Read Text Channels & See Voice Channels:** :white_check_mark:\n"
permissions += "**Connect:** :white_check_mark:"
else:
permissions += "**Read Text Channels & See Voice Channels:** :x:\n"
permissions += "**Connect:** :x:"
else:
description = "**Name:** " + channel.name + "\n**Position:** " + str(
channel.position) + "\n**Category:** "
if channel.category is not None:
description += channel.category.name
else:
description += "None"
# If a text channel
if channel.type is discord.ChannelType.text:
self.embed.title = "Text channel created"
if len(channel.overwrites) > 0:
for role in channel.overwrites:
if channel.overwrites[role].pair()[0].read_messages is True:
permissions += "**Read messages:** :white_check_mark:"
else:
permissions += "**Read messages:** :x:"
# If a VoiceChannel
else:
self.embed.title = "Voice channel created"
if len(channel.overwrites) > 0:
for role in channel.overwrites:
permissions = ""
if channel.overwrites[role].pair()[0].connect is True:
permissions += "**Connect:** :white_check_mark:"
else:
permissions += "**Connect:** :x:"
self.embed.add_field(name="Overwrites for " + str(role.name), value=permissions, inline=False)
self.embed.description = description
self.embed.set_footer(text="ID: " + str(channel.id))
self.embed.timestamp = datetime.utcnow()
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_guild_channel_delete(self, channel):
"""
Sends a logging message containing
the name, category, and permissions of the channel
"""
if self.logs[str(channel.guild.id)]["channel"] is not None:
loggingChannel = channel.guild.get_channel(int(self.logs[str(channel.guild.id)]["channel"]))
self.embed = discord.Embed()
self.embed.colour = discord.Colour(0xbe4041)
if channel.type is discord.ChannelType.category:
self.embed.title = "Category deleted"
description = "**Name:** " + channel.name
else:
if channel.type is discord.ChannelType.text:
self.embed.title = "Text channel deleted"
else:
self.embed.title = "Voice channel deleted"
description = "**Name:** " + channel.name + "\n**Category:** "
if channel.category is not None:
description += channel.category.name
else:
description += "None"
self.embed.description = description
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_guild_channel_update(self, before, after):
"""
Sends a logging message containing
the updated properties of the channel
"""
# Check name update
if before.name != after.name:
if before.type is discord.ChannelType.category:
self.embed.title
# Check position update
# Check permission update
# Slow mode
# NSFW
return
@commands.Cog.listener()
async def on_guild_channel_pins_update(self, channel, last_pin):
"""
Sends a logging message containing
the name of the channel, the content of the pinned message, and a link to the message
"""
return
@commands.Cog.listener()
async def on_guild_integrations_update(self, guild):
"""
WTF are guild integrations???
"""
return
@commands.Cog.listener()
async def on_webhooks_update(self, channel):
"""
WTF are webhooks???
"""
return
@commands.Cog.listener()
async def on_member_join(self, member):
"""
Sends a logging message containing
the name, avatar, id, join position, account age
"""
if self.logs[str(member.guild.id)]["channel"] is not None:
loggingChannel = member.guild.get_channel(int(self.logs[str(member.guild.id)]["channel"]))
ordinal = lambda n: "%d%s" % (n, "tsnrhtdd"[(n / 10 % 10 != 1) * (n % 10 < 4) * n % 10::4])
self.embed = discord.Embed()
self.embed.colour = discord.Colour(0x43b581)
self.embed.set_author(name=member.name + "#" + member.discriminator, icon_url=member.avatar_url)
self.embed.title = "Member joined"
creationDelta = datetime.now() - member.created_at
count = 0
self.embed.description = "<@" + str(member.id) + "> " + ordinal(member.guild.member_count) + " to join\ncreated "
self.embed.set_footer(text="ID: " + str(member.id))
self.embed.timestamp = datetime.utcnow()
await loggingChannel.send(embed=self.embed)
@commands.Cog.listener()
async def on_member_remove(self, member):
"""
Sends a logging message containing
the name, avatar, id, time spent on the server
"""
return
@commands.Cog.listener()
async def on_member_update(self, before, after):
"""
Sends a logging message containing
the property of the member updated before and after
"""
return
@commands.Cog.listener()
async def on_user_update(self, before, after):
"""
Sends a logging message containing
the property of the user updated before and after
"""
return
@commands.Cog.listener()
async def on_guild_update(self, before, after):
"""
Sends a logging message containing
the property of the guild updated before and after
"""
return
@commands.Cog.listener()
async def on_guild_role_create(self, role):
"""
Sends a logging message containing
the id, name, color, mentionable, and hoisted properties of the role
"""
return
@commands.Cog.listener()
async def on_guild_role_delete(self, role):
"""
Sends a logging message containing
the id, name, color, mentionable, and hoisted properties of the role
"""
return
@commands.Cog.listener()
async def on_guild_role_update(self, before, after):
"""
Sends a logging message containing
the property of the role updated before and after
"""
return
@commands.Cog.listener()
async def on_guild_emojis_update(self, guild, before, after):
"""
Sends a logging message containing
the id, name, and picture of the emoji
"""
return
@commands.Cog.listener()
async def on_voice_state_update(self, member, before, after):
"""
Sends a logging message containing
the id, name, and updated voice properties of the member
"""
return
@commands.Cog.listener()
async def on_member_ban(self, guild, user):
"""
Sends a logging message containing
the id, name, and join date of the member
"""
return
@commands.Cog.listener()
async def on_member_unban(self, guild, user):
"""
Sends a logging message containing
the id and name of the member
"""
return
@commands.Cog.listener()
async def on_invite_create(self, invite):
"""
Sends a logging message containing
the invite code, inviter name, inviter id, expiration time
"""
return
@commands.Cog.listener()
async def on_invite_delete(self, invite):
"""
Sends a logging message containing
the invite code, inviter name, and expiration time
"""
return
| [
"samuelcurrid@gmail.com"
] | samuelcurrid@gmail.com |
91b9e1b36fadf5d38e7788326e49195823ae4444 | 957563c6d08819967813063a193619b7df7f0050 | /mbof/migrations/0010_auto_20160303_1142.py | 5840ed33e44677751ee650c027ae7832c5cc6e5b | [] | no_license | jlost/hacks_mbof | 0c44657448c58c35b2443f285e2e0aa107980431 | 9bfe464e2842a09d2974103b5e8b5be15bd5d1cc | refs/heads/master | 2021-01-21T07:45:59.878779 | 2016-03-04T16:13:27 | 2016-03-04T16:13:27 | 53,062,453 | 0 | 0 | null | 2016-03-03T15:43:03 | 2016-03-03T15:43:03 | null | UTF-8 | Python | false | false | 535 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.9.3 on 2016-03-03 16:42
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('mbof', '0009_auto_20160303_1131'),
]
operations = [
migrations.AlterField(
model_name='user',
name='roles',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='mbof.Role'),
),
]
| [
"its-jlost@adsroot.itcs.umich.edu"
] | its-jlost@adsroot.itcs.umich.edu |
06229e6afb5087b342f48ced5e2d41a803b865c3 | 30b084acbe36d02e85d756e4580f0e845dab65c9 | /setup.py | 4f793631bb4105c6c26c9395bfc1f42ed30854ef | [] | no_license | JavanTang/py2aliyungdb | 47757ae9aacd4496a4fd4dda2733fc11c0ac5548 | c62b985d04e1cb00c8f63f881a4ade1d2ed0eaa6 | refs/heads/master | 2022-12-03T01:48:53.163098 | 2020-08-17T05:40:46 | 2020-08-17T05:40:46 | 288,082,092 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 405 | py | '''
Author: JavanTang
Data: Do not edit
LastEditors: JavanTang
LastEditTime: 2020-08-17 11:04:35
Description:
'''
from setuptools import setup
setup(
name='py2aliyungdb', # 应用名
version='0.0.1', # 版本号
packages=['py2aliyungdb'], # 包括在安装包内的 Python 包
author='JavanTang',
author_email='tzfjobmail@gmail.com',
url='https://github.com/pypa/sampleproject'
) | [
"tzfjobmail@gmail.com"
] | tzfjobmail@gmail.com |
1922476617a16ac1492b7ae020e4478f854a244c | 97db962c17f91f6ca5da71a5a301094277d26a8e | /setup.py | ddd05323c9f71b1b4c9a1e80868e6267655cee53 | [] | no_license | citrix-openstack/osnotify | 0a510457e3663092a6a6d8e575019a5052c896e5 | 2feca02a843fed93a9d36254d7e896ba95107a9c | refs/heads/master | 2020-05-17T01:04:23.088988 | 2013-03-01T17:34:37 | 2013-03-01T17:34:37 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 576 | py | from setuptools import setup
setup(
name="osnotify",
version="0.0",
packages=["osnotify"],
entry_points={
'console_scripts': [
'osnotify-proxy = osnotify.scripts:proxy',
'osnotify-subscribe = osnotify.scripts:subscribe',
'osnotify-publish = osnotify.scripts:publish',
'osnotify-install-service = osnotify.scripts:install_service',
'osnotify-gerrit-to-githook = osnotify.scripts:gerrit_to_githook',
'generate-initscript = osnotify.scripts:generate_initscript',
]
}
)
| [
"mate.lakat@citrix.com"
] | mate.lakat@citrix.com |
1984950eeeabd376b7d534bbc788f09949c9ea71 | f3416956f9bfc7af870867e2fe8644f08d513b23 | /combine/contest_20150310a/data_prep/prepare_pgmodel.py | 18a14ff2cbcfdb41cfe5e56133323bb4b304d6ed | [] | no_license | dsjoerg/blundercheck | a71012c0d3ded929599d191d4f73dcb14f94030a | 04fb39ba0dd1591b387f573f767973518b688822 | refs/heads/master | 2021-01-18T18:35:21.992359 | 2015-03-24T18:11:11 | 2015-03-24T18:11:11 | 27,928,453 | 4 | 1 | null | null | null | null | UTF-8 | Python | false | false | 8,108 | py | #!/usr/bin/env python
from pandas import *
from numpy import *
from djeval import *
import csv, code
import cPickle as pickle
from sklearn.externals import joblib
GAMELIMIT=60000
NUM_GAMES=100000
def shell():
vars = globals()
vars.update(locals())
shell = code.InteractiveConsole(vars)
shell.interact()
msg("Hi! Reading eheaders")
eheaders_filename = '/data/eheaders.p'
eheaders_file = open(eheaders_filename, 'r')
eheaders = pickle.load(eheaders_file)
elos = eheaders['elos']
result = eheaders['result']
checkmate = eheaders['checkmate']
openings = eheaders['openings']
ocount = eheaders['opening_count']
msg("Hi! Reading crunched movescores from %s" % sys.argv[1])
crunched_path = sys.argv[1]
crunched_df = read_csv(crunched_path, sep=',', engine='c', index_col=['gamenum', 'side'])
msg("Hi! Reading GB scores from %s" % sys.argv[2])
gb_path = sys.argv[2]
gb_df = read_csv(gb_path, sep=',', engine='c', index_col=['gamenum'])
msg("Hi! Reading depthstats")
depthstats_path = '/data/depthstats.csv'
columns = [
'gamenum',
'side',
'mean_depth',
'mean_seldepth',
'mean_depths_agreeing_ratio',
'mean_deepest_agree_ratio',
'pct_sanemoves',
'gamelength',
'mean_num_bestmoves',
'mean_num_bestmove_changes',
'mean_bestmove_depths_agreeing',
'mean_deepest_change',
'mean_deepest_change_ratio',
]
depthstats_df = read_csv(depthstats_path, sep=' ', engine='c', header=None, names=columns, index_col=False)
depthstats_df = depthstats_df.set_index(['gamenum', 'side'])
# we have the gamelength column in another df, drop it here to avoid conflicts
depthstats_df.drop('gamelength', axis=1, inplace=True)
msg("Hi! Reading material")
material_path = '/data/material.csv'
columns = [
'gamenum',
'material_break_0',
'material_break_1',
'material_break_2',
'material_break_3',
'material_break_4',
'opening_length',
'midgame_length',
'endgame_length',
'mean_acwsa',
'mean_acwsa_0',
'mean_acwsa_1',
'mean_acwsa_2',
'mean_acwsa_3',
'mean_acwsa_4',
'mean_acwsa_5',
'mean_acwsa_6',
'mean_acwsa_7',
'mean_acwsa_8',
'mean_acwsa_9',
]
material_df = read_csv(material_path, sep=' ', engine='c', header=None, names=columns, index_col=False)
material_df = material_df.set_index(['gamenum'])
material_df = material_df.reindex(range(1, NUM_GAMES+1))
material_df = material_df.fillna(material_df.mean())
msg("Reading ELOscored data")
eloscored_cols = [
'gamenum',
'final_elo',
'final_ply',
'final_num_games',
'final_elo_stdev',
'elopath_min',
'elopath_max',
]
eloscored_df = read_csv('/data/data.pgn.eloscored21', sep=',', engine='c', header=None, names=eloscored_cols, index_col=False)
eloscored_df = eloscored_df.set_index(['gamenum'])
msg("Reading ELOscored data 4")
eloscored4_cols = [
'gamenum',
'final_elo',
'final_ply',
'final_num_games',
'final_elo_stdev',
]
eloscored4_cols[1:] = [x + '_elo4' for x in eloscored4_cols[1:]]
eloscored4_df = read_csv('/data/data.pgn.eloscored4', sep=',', engine='c', header=None, names=eloscored4_cols, index_col=False)
eloscored4_df = eloscored4_df.set_index(['gamenum'])
msg("Reading ELOscored data 10")
eloscored10_cols = [
'gamenum',
'final_elo',
'final_ply',
'final_num_games',
'final_elo_stdev',
]
eloscored10_cols[1:] = [x + '_elo10' for x in eloscored10_cols[1:]]
eloscored10_df = read_csv('/data/data.pgn.eloscored10', sep=',', engine='c', header=None, names=eloscored10_cols, index_col=False)
eloscored10_df = eloscored10_df.set_index(['gamenum'])
msg("Hi! Reading moveaggs")
move_aggs = joblib.load('/data/move_aggs.p')
move_aggs.fillna(move_aggs.mean(), inplace=True)
msg("Hi! Reading wmoveaggs")
wmove_aggs = joblib.load('/data/wmove_aggs.p')
wmove_aggs.fillna(wmove_aggs.mean(), inplace=True)
wmove_aggs.rename(columns={'elo_pred': 'moveelo_weighted'}, inplace=True)
do_elochunk = True
if do_elochunk:
ch_agg_df = joblib.load('/data/chunk_aggs.p')
ch_agg_df.index = ch_agg_df.index.droplevel('elo')
ch_agg_df.columns = ['elochunk_' + x for x in ch_agg_df.columns]
msg("Hi! Setting up playergame rows")
if do_elochunk:
elorange_cols = list(ch_agg_df.columns.values)
msg("elorange cols are %s" % elorange_cols)
msg('Preparing ELO df')
elo_rows = [[x[0][0], x[0][1], x[1]] for x in elos.items()]
elo_df = DataFrame(elo_rows, columns=['gamenum','side','elo'])
elo_df.set_index(['gamenum','side'], inplace=True)
msg('Joining DFs')
supplemental_dfs = [move_aggs[['mean', 'median', '25', '10', 'min', 'max', 'stdev']], wmove_aggs['moveelo_weighted'], depthstats_df, elo_df, crunched_df]
if do_elochunk:
supplemental_dfs.append(ch_agg_df)
mega_df = concat(supplemental_dfs, axis=1)
mega_df = mega_df.join(material_df, how='outer')
mega_df = mega_df.join(eloscored_df, how='outer')
mega_df = mega_df.join(eloscored4_df, how='outer')
mega_df = mega_df.join(eloscored10_df, how='outer')
mega_df = mega_df.join(gb_df, how='outer')
yy_df = mega_df
msg("hi, columns are %s" % yy_df.columns)
# TODO confirm that all columns are there
def opening_feature(opening):
if ocount[opening] < 20:
return 'rare'
if ocount[opening] < 200:
return 'uncommon'
return opening
msg("Hi! Computing additional features")
yy_df['opening_feature'] = [opening_feature(openings[x]) for x in yy_df.index.get_level_values('gamenum')]
yy_df['opening_count'] = [ocount[openings[x]] for x in yy_df.index.get_level_values('gamenum')]
yy_df['any_grit'] = (yy_df['grit'] > 0)
yy_df['major_grit'] = (yy_df['grit'] > 5)
yy_df['nmerror'] = log((-1 * yy_df['meanerror']).clip(1,60)).clip(1,4) - 2.53
yy_df['premature_quit'] = (yy_df['gameoutcome'] == -1) & (yy_df['my_final_equity'] > -100)
yy_df['drawn_game'] = (yy_df['gameoutcome'] == 0)
yy_df['ended_by_checkmate'] = yy_df['won_by_checkmate'] | yy_df['lost_by_checkmate']
yy_df['noblunders'] = (yy_df['blunderrate'] == 0)
yy_df['final_equity'] = yy_df['my_final_equity'].abs().clip(0,300)
yy_df['early_lead'] = yy_df['early_lead'].clip(0,100)
yy_df['mean_depth_clipped'] = yy_df['mean_depth'].clip(0,25)
yy_df['gamelength_clipped'] = yy_df['gamelength'].clip(20,200)
# prepare opponent_df with selected info about opponent
opponent_columns = ['meanerror', 'blunderrate', 'perfectrate', 'grit', 'meanecho', 'mate_created', 'mate_destroyed', 'q_error_one', 'q_error_two', 'stdeverror', 'elo', 'any_grit', 'noblunders', 'nmerror', 'mean_depths_agreeing_ratio', 'mean_deepest_agree_ratio']
if do_elochunk:
opponent_columns.extend(elorange_cols)
opponent_df = yy_df[opponent_columns]
opponent_df = opponent_df.reset_index()
opponent_df['side'] = opponent_df['side'] * -1
opponent_df.set_index(['gamenum', 'side'], inplace=True)
opponent_df.columns = ['opponent_' + x for x in opponent_df.columns]
yy_df = concat([yy_df, opponent_df], axis=1)
# more derived columns that use opponent comparisons
yy_df['elo_advantage'] = (yy_df['elo'] - yy_df['opponent_elo']).clip(-500, 500)
yy_df['max_nmerror'] = yy_df[['nmerror', 'opponent_nmerror']].max(axis=1)
yy_df['min_nmerror'] = yy_df[['nmerror', 'opponent_nmerror']].min(axis=1)
yy_df['max_meanecho'] = yy_df[['meanecho', 'opponent_meanecho']].max(axis=1)
yy_df['elo_avg'] = (yy_df['elo'] + yy_df['opponent_elo'])/2.0
yy_df['elo_advantage'] = (yy_df['elo'] - yy_df['opponent_elo'])
yy_df['winner_elo_advantage'] = yy_df['elo_advantage'] * yy_df['gameoutcome']
msg("Hi! Computing dummy variables")
categorical_features = ['opening_feature']
dummies = get_dummies(yy_df[categorical_features]).astype(np.int8)
yy_df = yy_df.join(dummies)
# fill in missing values
msg("Hi! Filling in missing values")
full_index = pandas.MultiIndex.from_product([range(1,NUM_GAMES + 1), [1,-1]], names=['gamenum', 'side'])
yy_df = yy_df.reindex(full_index)
yy_elo = yy_df['elo'].copy(True)
yy_df.fillna(yy_df.mean(numeric_only=True), inplace=True)
yy_df.fillna(False, inplace=True)
yy_df['elo'] = yy_elo
# stupid patch for some stupid opening feature that got assigned to False by fillna ?!!?!?!?
yy_df.loc[yy_df['opening_feature'] == False,'opening_feature'] = 'rare'
msg("Hi! Writing yy_df to disk")
yy_df.to_pickle(sys.argv[3])
msg("Column counts are:")
counts = yy_df.count(axis=0)
print counts
| [
"dsjoerg@gmail.com"
] | dsjoerg@gmail.com |
45b49213838540d4cfa9b40c36aa8caf8d58558d | 38445323b49947266d72645ec973b02e96879eed | /harshad number.py | 8a99c9850563a0ad3ee51f2ed7074159f804f964 | [] | no_license | pooja-pichad/loop | 2d9989b472a2fbacf0a85da06d869016b2d74083 | 47dafba1253da98f98c8fa389e13283ce1e14dee | refs/heads/main | 2023-04-22T02:58:49.274211 | 2021-05-22T07:13:39 | 2021-05-22T07:13:39 | 369,741,349 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 717 | py | # harshad number :
# it is take any number and add this two digit number and check the
# addition value is divisible bye this two digit number then it is divisible then its harshad
# number then it not divisiblr then it not harshad number
# forEx; 43
# 4+3=7
# 7/43
# num=int(input("enter a number "))
# i=0
# while i<1:
# a=num%10
# b=(num//10)%10
# c=(num//10)//10
# d=a+b+c
# i=i+1
# if num%d==0:
# print("harshad number")
# else:
# print("not harshad number")
i=1
while i<1000:
a=i%10
b=(i//10)%10
c=(i//10)//10
d=a+b+c
i=i+1
if i%d==0:
print("harshad number",i)
else:
print("not harshad number",i) | [
"noreply@github.com"
] | noreply@github.com |
e0eb2aa256dc0a8e392bfc9cb168920d0555df1b | 5f04fccd92eb698fa76ab972c01188d699125a50 | /ourdesign/wsgi.py | 3b753904a90607efbaaae48b7d70cb0ba37388e5 | [] | no_license | ourdesignspvt/ourdesign | 9dbc8b2b7e2dd7b3019b699a19cb6aa80c3a65a7 | cf9d8a3115d024c251d91b421510e1c4b8682c8a | refs/heads/master | 2020-04-05T17:16:37.610982 | 2018-11-11T06:20:49 | 2018-11-11T06:20:49 | 157,052,786 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 396 | py | """
WSGI config for ourdesign project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "ourdesign.settings")
application = get_wsgi_application()
| [
"ourdesignspvt@gmail.com"
] | ourdesignspvt@gmail.com |
fed90f6926dd100b6713610ba1b01e6bcdb8133f | c4caffea3c284a2d9454f373dc7c66903c431e42 | /test/functional/test_framework/test_framework.py | 319fd494a6dfefc8b9c9141b0329c53f64bdea0b | [
"MIT"
] | permissive | heliumchain/squorum | 2c36fc2b5149b61054f9aa5c234588f01a3a5d29 | 2e57ca8e774ab4d75999636abfa870fb8000477d | refs/heads/master | 2022-12-02T05:52:59.747926 | 2020-08-23T16:55:03 | 2020-08-23T16:55:03 | 138,344,695 | 4 | 2 | NOASSERTION | 2020-08-23T16:55:04 | 2018-06-22T20:18:03 | C++ | UTF-8 | Python | false | false | 20,380 | py | #!/usr/bin/env python3
# Copyright (c) 2014-2017 The Bitcoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Base class for RPC testing."""
from enum import Enum
import logging
import optparse
import os
import pdb
import shutil
import sys
import tempfile
import time
from .authproxy import JSONRPCException
from . import coverage
from .test_node import TestNode
from .util import (
MAX_NODES,
PortSeed,
assert_equal,
check_json_precision,
connect_nodes_bi,
disconnect_nodes,
get_datadir_path,
initialize_datadir,
p2p_port,
set_node_times,
sync_blocks,
sync_mempools,
)
class TestStatus(Enum):
PASSED = 1
FAILED = 2
SKIPPED = 3
TEST_EXIT_PASSED = 0
TEST_EXIT_FAILED = 1
TEST_EXIT_SKIPPED = 77
class BitcoinTestFramework():
"""Base class for a squorum test script.
Individual squorum test scripts should subclass this class and override the set_test_params() and run_test() methods.
Individual tests can also override the following methods to customize the test setup:
- add_options()
- setup_chain()
- setup_network()
- setup_nodes()
The __init__() and main() methods should not be overridden.
This class also contains various public and private helper methods."""
def __init__(self):
"""Sets test framework defaults. Do not override this method. Instead, override the set_test_params() method"""
self.setup_clean_chain = False
self.nodes = []
self.mocktime = 0
self.supports_cli = False
self.set_test_params()
assert hasattr(self, "num_nodes"), "Test must set self.num_nodes in set_test_params()"
def main(self):
"""Main function. This should not be overridden by the subclass test scripts."""
parser = optparse.OptionParser(usage="%prog [options]")
parser.add_option("--nocleanup", dest="nocleanup", default=False, action="store_true",
help="Leave squorumds and test.* datadir on exit or error")
parser.add_option("--noshutdown", dest="noshutdown", default=False, action="store_true",
help="Don't stop squorumds after the test execution")
parser.add_option("--srcdir", dest="srcdir", default=os.path.normpath(os.path.dirname(os.path.realpath(__file__))+"/../../../src"),
help="Source directory containing squorumd/squorum-cli (default: %default)")
parser.add_option("--cachedir", dest="cachedir", default=os.path.normpath(os.path.dirname(os.path.realpath(__file__)) + "/../../cache"),
help="Directory for caching pregenerated datadirs")
parser.add_option("--tmpdir", dest="tmpdir", help="Root directory for datadirs")
parser.add_option("-l", "--loglevel", dest="loglevel", default="INFO",
help="log events at this level and higher to the console. Can be set to DEBUG, INFO, WARNING, ERROR or CRITICAL. Passing --loglevel DEBUG will output all logs to console. Note that logs at all levels are always written to the test_framework.log file in the temporary test directory.")
parser.add_option("--tracerpc", dest="trace_rpc", default=False, action="store_true",
help="Print out all RPC calls as they are made")
parser.add_option("--portseed", dest="port_seed", default=os.getpid(), type='int',
help="The seed to use for assigning port numbers (default: current process id)")
parser.add_option("--coveragedir", dest="coveragedir",
help="Write tested RPC commands into this directory")
parser.add_option("--configfile", dest="configfile",
help="Location of the test framework config file")
parser.add_option("--pdbonfailure", dest="pdbonfailure", default=False, action="store_true",
help="Attach a python debugger if test fails")
parser.add_option("--usecli", dest="usecli", default=False, action="store_true",
help="use bitcoin-cli instead of RPC for all commands")
self.add_options(parser)
(self.options, self.args) = parser.parse_args()
PortSeed.n = self.options.port_seed
os.environ['PATH'] = self.options.srcdir + ":" + self.options.srcdir + "/qt:" + os.environ['PATH']
check_json_precision()
self.options.cachedir = os.path.abspath(self.options.cachedir)
# Set up temp directory and start logging
if self.options.tmpdir:
self.options.tmpdir = os.path.abspath(self.options.tmpdir)
os.makedirs(self.options.tmpdir, exist_ok=False)
else:
self.options.tmpdir = tempfile.mkdtemp(prefix="test")
self._start_logging()
success = TestStatus.FAILED
try:
if self.options.usecli and not self.supports_cli:
raise SkipTest("--usecli specified but test does not support using CLI")
self.setup_chain()
self.setup_network()
time.sleep(5)
self.run_test()
success = TestStatus.PASSED
except JSONRPCException as e:
self.log.exception("JSONRPC error")
except SkipTest as e:
self.log.warning("Test Skipped: %s" % e.message)
success = TestStatus.SKIPPED
except AssertionError as e:
self.log.exception("Assertion failed")
except KeyError as e:
self.log.exception("Key error")
except Exception as e:
self.log.exception("Unexpected exception caught during testing")
except KeyboardInterrupt as e:
self.log.warning("Exiting after keyboard interrupt")
if success == TestStatus.FAILED and self.options.pdbonfailure:
print("Testcase failed. Attaching python debugger. Enter ? for help")
pdb.set_trace()
if not self.options.noshutdown:
self.log.info("Stopping nodes")
if self.nodes:
self.stop_nodes()
else:
for node in self.nodes:
node.cleanup_on_exit = False
self.log.info("Note: squorumds were not stopped and may still be running")
if not self.options.nocleanup and not self.options.noshutdown and success != TestStatus.FAILED:
self.log.info("Cleaning up")
shutil.rmtree(self.options.tmpdir)
else:
self.log.warning("Not cleaning up dir %s" % self.options.tmpdir)
if success == TestStatus.PASSED:
self.log.info("Tests successful")
exit_code = TEST_EXIT_PASSED
elif success == TestStatus.SKIPPED:
self.log.info("Test skipped")
exit_code = TEST_EXIT_SKIPPED
else:
self.log.error("Test failed. Test logging available at %s/test_framework.log", self.options.tmpdir)
self.log.error("Hint: Call {} '{}' to consolidate all logs".format(os.path.normpath(os.path.dirname(os.path.realpath(__file__)) + "/../combine_logs.py"), self.options.tmpdir))
exit_code = TEST_EXIT_FAILED
logging.shutdown()
sys.exit(exit_code)
# Methods to override in subclass test scripts.
def set_test_params(self):
"""Tests must this method to change default values for number of nodes, topology, etc"""
raise NotImplementedError
def add_options(self, parser):
"""Override this method to add command-line options to the test"""
pass
def setup_chain(self):
"""Override this method to customize blockchain setup"""
self.log.info("Initializing test directory " + self.options.tmpdir)
if self.setup_clean_chain:
self._initialize_chain_clean()
else:
self._initialize_chain()
def setup_network(self):
"""Override this method to customize test network topology"""
self.setup_nodes()
# Connect the nodes as a "chain". This allows us
# to split the network between nodes 1 and 2 to get
# two halves that can work on competing chains.
for i in range(self.num_nodes - 1):
connect_nodes_bi(self.nodes, i, i + 1)
self.sync_all()
def setup_nodes(self):
"""Override this method to customize test node setup"""
extra_args = None
if hasattr(self, "extra_args"):
extra_args = self.extra_args
self.add_nodes(self.num_nodes, extra_args)
self.start_nodes()
def run_test(self):
"""Tests must override this method to define test logic"""
raise NotImplementedError
# Public helper methods. These can be accessed by the subclass test scripts.
def add_nodes(self, num_nodes, extra_args=None, rpchost=None, timewait=None, binary=None):
"""Instantiate TestNode objects"""
if extra_args is None:
extra_args = [[]] * num_nodes
if binary is None:
binary = [None] * num_nodes
assert_equal(len(extra_args), num_nodes)
assert_equal(len(binary), num_nodes)
for i in range(num_nodes):
self.nodes.append(TestNode(i, self.options.tmpdir, extra_args[i], rpchost, timewait=timewait, binary=binary[i], stderr=None, mocktime=self.mocktime, coverage_dir=self.options.coveragedir, use_cli=self.options.usecli))
def start_node(self, i, *args, **kwargs):
"""Start a squorumd"""
node = self.nodes[i]
node.start(*args, **kwargs)
node.wait_for_rpc_connection()
time.sleep(10)
if self.options.coveragedir is not None:
coverage.write_all_rpc_commands(self.options.coveragedir, node.rpc)
def start_nodes(self, extra_args=None, *args, **kwargs):
"""Start multiple squorumds"""
if extra_args is None:
extra_args = [None] * self.num_nodes
assert_equal(len(extra_args), self.num_nodes)
try:
for i, node in enumerate(self.nodes):
node.start(extra_args[i], *args, **kwargs)
for node in self.nodes:
node.wait_for_rpc_connection()
except:
# If one node failed to start, stop the others
self.stop_nodes()
raise
time.sleep(10)
if self.options.coveragedir is not None:
for node in self.nodes:
coverage.write_all_rpc_commands(self.options.coveragedir, node.rpc)
def stop_node(self, i):
"""Stop a squorumd test node"""
self.nodes[i].stop_node()
self.nodes[i].wait_until_stopped()
def stop_nodes(self):
"""Stop multiple squorumd test nodes"""
for node in self.nodes:
# Issue RPC to stop nodes
node.stop_node()
for node in self.nodes:
# Wait for nodes to stop
time.sleep(5)
node.wait_until_stopped()
def restart_node(self, i, extra_args=None):
"""Stop and start a test node"""
self.stop_node(i)
self.start_node(i, extra_args)
def assert_start_raises_init_error(self, i, extra_args=None, expected_msg=None, *args, **kwargs):
with tempfile.SpooledTemporaryFile(max_size=2**16) as log_stderr:
try:
self.start_node(i, extra_args, stderr=log_stderr, *args, **kwargs)
self.stop_node(i)
except Exception as e:
assert 'squorumd exited' in str(e) # node must have shutdown
self.nodes[i].running = False
self.nodes[i].process = None
if expected_msg is not None:
log_stderr.seek(0)
stderr = log_stderr.read().decode('utf-8')
if expected_msg not in stderr:
raise AssertionError("Expected error \"" + expected_msg + "\" not found in:\n" + stderr)
else:
if expected_msg is None:
assert_msg = "squorumd should have exited with an error"
else:
assert_msg = "squorumd should have exited with expected error " + expected_msg
raise AssertionError(assert_msg)
def wait_for_node_exit(self, i, timeout):
self.nodes[i].process.wait(timeout)
def split_network(self):
"""
Split the network of four nodes into nodes 0/1 and 2/3.
"""
disconnect_nodes(self.nodes[1], 2)
disconnect_nodes(self.nodes[2], 1)
self.sync_all([self.nodes[:2], self.nodes[2:]])
def join_network(self):
"""
Join the (previously split) network halves together.
"""
connect_nodes_bi(self.nodes, 1, 2)
self.sync_all()
def sync_all(self, node_groups=None):
if not node_groups:
node_groups = [self.nodes]
for group in node_groups:
sync_blocks(group)
sync_mempools(group)
def enable_mocktime(self):
"""Enable mocktime for the script.
mocktime may be needed for scripts that use the cached version of the
blockchain. If the cached version of the blockchain is used without
mocktime then the mempools will not sync due to IBD.
For backwared compatibility of the python scripts with previous
versions of the cache, this helper function sets mocktime to Jan 1,
2014 + (201 * 10 * 60)"""
self.mocktime = 1454124732 + (201 * 10 * 60)
def disable_mocktime(self):
self.mocktime = 0
# Private helper methods. These should not be accessed by the subclass test scripts.
def _start_logging(self):
# Add logger and logging handlers
self.log = logging.getLogger('TestFramework')
self.log.setLevel(logging.DEBUG)
# Create file handler to log all messages
fh = logging.FileHandler(self.options.tmpdir + '/test_framework.log')
fh.setLevel(logging.DEBUG)
# Create console handler to log messages to stderr. By default this logs only error messages, but can be configured with --loglevel.
ch = logging.StreamHandler(sys.stdout)
# User can provide log level as a number or string (eg DEBUG). loglevel was caught as a string, so try to convert it to an int
ll = int(self.options.loglevel) if self.options.loglevel.isdigit() else self.options.loglevel.upper()
ch.setLevel(ll)
# Format logs the same as squorumd's debug.log with microprecision (so log files can be concatenated and sorted)
formatter = logging.Formatter(fmt='%(asctime)s.%(msecs)03d000 %(name)s (%(levelname)s): %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
formatter.converter = time.gmtime
fh.setFormatter(formatter)
ch.setFormatter(formatter)
# add the handlers to the logger
self.log.addHandler(fh)
self.log.addHandler(ch)
if self.options.trace_rpc:
rpc_logger = logging.getLogger("BitcoinRPC")
rpc_logger.setLevel(logging.DEBUG)
rpc_handler = logging.StreamHandler(sys.stdout)
rpc_handler.setLevel(logging.DEBUG)
rpc_logger.addHandler(rpc_handler)
def _initialize_chain(self):
"""Initialize a pre-mined blockchain for use by the test.
Create a cache of a 200-block-long chain (with wallet) for MAX_NODES
Afterward, create num_nodes copies from the cache."""
assert self.num_nodes <= MAX_NODES
create_cache = False
for i in range(MAX_NODES):
if not os.path.isdir(get_datadir_path(self.options.cachedir, i)):
create_cache = True
break
if create_cache:
self.log.debug("Creating data directories from cached datadir")
# find and delete old cache directories if any exist
for i in range(MAX_NODES):
if os.path.isdir(get_datadir_path(self.options.cachedir, i)):
shutil.rmtree(get_datadir_path(self.options.cachedir, i))
# Create cache directories, run bitcoinds:
for i in range(MAX_NODES):
datadir = initialize_datadir(self.options.cachedir, i)
args = [os.getenv("BITCOIND", "squorumd"), "-spendzeroconfchange=1", "-server", "-keypool=1", "-datadir=" + datadir, "-discover=0"]
if i > 0:
args.append("-connect=127.0.0.1:" + str(p2p_port(0)))
self.nodes.append(TestNode(i, self.options.cachedir, extra_args=[], rpchost=None, timewait=None, binary=None, stderr=None, mocktime=self.mocktime, coverage_dir=None))
self.nodes[i].args = args
self.start_node(i)
# Wait for RPC connections to be ready
for node in self.nodes:
node.wait_for_rpc_connection()
# Create a 200-block-long chain; each of the 4 first nodes
# gets 25 mature blocks and 25 immature.
# Note: To preserve compatibility with older versions of
# initialize_chain, only 4 nodes will generate coins.
#
# blocks are created with timestamps 10 minutes apart
# starting from 2010 minutes in the past
self.enable_mocktime()
block_time = self.mocktime - (201 * 60)
for i in range(2):
for peer in range(4):
for j in range(25):
set_node_times(self.nodes, block_time)
self.nodes[peer].generate(1)
block_time += 60
# Must sync before next peer starts generating blocks
sync_blocks(self.nodes)
# Shut them down, and clean up cache directories:
self.stop_nodes()
self.nodes = []
self.disable_mocktime()
def cache_path(n, *paths):
return os.path.join(get_datadir_path(self.options.cachedir, n), "regtest", *paths)
for i in range(MAX_NODES):
for entry in os.listdir(cache_path(i)):
if entry not in ['wallet.dat', 'chainstate', 'blocks', 'sporks', 'zerocoin', 'backups']:
os.remove(cache_path(i, entry))
for i in range(self.num_nodes):
from_dir = get_datadir_path(self.options.cachedir, i)
to_dir = get_datadir_path(self.options.tmpdir, i)
shutil.copytree(from_dir, to_dir)
initialize_datadir(self.options.tmpdir, i) # Overwrite port/rpcport in bitcoin.conf
def _initialize_chain_clean(self):
"""Initialize empty blockchain for use by the test.
Create an empty blockchain and num_nodes wallets.
Useful if a test case wants complete control over initialization."""
for i in range(self.num_nodes):
initialize_datadir(self.options.tmpdir, i)
class ComparisonTestFramework(BitcoinTestFramework):
"""Test framework for doing p2p comparison testing
Sets up some squorumd binaries:
- 1 binary: test binary
- 2 binaries: 1 test binary, 1 ref binary
- n>2 binaries: 1 test binary, n-1 ref binaries"""
def set_test_params(self):
self.num_nodes = 2
self.setup_clean_chain = True
def add_options(self, parser):
parser.add_option("--testbinary", dest="testbinary",
default=os.getenv("BITCOIND", "squorumd"),
help="squorumd binary to test")
parser.add_option("--refbinary", dest="refbinary",
default=os.getenv("BITCOIND", "squorumd"),
help="squorumd binary to use for reference nodes (if any)")
def setup_network(self):
extra_args = [['-whitelist=127.0.0.1']] * self.num_nodes
if hasattr(self, "extra_args"):
extra_args = self.extra_args
self.add_nodes(self.num_nodes, extra_args,
binary=[self.options.testbinary] +
[self.options.refbinary] * (self.num_nodes - 1))
self.start_nodes()
class SkipTest(Exception):
"""This exception is raised to skip a test"""
def __init__(self, message):
self.message = message
| [
"tischenko_2006@ukr.net"
] | tischenko_2006@ukr.net |
25c53610cddc7f13a5edb9ef2f6bd7a082359139 | 25b96157297c6ee9d1a7faf4b0e85051aaf11591 | /preprocess/features/Interval.py | 0c27eb3b7f36d772c935063ab3fe285700051d3c | [] | no_license | notem/reWeFDE | 07ae4088d8d60bbd4a5fdde334cec9e0a4b7f0b0 | 6fe576db1c470f33ffd158c52cf1130c96351f8e | refs/heads/master | 2023-01-02T18:05:06.907759 | 2020-10-30T15:31:32 | 2020-10-30T15:31:32 | 179,397,367 | 18 | 6 | null | null | null | null | UTF-8 | Python | false | false | 2,677 | py | # inflow interval (icics, knn)
from features.common import X
def IntervalFeature(times, sizes, features, Category):
if Category == 'KNN':
# a list of first 300 intervals (KNN)
# incoming interval
count = 0
prevloc = 0
for i in range(0, len(sizes)):
if sizes[i] > 0:
count += 1
features.append(i - prevloc)
prevloc = i
if count == 300:
break
for i in range(count, 300):
features.append(X)
# outgoing interval
count = 0
prevloc = 0
for i in range(0, len(sizes)):
if sizes[i] < 0:
count += 1
features.append(i - prevloc)
prevloc = i
if count == 300:
break
for i in range(count, 300):
features.append(X)
if Category == "ICICS" or Category == "WPES11":
MAX_INTERVAL = 300
# Distribution of the intervals
# incoming interval
count = 0
prevloc = 0
interval_freq_in = [0] * (MAX_INTERVAL + 1)
for i in range(0, len(sizes)):
if sizes[i] > 0:
inv = i - prevloc - 1
prevloc = i
# record the interval
if inv > MAX_INTERVAL:
inv = MAX_INTERVAL
interval_freq_in[inv] += 1
# outgoing interval
count = 0
prevloc = 0
interval_freq_out = [0] * (MAX_INTERVAL + 1)
for i in range(0, len(sizes)):
if sizes[i] < 0:
inv = i - prevloc - 1
prevloc = i
# record the interval
if inv > MAX_INTERVAL:
inv = MAX_INTERVAL
interval_freq_out[inv] += 1
# ICICS: no grouping
if Category == "ICICS":
features.extend(interval_freq_in)
features.extend(interval_freq_out)
# WPES 11: 1, 2, 3-5, 6-8, 9-13, 14 (grouping)
if Category == "WPES11":
# incoming
features.extend(interval_freq_in[0:3])
features.append(sum(interval_freq_in[3:6]))
features.append(sum(interval_freq_in[6:9]))
features.append(sum(interval_freq_in[9:14]))
features.extend(interval_freq_in[14:])
# outgoing
features.extend(interval_freq_out[0:3])
features.append(sum(interval_freq_out[3:6]))
features.append(sum(interval_freq_out[6:9]))
features.append(sum(interval_freq_out[9:14]))
features.extend(interval_freq_out[14:])
| [
"njm3308@rit.edu"
] | njm3308@rit.edu |
3064cd6f1c55c75609f9e92b45a1a1caa35e25ed | 4e3c8b2cd89828e5f8d902d9d731e81c6dd33d55 | /2015-16/Meeting_1/Minecraft-master/pyglet/gl/cocoa.py | 0e6ce34ee5ff2ff4e4b66fc6a25ca5c7a73492ca | [
"MIT"
] | permissive | momja/Code-Club | c2a2c670545a8a77913b0a15078848e3f520bfe1 | 410c5ffbdae48aa69a170e80642405928e9cb6d5 | refs/heads/master | 2020-09-25T23:45:16.805921 | 2017-10-03T22:05:13 | 2017-10-03T22:05:13 | 66,742,298 | 64 | 5 | null | null | null | null | UTF-8 | Python | false | false | 6,931 | py | #!/usr/bin/env python
'''
'''
__docformat__ = 'restructuredtext'
__version__ = '$Id: $'
from pyglet.gl.base import Config, CanvasConfig, Context
from pyglet.gl import ContextException
from pyglet.gl import gl
from pyglet.gl import agl
from pyglet.canvas.cocoa import CocoaCanvas
from pyglet.libs.darwin.cocoapy import *
NSOpenGLPixelFormat = ObjCClass('NSOpenGLPixelFormat')
NSOpenGLContext = ObjCClass('NSOpenGLContext')
# Valid names for GL attributes and their corresponding NSOpenGL constant.
_gl_attributes = {
'double_buffer': NSOpenGLPFADoubleBuffer,
'stereo': NSOpenGLPFAStereo,
'buffer_size': NSOpenGLPFAColorSize,
'sample_buffers': NSOpenGLPFASampleBuffers,
'samples': NSOpenGLPFASamples,
'aux_buffers': NSOpenGLPFAAuxBuffers,
'alpha_size': NSOpenGLPFAAlphaSize,
'depth_size': NSOpenGLPFADepthSize,
'stencil_size': NSOpenGLPFAStencilSize,
# Not exposed by pyglet API (set internally)
'all_renderers': NSOpenGLPFAAllRenderers,
'fullscreen': NSOpenGLPFAFullScreen,
'minimum_policy': NSOpenGLPFAMinimumPolicy,
'maximum_policy': NSOpenGLPFAMaximumPolicy,
'screen_mask' : NSOpenGLPFAScreenMask,
# Not supported in current pyglet API
'color_float': NSOpenGLPFAColorFloat,
'offscreen': NSOpenGLPFAOffScreen,
'sample_alpha': NSOpenGLPFASampleAlpha,
'multisample': NSOpenGLPFAMultisample,
'supersample': NSOpenGLPFASupersample,
}
# NSOpenGL constants which do not require a value.
_boolean_gl_attributes = frozenset([
NSOpenGLPFAAllRenderers,
NSOpenGLPFADoubleBuffer,
NSOpenGLPFAStereo,
NSOpenGLPFAMinimumPolicy,
NSOpenGLPFAMaximumPolicy,
NSOpenGLPFAOffScreen,
NSOpenGLPFAFullScreen,
NSOpenGLPFAColorFloat,
NSOpenGLPFAMultisample,
NSOpenGLPFASupersample,
NSOpenGLPFASampleAlpha,
])
# Attributes for which no NSOpenGLPixelFormatAttribute name exists.
# We could probably compute actual values for these using
# NSOpenGLPFAColorSize / 4 and NSOpenGLFAAccumSize / 4, but I'm not that
# confident I know what I'm doing.
_fake_gl_attributes = {
'red_size': 0,
'green_size': 0,
'blue_size': 0,
'accum_red_size': 0,
'accum_green_size': 0,
'accum_blue_size': 0,
'accum_alpha_size': 0
}
class CocoaConfig(Config):
def match(self, canvas):
# Construct array of attributes for NSOpenGLPixelFormat
attrs = []
for name, value in self.get_gl_attributes():
attr = _gl_attributes.get(name)
if not attr or not value:
continue
attrs.append(attr)
if attr not in _boolean_gl_attributes:
attrs.append(int(value))
# Support for RAGE-II, which is not compliant.
attrs.append(NSOpenGLPFAAllRenderers)
# Force selection policy.
attrs.append(NSOpenGLPFAMaximumPolicy)
# NSOpenGLPFAFullScreen is always supplied so we can switch to and
# from fullscreen without losing the context. Also must supply the
# NSOpenGLPFAScreenMask attribute with appropriate display ID.
# Note that these attributes aren't necessary to render in fullscreen
# on Mac OS X 10.6, because there we are simply rendering into a
# screen sized window. See:
# http://developer.apple.com/library/mac/#documentation/GraphicsImaging/Conceptual/OpenGL-MacProgGuide/opengl_fullscreen/opengl_cgl.html%23//apple_ref/doc/uid/TP40001987-CH210-SW6
attrs.append(NSOpenGLPFAFullScreen)
attrs.append(NSOpenGLPFAScreenMask)
attrs.append(quartz.CGDisplayIDToOpenGLDisplayMask(quartz.CGMainDisplayID()))
# Terminate the list.
attrs.append(0)
# Create the pixel format.
attrsArrayType = c_uint32 * len(attrs)
attrsArray = attrsArrayType(*attrs)
pixel_format = NSOpenGLPixelFormat.alloc().initWithAttributes_(attrsArray)
# Return the match list.
if pixel_format is None:
return []
else:
return [CocoaCanvasConfig(canvas, self, pixel_format)]
class CocoaCanvasConfig(CanvasConfig):
def __init__(self, canvas, config, pixel_format):
super(CocoaCanvasConfig, self).__init__(canvas, config)
self._pixel_format = pixel_format
# Query values for the attributes of the pixel format, and then set the
# corresponding attributes of the canvas config.
for name, attr in _gl_attributes.items():
vals = c_int()
self._pixel_format.getValues_forAttribute_forVirtualScreen_(byref(vals), attr, 0)
setattr(self, name, vals.value)
# Set these attributes so that we can run pyglet.info.
for name, value in _fake_gl_attributes.items():
setattr(self, name, value)
def create_context(self, share):
# Determine the shared NSOpenGLContext.
if share:
share_context = share._nscontext
else:
share_context = None
# Create a new NSOpenGLContext.
nscontext = NSOpenGLContext.alloc().initWithFormat_shareContext_(
self._pixel_format,
share_context)
return CocoaContext(self, nscontext, share)
def compatible(self, canvas):
return isinstance(canvas, CocoaCanvas)
class CocoaContext(Context):
def __init__(self, config, nscontext, share):
super(CocoaContext, self).__init__(config, share)
self.config = config
self._nscontext = nscontext
def attach(self, canvas):
super(CocoaContext, self).attach(canvas)
# The NSView instance should be attached to a nondeferred window before calling
# setView, otherwise you get an "invalid drawable" message.
self._nscontext.setView_(canvas.nsview)
self._nscontext.view().setWantsBestResolutionOpenGLSurface_(1)
self.set_current()
def detach(self):
super(CocoaContext, self).detach()
self._nscontext.clearDrawable()
def set_current(self):
self._nscontext.makeCurrentContext()
super(CocoaContext, self).set_current()
def update_geometry(self):
# Need to call this method whenever the context drawable (an NSView)
# changes size or location.
self._nscontext.update()
def set_full_screen(self):
self._nscontext.makeCurrentContext()
self._nscontext.setFullScreen()
def destroy(self):
super(CocoaContext, self).destroy()
self._nscontext.release()
self._nscontext = None
def set_vsync(self, vsync=True):
vals = c_int(vsync)
self._nscontext.setValues_forParameter_(byref(vals), NSOpenGLCPSwapInterval)
def get_vsync(self):
vals = c_int()
self._nscontext.getValues_forParameter_(byref(vals), NSOpenGLCPSwapInterval)
return vals.value
def flip(self):
self._nscontext.flushBuffer()
| [
"mjomdal@gmail.com"
] | mjomdal@gmail.com |
0d3b899d072571d9b6f47263ee86838fd0b208a6 | 6ecc1d05bbd9ca2c1d21322faef076c1f28454db | /chrome/browser/ui/webui/chromeos/login/DEPS | 52acfb6a38a1c062632e3dbccf09ecbcc162ff4b | [
"BSD-3-Clause"
] | permissive | pandareen/chromium | 0e3a9fb92bb9ad027d5b3482a6b03d0bb51c16a1 | 3ea799335afb5178c519f9e12db8b31390375736 | refs/heads/master | 2023-03-14T05:47:29.433132 | 2018-06-27T07:21:08 | 2018-06-27T07:21:08 | 138,843,522 | 0 | 0 | null | 2018-06-27T07:09:52 | 2018-06-27T07:09:52 | null | UTF-8 | Python | false | false | 863 | specific_include_rules = {
# TODO(mash): Fix. https://crbug.com/770866
"core_oobe_handler\.cc": [
"+ash/shell.h",
],
"oobe_display_chooser\.cc": [
"+ash/display/window_tree_host_manager.h",
"+ash/shell.h",
],
# TODO(mash): Fix. https://crbug.com/678990
"signin_screen_handler\.cc": [
"+ash/detachable_base",
"+ash/shell.h",
],
"signin_screen_handler\.h": [
"+ash/detachable_base/detachable_base_observer.h",
],
# Tests.
"oobe_display_chooser_browsertest\.cc": [
"+ash/shell.h",
],
"oobe_display_chooser_unittest.cc": [
"+ash/display/display_configuration_controller.h",
"+ash/shell.h",
"+ash/test/ash_test_base.h",
# TODO(mash): Remove. http://crbug.com/720917.
"+ui/events/devices/device_data_manager.h",
],
"signin_userlist_unittest\.cc": [
"+ash/test/ash_test_base.h"
],
}
| [
"commit-bot@chromium.org"
] | commit-bot@chromium.org | |
9b27fd8e4dbd66e5d9c1bd4174439f8c73cf96dc | fc6909db970d6894e8e2a097e10e7c17ddbaece2 | /tutorials/frontend/from_pytorch.py | 503f64a4e7d90d3d7da7adecd125320c11a3b2aa | [
"Apache-2.0",
"Zlib",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Unlicense",
"BSD-2-Clause"
] | permissive | yagnasrinath/incubator-tvm | e631f9b91943f6780082cebbbe2c26666c3abaf8 | 8b2476fa87cda205daf4bd17d7d58e07a259043c | refs/heads/master | 2021-01-09T12:50:17.506603 | 2020-03-15T09:54:29 | 2020-03-15T09:54:29 | 242,306,771 | 0 | 0 | Apache-2.0 | 2020-02-28T23:20:14 | 2020-02-22T08:29:20 | Python | UTF-8 | Python | false | false | 5,825 | py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
"""
Compile PyTorch Models
======================
**Author**: `Alex Wong <https://github.com/alexwong/>`_
This article is an introductory tutorial to deploy PyTorch models with Relay.
For us to begin with, PyTorch should be installed.
TorchVision is also required since we will be using it as our model zoo.
A quick solution is to install via pip
.. code-block:: bash
pip install torch==1.4.0
pip install torchvision==0.5.0
or please refer to official site
https://pytorch.org/get-started/locally/
PyTorch versions should be backwards compatible but should be used
with the proper TorchVision version.
Currently, TVM supports PyTorch 1.4, 1.3, and 1.2. Other versions may
be unstable.
"""
import tvm
from tvm import relay
import numpy as np
from tvm.contrib.download import download_testdata
from tvm.relay.frontend.pytorch import get_graph_input_names
# PyTorch imports
import torch
import torchvision
######################################################################
# Load a pretrained PyTorch model
# -------------------------------
model_name = 'resnet18'
model = getattr(torchvision.models, model_name)(pretrained=True)
model = model.eval()
# We grab the TorchScripted model via tracing
input_shape = [1, 3, 224, 224]
input_data = torch.randn(input_shape)
scripted_model = torch.jit.trace(model, input_data).eval()
######################################################################
# Load a test image
# -----------------
# Classic cat example!
from PIL import Image
img_url = 'https://github.com/dmlc/mxnet.js/blob/master/data/cat.png?raw=true'
img_path = download_testdata(img_url, 'cat.png', module='data')
img = Image.open(img_path).resize((224, 224))
# Preprocess the image and convert to tensor
from torchvision import transforms
my_preprocess = transforms.Compose([
transforms.Resize(256),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
])
img = my_preprocess(img)
img = np.expand_dims(img, 0)
######################################################################
# Import the graph to Relay
# -------------------------
# Convert PyTorch graph to Relay graph.
input_name = get_graph_input_names(scripted_model)[0] # only one input
shape_dict = {input_name: img.shape}
mod, params = relay.frontend.from_pytorch(scripted_model,
shape_dict)
######################################################################
# Relay Build
# -----------
# Compile the graph to llvm target with given input specification.
target = 'llvm'
target_host = 'llvm'
ctx = tvm.cpu(0)
with relay.build_config(opt_level=3):
graph, lib, params = relay.build(mod,
target=target,
target_host=target_host,
params=params)
######################################################################
# Execute the portable graph on TVM
# ---------------------------------
# Now we can try deploying the compiled model on target.
from tvm.contrib import graph_runtime
dtype = 'float32'
m = graph_runtime.create(graph, lib, ctx)
# Set inputs
m.set_input(input_name, tvm.nd.array(img.astype(dtype)))
m.set_input(**params)
# Execute
m.run()
# Get outputs
tvm_output = m.get_output(0)
#####################################################################
# Look up synset name
# -------------------
# Look up prediction top 1 index in 1000 class synset.
synset_url = ''.join(['https://raw.githubusercontent.com/Cadene/',
'pretrained-models.pytorch/master/data/',
'imagenet_synsets.txt'])
synset_name = 'imagenet_synsets.txt'
synset_path = download_testdata(synset_url, synset_name, module='data')
with open(synset_path) as f:
synsets = f.readlines()
synsets = [x.strip() for x in synsets]
splits = [line.split(' ') for line in synsets]
key_to_classname = {spl[0]:' '.join(spl[1:]) for spl in splits}
class_url = ''.join(['https://raw.githubusercontent.com/Cadene/',
'pretrained-models.pytorch/master/data/',
'imagenet_classes.txt'])
class_name = 'imagenet_classes.txt'
class_path = download_testdata(class_url, class_name, module='data')
with open(class_path) as f:
class_id_to_key = f.readlines()
class_id_to_key = [x.strip() for x in class_id_to_key]
# Get top-1 result for TVM
top1_tvm = np.argmax(tvm_output.asnumpy()[0])
tvm_class_key = class_id_to_key[top1_tvm]
# Convert input to PyTorch variable and get PyTorch result for comparison
with torch.no_grad():
torch_img = torch.from_numpy(img)
output = model(torch_img)
# Get top-1 result for PyTorch
top1_torch = np.argmax(output.numpy())
torch_class_key = class_id_to_key[top1_torch]
print('Relay top-1 id: {}, class name: {}'.format(top1_tvm, key_to_classname[tvm_class_key]))
print('Torch top-1 id: {}, class name: {}'.format(top1_torch, key_to_classname[torch_class_key]))
| [
"noreply@github.com"
] | noreply@github.com |
307b39b476091ab984dde86e503be570839f4667 | 77a7508c3a647711191b924959db80fb6d2bd146 | /src/gamesbyexample/countingquiz.py | 8b3131533dd87c5a56493d1814d27b3cca90f27e | [
"MIT"
] | permissive | surlydev/PythonStdioGames | ff7edb4c8c57a5eb6e2036e2b6ebc7e23ec994e0 | d54c2509c12a5b1858eda275fd07d0edd456f23f | refs/heads/master | 2021-05-22T21:01:15.529159 | 2020-03-26T07:34:10 | 2020-03-26T07:34:10 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,345 | py | """Counting Quiz, by Al Sweigart al@inventwithpython.com
Use multiplication and subtraction to count the number of stars shown
as fast as possible.
Tags: short, math"""
import math, random, time
def main():
print('''Counting Quiz, by Al Sweigart al@inventwithpython.com
Use multiplication and subtraction to count the number of stars shown
as fast as possible. The quiz is 60 seconds long. For example:
* * * * * *
* * * * *
* * * * *
This is a 6 x 3 star field with 2 missing stars.
The answer is 6 x 3 - 2 = 16
''')
while True:
input('Press Enter to begin...')
runQuiz()
print('Would you like to play again? Y/N')
response = input().upper()
if not response.startswith('Y'):
print('Thanks for playing!')
break
def runQuiz():
correct = 0
startTime = time.time()
while time.time() < startTime + 60:
print('\n' * 40) # Clear the screen by printing several newlines.
# Generate the problem and the star field to display:
width = random.randint(1, 10)
height = random.randint(1, 10)
canvas = {}
for x in range(width):
for y in range(height):
canvas[(x, y)] = '*'
numMissing = random.randint(0, math.sqrt(width * height) // 2)
for i in range(numMissing):
while True:
x = random.randint(0, width - 1)
y = random.randint(0, height - 1)
if canvas[(x, y)] == '*':
break
canvas[(x, y)] = ' '
answer = width * height - numMissing
# Display the star field:
for y in range(height):
for x in range(width):
print(canvas[(x, y)] + ' ', end='')
print() # Print a newline.
# Let the player answer and determine if they're right or wrong.
response = input('Enter the number of stars. > ')
if response.isdecimal() and int(response) == answer:
correct += 1
else:
print('Wrong:', answer)
time.sleep(1)
print('Time\'s up!')
print('You were able to count', correct, 'star fields correctly.')
print()
# If the program is run (instead of imported), run the game:
if __name__ == '__main__':
main()
| [
"asweigart@gmail.com"
] | asweigart@gmail.com |
7365f9c8cd8272ff89d5a4395be8d501ab43d64b | 514f11a1e5643459594a90485c93332a3a53a338 | /barf/barf/analysis/basicblock/basicblock.py | a2460e0ef5f0d7dfa4ff9d3839b0abfb3a3e113a | [
"BSD-2-Clause"
] | permissive | ksmaheshkumar/barf-project | b17cdfb3bd9f7eaeabba69ddd1f048d90d3d43ef | f5a4e081b458987676e1abf1f5f54f0ff49133b1 | refs/heads/master | 2021-01-17T21:55:27.477007 | 2015-01-16T14:34:56 | 2015-01-16T14:34:56 | 31,496,855 | 1 | 0 | null | 2015-03-01T13:10:51 | 2015-03-01T13:10:50 | Python | UTF-8 | Python | false | false | 18,362 | py | import bisect
import itertools
import networkx
from Queue import Queue
from pydot import Dot
from pydot import Edge
from pydot import Node
from barf.core.reil import DualInstruction
from barf.core.reil import ReilMnemonic
from barf.core.reil import ReilImmediateOperand
# CFG recovery mode
BARF_DISASM_LINEAR = 0 # linear sweep
BARF_DISASM_RECURSIVE = 1 # recursive descent
BARF_DISASM_MIXED = 2 # linear sweep + recursive descent
verbose = False
class BasicBlock(object):
"""Basic block representation.
"""
def __init__(self):
# List of instruction within the basic block. Each instruction
# is a 'dual' instruction, e.i. it pairs an assembler
# instruction with its REIL translation.
self._instrs = []
# Start address of the basic block.
self._address = None
# Taken branch address. If a basic block ends in a conditional
# instruction, this field has the address of the taken branch
# (condition equals True)
self._taken_branch = None
# Similar to taken branch but it holds the target address of
# the jump when the condition is false.
self._not_taken_branch = None
# If a basic block ends in a direct jump or in an instruction
# different from a conditional jump, this fields holds the
# address of the jump or next instruction.
self._direct_branch = None
@property
def instrs(self):
"""Get basic block instructions.
"""
return self._instrs
@property
def address(self):
"""Get basic block start address.
"""
if self._instrs == []:
return None
return self._instrs[0].address
@property
def start_address(self):
"""Get basic block start address.
"""
if self._instrs is []:
return None
return self._instrs[0].address
@property
def end_address(self):
"""Get basic block end address.
"""
if self._instrs is []:
return None
return self._instrs[-1].address + self._instrs[-1].asm_instr.size - 1
@property
def size(self):
"""Get basic block size.
"""
if self._instrs is []:
return None
return sum([dinstr.asm_instr.size for dinstr in self._instrs])
@property
def taken_branch(self):
"""Get basic block taken branch.
"""
return self._taken_branch
@taken_branch.setter
def taken_branch(self, value):
"""Set basic block taken branch.
"""
self._taken_branch = value
@property
def not_taken_branch(self):
"""Get basic block not taken branch.
"""
return self._not_taken_branch
@not_taken_branch.setter
def not_taken_branch(self, value):
"""Set basic block not taken branch.
"""
self._not_taken_branch = value
@property
def direct_branch(self):
"""Get basic block direct branch.
"""
return self._direct_branch
@direct_branch.setter
def direct_branch(self, value):
"""Set basic block direct branch.
"""
self._direct_branch = value
@property
def branches(self):
"""Get basic block branches.
"""
branches = []
if self._taken_branch:
branches += [(self._taken_branch, 'taken')]
if self._not_taken_branch:
branches += [(self._not_taken_branch, 'not-taken')]
if self._direct_branch:
branches += [(self._direct_branch, 'direct')]
return branches
def contains(self, address):
"""Check if an address is within the range of a basic block.
"""
return address >= self.address and address <= self.end_address
def empty(self):
"""Check if a basic block is empty.
"""
return len(self._instrs) == 0
def __str__(self):
lines = ["Basic Block @ 0x%08x" % (self.address if self.address else 0)]
for instr in self._instrs:
lines += [" %s ; %s" % (str(instr.ir_instrs[0]).ljust(25), str(instr.asm_instr))]
for ir_instr in instr.ir_instrs[1:]:
lines += [" %s" % str(ir_instr)]
return "\n".join(lines)
def __eq__(self, other):
# Assumes that you are comparing basic block from the same binary
return self.address == other.address and self.end_address == other.end_address
def __ne__(self, other):
return not self.__eq__(other)
class BasicBlockGraph(object):
"""Basic block graph representation.
"""
def __init__(self, basic_blocks):
# List of basic blocks.
self._basic_blocks = basic_blocks
# Basic block accessed by address
self._bb_by_addr = dict([(bb.address, bb) for bb in basic_blocks])
# Basic block graph
self._graph = self._build_graph(basic_blocks)
def all_simple_bb_paths(self, start_address, end_address):
"""Return a list of path between start and end address.
"""
bb_start = self._find_basic_block(start_address)
bb_end = self._find_basic_block(end_address)
paths = networkx.all_simple_paths(self._graph, \
source=bb_start.address, target=bb_end.address)
return (map(lambda addr : self._bb_by_addr[addr], path) for path in paths)
def save(self, filename, print_ir=False, format='dot'):
"""Save basic block graph into a file.
"""
node_format = {
'shape' : 'Mrecord',
'rankdir' : 'LR',
'fontname' : 'monospace',
'fontsize' : '9.0'
}
edge_format = {
'fontname' : 'monospace',
'fontsize' : '8.0'
}
edge_colors = {
'taken' : 'green',
'not-taken' : 'red',
'direct' : 'blue'
}
try:
# for each conneted component
for idx, gr in enumerate(networkx.connected_component_subgraphs(self._graph.to_undirected())):
graph = Dot(graph_type="digraph", rankdir="TB")
# add nodes
nodes = {}
for bb_addr in gr.node.keys():
dump = self._dump_bb(self._bb_by_addr[bb_addr], print_ir)
label = "{<f0> 0x%08x | %s}" % (bb_addr, dump)
# html-encode colon character
label = label.replace(":", ":")
nodes[bb_addr] = Node(bb_addr, label=label, **node_format)
graph.add_node(nodes[bb_addr])
# add edges
for bb_src_addr in gr.node.keys():
for bb_dst_addr, branch_type in self._bb_by_addr[bb_src_addr].branches:
graph.add_edge(Edge(nodes[bb_src_addr],
nodes[bb_dst_addr], label=branch_type, \
color=edge_colors[branch_type], **edge_format))
graph.write("%s_%03d.%s" % (filename, idx, format), format=format)
except Exception as err:
import traceback
import sys
print("[E] Error loading BARF (%s:%d) : '%s'" %
(__name__, sys.exc_traceback.tb_lineno, str(err)))
print("")
print(traceback.format_exc())
# Auxiliary functions
# ======================================================================== #
def _build_graph(self, basic_blocks):
graph = networkx.DiGraph()
# add nodes
for bb_addr in self._bb_by_addr.keys():
graph.add_node(bb_addr, address=bb_addr)
# add edges
for bb_src_addr in self._bb_by_addr.keys():
for bb_dst_addr, branch_type in self._bb_by_addr[bb_src_addr].branches:
graph.add_edge(bb_src_addr, bb_dst_addr, branch_type=branch_type)
return graph
def _find_basic_block(self, address):
bb_rv = None
for bb in self._basic_blocks:
if address >= bb.address and address <= bb.end_address:
bb_rv = bb
break
return bb_rv
def _dump_bb(self, basic_block, print_ir=False):
lines = []
base_addr = basic_block.instrs[0].address
for instr in basic_block.instrs:
lines += ["0x%08x (%2d) " % (instr.address, instr.asm_instr.size) + str(instr.asm_instr) + "\\l"]
# lines += ["+%02x " % (instr.address - base_addr) + str(instr.asm_instr) + "\\l"]
# lines += [str(instr.asm_instr) + "\\l"]
if print_ir:
for ir_instr in instr.ir_instrs:
lines += [" " + str(ir_instr) + "\\l"]
return "".join(lines)
@property
def basic_blocks(self):
return self._basic_blocks
class BasicBlockBuilder(object):
"""Basic block builder.
"""
def __init__(self, disassembler, memory, translator):
# An instance of a disassembler.
self._disasm = disassembler
# And instance of a REIL translator.
self._ir_trans = translator
# Maximun number of bytes that gets from memory to disassemble.
self._lookahead_max = 16
# Memory of the program being analyze.
self._mem = memory
def build(self, start_address, end_address):
"""Return the list of basic blocks.
Linear Sweep Disassembly.
@param start_address: Address of the first byte to start disassembling
basic blocks.
@param end_address: Address of the last byte (inclusive) to finish
disassembling basic blocks.
"""
if verbose:
print("[+] Recovering Basic Blocks :")
if verbose:
print(" Finding candidate BBs...")
bbs = self._find_candidate_bbs(start_address, end_address)
if verbose:
print(" %d" % len(bbs))
# print " Number of instrs..."
# asm_count = 0
# ir_count = 0
# for bb in bbs:
# asm_count += len(bb.instrs)
# ir_count += sum(map(lambda i : len(i.ir_instrs), bb.instrs))
# print " asm : %d" % asm_count
# print " ir : %d" % ir_count
if verbose:
print(" Refining BBs...")
bbs = self._refine_bbs(bbs)
if verbose:
print(" %d" % len(bbs))
# print " Checking gaps..."
# for curr, next in zip(bbs[:-1], bbs[1:]):
# if curr.address + curr.size != next.address:
# print "gap found @ %s" % hex(curr.address + curr.size)
if verbose:
print(" Stripping BBs...")
bbs = self._strip_bbs(bbs)
if verbose:
print(" %d" % len(bbs))
if verbose:
print(" Updating branches...")
self._update_branches(bbs)
if verbose:
print(" %d" % len(bbs))
return bbs
def _find_candidate_bbs(self, start_address, end_address, mode=BARF_DISASM_MIXED):
bbs = []
addrs_to_process = Queue()
addrs_processed = set()
addrs_to_process.put(start_address)
while not addrs_to_process.empty():
curr_addr = addrs_to_process.get()
# there no standard way to check if an item is in the queue
# before pushing it in. So, it is necesary to check if the pop
# address have already been processed.
if curr_addr in addrs_processed:
continue
# print "curr_addr : ", hex(curr_addr)
bb = self._disassemble_bb(curr_addr, end_address + 0x1)
if bb.empty():
# print " empty bb"
continue
# print " valid bb"
# add bb to the list
bbs += [bb]
addrs_processed.add(curr_addr)
# linear sweep mode: add next addr to process queue
if mode in [BARF_DISASM_LINEAR, BARF_DISASM_MIXED]:
next_addr = bb.address + bb.size
# print "next_addr : ", hex(next_addr)
if next_addr < end_address and not next_addr in addrs_processed:
addrs_to_process.put(next_addr)
# recursive descent mode: add branches to process queue
if mode in [BARF_DISASM_RECURSIVE, BARF_DISASM_MIXED]:
for addr, branch_type in bb.branches:
if not addr in addrs_processed:
addrs_to_process.put(addr)
return bbs
def _refine_bbs(self, bbs):
bbs.sort(key=lambda x : x.address)
bbs_addrs = map(lambda x : x.address, bbs)
bbs_new = []
for idx, bb1 in enumerate(bbs):
# sys.stdout.write("\r Processing : %d/%d" % (idx, len(bbs)))
# sys.stdout.flush()
bb_divided = False
lower = bisect.bisect_left(bbs_addrs, bb1.start_address)
upper = bisect.bisect_right(bbs_addrs, bb1.end_address)
for bb2 in bbs[lower:upper]:
if bb1.contains(bb2.address) and bb1 != bb2:
# print "split!!", hex(bb2.address)
bba = self._divide_bb(bb1, bb2.address)
if len(bba.instrs) > 0 and bba not in bbs_new:
bbs_new += [bba]
bb_divided = True
break
if not bb_divided:
if bb1 not in bbs_new:
bbs_new += [bb1]
return bbs_new
def _strip_bbs(self, bbs):
return [bb for bb in map(self._strip_bb, bbs) if len(bb.instrs) > 0]
def _update_branches(self, bbs):
bb_addrs = [bb.address for bb in bbs]
for bb in bbs:
if not bb.taken_branch in bb_addrs:
bb.taken_branch = None
if not bb.not_taken_branch in bb_addrs:
bb.not_taken_branch = None
if not bb.direct_branch in bb_addrs:
bb.direct_branch = None
def _strip_bb(self, bb):
# top
while len(bb.instrs) > 0:
if bb.instrs[0].ir_instrs[0].mnemonic == ReilMnemonic.NOP:
del bb.instrs[0]
else:
break
# bottom
while len(bb.instrs) > 0:
if bb.instrs[-1].ir_instrs[0].mnemonic == ReilMnemonic.NOP:
del bb.instrs[-1]
else:
break
return bb
def _divide_bb(self, bb, address):
bb_new = BasicBlock()
for dinstr in bb.instrs:
if dinstr.address == address:
break
bb_new.instrs.append(dinstr)
bb_new.direct_branch = address
return bb_new
def _disassemble_bb(self, start_address, end_address):
bb_current = BasicBlock()
if start_address > end_address:
return bb_current
addr = start_address
taken = None
not_taken = None
direct = None
while addr < end_address:
start, end = addr, min(addr + self._lookahead_max, end_address)
asm, size = self._disasm.disassemble(self._mem[start:end], addr)
if not asm:
break
ir = self._ir_trans.translate(asm)
bb_current.instrs.append(DualInstruction(addr, asm, ir))
# if there is an 'end' instruction process it accordingly
if ir[-1].mnemonic == ReilMnemonic.RET:
break
# TODO: Manage 'call' instruction properly (without
# resorting to 'asm.mnemonic == "call"').
if ir[-1].mnemonic == ReilMnemonic.JCC and not asm.mnemonic == "call":
taken, not_taken, direct = self._extract_branches(addr, asm, size, ir)
break
# if ir[-1].mnemonic == ReilMnemonic.JCC and asm.mnemonic == "call":
# direct_branch = addr + size
# break
# update instruction pointer and iterate
addr += size
bb_current.taken_branch = taken
bb_current.not_taken_branch = not_taken
bb_current.direct_branch = direct
# print "bb addr : ", hex(bb_current.address), " bb end addr : ", hex(bb_current.end_address)
# print " taken :", hex(taken) if taken else ""
# print " not_taken :", hex(not_taken) if not_taken else ""
# print " direct :", hex(direct) if direct else ""
return bb_current
def _resolve_branch_address(self, jmp_instr, instrs):
dst = jmp_instr.operands[2]
if isinstance(dst, ReilImmediateOperand):
# branch address is an immediate
# Transform Reil address back to source arch address
return dst.immediate >> 8
else:
# try to resolve branch address
for instr in instrs[::-1]:
if instr.mnemonic == ReilMnemonic.STR and \
isinstance(instr.operands[0], ReilImmediateOperand) and \
instr.dst == dst:
# Transform Reil address back to source arch address
return instr.operands[0].immediate >> 8
def _extract_branches(self, addr, asm, size, ir):
taken_branch = None
not_taken_branch = None
direct_branch = None
instr_last = ir[-1]
if instr_last.mnemonic == ReilMnemonic.JCC:
cond = instr_last.operands[0]
dst = instr_last.operands[2]
branch_addr = self._resolve_branch_address(instr_last, ir)
# set branch address according to its type
if isinstance(cond, ReilImmediateOperand):
if cond.immediate == 0x0:
taken_branch = addr + size
not_taken_branch = branch_addr
if cond.immediate == 0x1 and asm.mnemonic == 'call':
direct_branch = addr + size
if cond.immediate == 0x1 and asm.mnemonic != 'call':
direct_branch = branch_addr
else:
taken_branch = branch_addr
not_taken_branch = addr + size
return taken_branch, not_taken_branch, direct_branch
| [
"cnheitman@fundacionsadosky.org.ar"
] | cnheitman@fundacionsadosky.org.ar |
ed3a646a75a5bb898ae2f02208dd96258d05759e | da63ecb7ba6afc40731b3b4268f21ed03c882b1b | /src/main/java/jython/toolbar.py | 6c8644b14d882416e83a6e22550ee55dfc5a6d9e | [] | no_license | neopsis/jython-interpreter | 5622dfe58769a3abac6c87119e4f4b581701a03b | 85e6e448acee46dc24deb775f232f8a5d30071a5 | refs/heads/master | 2021-01-09T19:03:00.943500 | 2020-02-22T23:04:38 | 2020-02-22T23:04:38 | 242,421,886 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,491 | py | """
toolbar.py Contains utility classes for toolbar construction
author: Carlos Quiroz
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
"""
from javax.swing import JToolBar, JButton
from java.awt import Insets
from org.gjt.sp.jedit import jEdit, GUIUtilities
class ToolbarHandler(object):
""" Utility class to simplify the toolbar creation process """
def __init__(self, actions = None):
self.actions = actions
def createToolbar(self):
toolBar = JToolBar()
margin = Insets(1,1,1,1)
[self.createButton(toolBar, i, t ,f) for (i,t,f) in self.actions]
return toolBar
def createButton(self, toolBar, i, t, f):
if i == "separator":
toolBar.addSeparator()
else:
b = JButton(icon = GUIUtilities.loadIcon(i), \
toolTipText = jEdit.getProperty(t), actionPerformed = f)
toolBar.add(b)
# :indentSize=4:lineSeparator=\n:noTabs=false:tabSize=4:
| [
"robert@neopsis.com"
] | robert@neopsis.com |
27a6f1c6036145a7c8adf46f99b0c810c9572c18 | 89ddb1c0bd5793964cde9cdf1bb7c622c0662f29 | /strategies/betray.py | 1bb7cbea0d23bc1d1fcf8ad76530b97136f8dbf8 | [] | no_license | evelinag/iterated-prisoners-dilemma | c48958e2e3153f634137fbdca5a13c0ce7a2d664 | b339d69923515cce1184fad7b83fde6a0c5f9f36 | refs/heads/main | 2023-02-27T13:18:53.725466 | 2021-02-11T08:59:14 | 2021-02-11T08:59:14 | 337,871,467 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 147 | py | #!/usr/bin/env python
import sys
while True:
inputs = sys.stdin.readline()
# Always betray the opponent
print("B\n")
sys.stdout.flush()
| [
"evelina@evelinag.com"
] | evelina@evelinag.com |
fdf19265fb0e3cb327ccb42c022c93c96051ef51 | 59db30b968d025fcdf2a01eaad0a93fc5477a5fe | /src/smads_core/interface/robot_sensor_interface.py | 169f5182c24a6bc7086184020b58c5a3b4ae1305 | [
"BSD-3-Clause"
] | permissive | UTSMADS/smads_core | e727b7ecb3d45b93c55eed2dabd82eacd6d952e1 | 546b6bf6d3e31f226664a25153a2a931ce4b5035 | refs/heads/master | 2023-02-19T02:30:31.693606 | 2021-01-15T19:07:12 | 2021-01-15T19:07:12 | 279,627,165 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,406 | py | #!/usr/bin/env python3
import rospy
import sensor_msgs
from nav_msgs.msg import Odometry
from sensor_msgs.msg import LaserScan
from smads_core.client import RobotClient
class RobotSensorInterface:
def __init__(self, client, mutex, poll_rate=10, robot_prefix="smads_platform"):
self.client = client
self.mutex = mutex
self.poll_rate = poll_rate
self.robot_prefix = robot_prefix
self.odom_pub = None
self.scan_pub = None
odom_postfix = rospy.get_param("smads_output_odom_topic")
scan_postfix = rospy.get_param("smads_output_scan_topic")
self.odom_pub = rospy.Publisher(self.robot_prefix + odom_postfix, Odometry, queue_size=10)
self.scan_pub = rospy.Publisher(self.robot_prefix + scan_postfix, LaserScan, queue_size=10)
def poll(self):
r = rospy.Rate(self.poll_rate)
while not rospy.is_shutdown():
scan_data = LaserScan()
odom_data = Odometry()
with self.mutex:
scan_data = self.client.get_laserscan()
odom_data = self.client.get_odom()
self.scan_pub.publish(scan_data)
self.odom_pub.publish(odom_data)
r.sleep()
def start(self):
rospy.loginfo("robot_sensor_interface active")
self.poll()
rospy.loginfo("Polling of Client sensor data stopped.")
| [
"maxsvetlik@gmail.com"
] | maxsvetlik@gmail.com |
d134d707422b4f7133ac34d32cd47be72a95a753 | f0801ad1a4e4097a7026cca8767e88fe74036ea7 | /main/migrations/0001_initial.py | d9a3a1b77e612221874098a8914764b504ec1400 | [] | no_license | meadhikari/django-crm | 4ca446e020f07c50286a4d6debb5ecbf275abb39 | 944319ed0ead8aa1911b8ba2d66b390411972f35 | refs/heads/master | 2021-01-19T13:42:17.014964 | 2017-02-18T19:32:39 | 2017-02-18T19:32:41 | 82,411,094 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,907 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.10.5 on 2017-02-18 09:18
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Customer',
fields=[
('internal_identification_number', models.AutoField(primary_key=True, serialize=False)),
('name', models.CharField(max_length=100, verbose_name='\u0928\u093e\u092e')),
('address', models.CharField(max_length=250, verbose_name='\u0920\u0947\u0917\u093e\u0928\u093e')),
('margh', models.CharField(max_length=100, verbose_name='\u092e\u093e\u0930\u094d\u0917')),
('house_no', models.CharField(max_length=50, verbose_name='\u0918\u0930 \u0928.')),
('barga_fit', models.CharField(max_length=100, verbose_name='\u0935\u0930\u094d\u0917 \u092b\u093f\u091f')),
('land_kitta_number', models.CharField(max_length=100, verbose_name='\u091c\u0917\u094d\u0917\u093e \u0915\u093f. \u0928.')),
('land_area', models.CharField(max_length=100, verbose_name='\u091c\u0917\u094d\u0917\u093e\u0915\u094b \u091a\u0947\u0924\u094d\u0930\u092b\u0932')),
('monthly_fee', models.IntegerField(verbose_name='\u092e\u093e\u0938\u093f\u0915 \u0938\u0941\u0932\u094d\u0915')),
('chetra', models.CharField(choices=[(b'awasiya', '\u0906\u0935\u093e\u0938\u0940\u092f'), (b'angsik_bajar', '\u0905\u0928\u094d\u0917\u094d\u0938\u093f\u0915 \u092c\u091c\u093e\u0930'), (b'bajar', '\u092c\u091c\u093e\u0930'), (b'mukhya_bajar', '\u092e\u0941\u0916\u094d\u092f \u092c\u091c\u093e\u0930')], default=None, max_length=100, verbose_name=b'\xe0\xa4\x95\xe0\xa5\x8d\xe0\xa4\xb7\xe0\xa5\x87\xe0\xa4\xa4\xe0\xa5\x8d\xe0\xa4\xb0 ')),
('batoko_kisim', models.CharField(choices=[(b'kacchi', '\u0915\u091a\u094d\u091a\u0940'), (b'sahayek', '\u0938\u093e\u0939\u092f\u0947\u0915'), (b'pichbato', '\u092a\u0940\u091a\u092c\u093e\u091f\u094b'), (b'mukhya_pichbato', '\u092e\u0941\u0916\u094d\u092f \u092a\u093f\u091a\u092c\u093e\u091f\u094b')], default=None, max_length=100, verbose_name=b'\xe0\xa4\xac\xe0\xa4\xbe\xe0\xa4\x9f\xe0\xa5\x8b \xe0\xa4\x95\xe0\xa5\x8b \xe0\xa4\x95\xe0\xa4\xbf\xe0\xa4\xb8\xe0\xa4\xbf\xe0\xa4\xae')),
('ghar_ko_kisim', models.CharField(choices=[(b'kacchi', '\u0915\u091a\u094d\u091a\u0940'), (b'pakki', '\u092a\u0915\u094d\u0915\u093f')], default=None, max_length=100, verbose_name=b'\xe0\xa4\x98\xe0\xa4\xb0 \xe0\xa4\x95\xe0\xa5\x8b \xe0\xa4\x95\xe0\xa4\xbf\xe0\xa4\xb8\xe0\xa4\xbf\xe0\xa4\xae')),
],
options={
'verbose_name': '\u0917\u094d\u0930\u093e\u0939\u0915 \u092c\u093f\u0935\u0930\u0923',
'verbose_name_plural': '\u0917\u094d\u0930\u093e\u0939\u0915 \u092c\u093f\u0935\u0930\u0923',
},
),
migrations.CreateModel(
name='Payment',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('rasid_number', models.IntegerField(null=True, verbose_name='\u0930\u0938\u093f\u0926 \u0928.')),
('amount', models.IntegerField(verbose_name='\u0930\u0915\u092e')),
('remarks', models.CharField(max_length=300, verbose_name='\u091f\u093f\u092a\u094d\u092a\u0923\u0940')),
('customer', models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='main.Customer')),
],
options={
'verbose_name': '\u092d\u0941\u0915\u094d\u0924\u093e\u0928\u0940',
'verbose_name_plural': '\u092d\u0941\u0915\u094d\u0924\u093e\u0928\u0940',
},
),
]
| [
"salik.adhikari@gmail.com"
] | salik.adhikari@gmail.com |
dd921655e2403677d6faea4bd90156830e7665ee | 1c49952502f7684b5692011b8d9cc4d57886953c | /src/svdslow.py | 7fe28d82fb270d8fc713da9fd202b1298b77ee50 | [] | no_license | mokayy/KDDCup2011 | a5f027ec776aceaafb575076f3445956ed8c2484 | 7390b024d46b2bdb239189c1c9a0d0952915694b | refs/heads/master | 2021-01-14T12:31:35.573557 | 2011-08-09T20:30:22 | 2011-08-09T20:30:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,359 | py | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# vim: ts=4 sts=4 sw=4 tw=79 sta et
"""%prog [options]
Python source code - replace this with a description of the code and write the code below this text.
"""
__author__ = 'Patrick Butler'
__email__ = 'pbutler@killertux.org'
user_t = 'int, int' #ncount, sum
track_t = 'int, int, int, float, float' #id, count, sum, avg, pavg
rating_t = 'int,int,int,int' #user, movie, rating, cache
import os
import numpy as np
import cPickle as pickle
INIT = 0.1
class SVD(object):
def __init__(self, dir, nFeatures = 10):
self.dir = dir
self.tmap = {}
self.nFeatures = nFeatures
stats = open(os.path.join(dir, "info.txt")).readlines()
stats = [ x.strip().split("=") for x in stats]
stats = dict( [ (k,int(v)) for k,v in stats] )
self.stats = stats
self.users = np.ndarray(stats['nUsers'], dtype=user_t)
self.tracks = np.ndarray(stats['nTracks'], dtype=track_t)
trackFile = open(os.path.join(dir, "trackData1.txt"))
tidx = 0
for line in trackFile:
data = line.strip().split("|")
t = int(data[0])
self.tracks[tidx]= (t, 0, 0, 0, 0)
self.tmap[t] = tidx
tidx += 1
trackFile.close()
self.nratings = 0
self.ratings = np.ndarray(int(stats['nRatings']), dtype=rating_t)
trainFile = open(os.path.join(dir, "trainIdx1.txt"))
uidx = 0
ridx = 0
for line in trainFile:
u, n = ( int(a) for a in line.split("|") )
print n
a = 0
for i in range(n):
line = trainFile.next()
id, score, day, time = line.strip().split("\t")
id = int(id)
score = int(score)
if id not in self.tmap:
n -= 1
continue
a += score
id = self.tmap[id]
self.ratings[ridx] = (uidx, id, score, -1)
self.tracks[id][1] += 1
self.tracks[id][1] += score
ridx += 1
if n == 0:
continue
self.users[uidx] = (n, a)
uidx += 1
trainFile.close()
self.users.resize(uidx)
self.ratings.resize(ridx)
for i in range(len(self.tracks)):
n = float(self.tracks[i][1])
tot = float(self.tracks[i][2])
if n == 0:
self.tracks[i][3] = 0
else:
self.tracks[i][3] = tot / n
self.tracks[i][4] = ( ( 50*25 + tot) / (25 + n))
self.initFeatures()
self.save()
def initFeatures(self, nFeatures):
self.nFeatures = nFeatures
nUsers = self.stats['nUsers']
nTracks = self.stats['nTracks']
self.userFeatures = np.zeros(shape=(nFeatures, nUsers), dtype=np.float)
self.trackFeatures = np.zeros(shape=(nFeatures, nTracks), dtype=np.float)
self.userFeatures += INIT
self.trackFeatures += INIT
def __getstate__(self):
odict = self.__dict__.copy()
del odict['ratings']
del odict['tracks']
del odict['users']
del odict['userFeatures']
del odict['trackFeatures']
self.ratings.flush()
self.tracks.flush()
self.users.flush()
return odict
def __setstate__(self, dict):
self.__dict__.update(dict)
def loadmmaps(self):
self.users = np.memmap(os.path.join(self.dir, "user.mmap"), dtype=user_t)
self.ratings = np.memmap(os.path.join(self.dir, "rating.mmap"), dtype=rating_t)
self.tracks = np.memmap(os.path.join(self.dir, "track.mmap"), dtype=track_t)
def save(self):
mmap = np.memmap(os.path.join(self.dir, "rating.mmap"),
dtype=rating_t, shape=self.ratings.shape, mode="w+")
mmap[:] = self.ratings[:]
self.ratings = mmap
mmap = np.memmap(os.path.join(self.dir, "user.mmap"),
dtype=user_t, shape=self.users.shape, mode="w+")
mmap[:] = self.users[:]
self.users = mmap
mmap = np.memmap(os.path.join(self.dir, "track.mmap"),
dtype=track_t, shape=self.tracks.shape, mode="w+")
mmap[:] = self.tracks[:]
self.tracks = mmap
@classmethod
def load(cls, dir, nFeatures = 10):
pklfile = os.path.join(dir, "cache")
svd = pickle.load(open(pklfile))
svd.dir = dir
svd.loadmmaps()
svd.initFeatures(nFeatures)
return svd
def dump(self, file):
pickle.dump(self, open(os.path.join(self.dir, file), "w"), -1)
def train_all(self, nepochs = 10):
shortPredict = self.shortPredict
ratings = self.ratings
userFeatures = self.userFeatures
trackFeatures = self.trackFeatures
for f in range(self.nFeatures):
print "Training Feature %d" % f
for e in range(nepochs):
sq = 0
for r in range(len(ratings)):
u, t, s, c = ratings[r]
p = shortPredict(u, t, f, c, True)
err = s - p
sq += err**2
uf = userFeatures[f, u]
tf = trackFeatures[f, t]
userFeatures[f, u] += .001*(err*tf - .015 * uf)
trackFeatures[f, t] += .001*(err*uf - .015 * tf)
print " epoch=%d RMSE=%f" % (e, (sq/len(ratings))**.5)
for r in range(len(ratings)):
u, t, s, c = ratings[r]
ratings[r][3] = shortPredict(u,t, f, c, False)
def shortPredict(self, user, track, f, cache, trailing):
if f > 0:
sum = cache
else:
sum = self.tracks[track][4]
sum += self.userFeatures[f, user] * self.trackFeatures[f, track]
if sum < 0:
sum = 0
if sum > 100:
sum = 100
if trailing:
sum += INIT*INIT*(self.nFeatures-1-f)
if sum < 0:
sum = 0
if sum > 100:
sum = 100
return sum
def main(args):
import optparse
parser = optparse.OptionParser()
parser.usage = __doc__
parser.add_option("-q", "--quiet",
action="store_false", dest="verbose", default=True,
help="don't print status messages to stdout")
parser.add_option("-l", "--load",
action="store_true", dest="load",
help="load from a cache file")
parser.add_option("-f", "--features",
action="store", type=int, dest="nFeatures", default=10,
help="user nfeatures")
parser.add_option("-e", "--epochs",
action="store", type=int, dest="nepochs", default=10,
help="train through nepochs")
(options, args) = parser.parse_args()
if len(args) < 1:
parser.error("Not enough arguments given")
if options.load:
svd = SVD.load(args[0], options.nFeatures)
else:
svd = SVD(args[0], options.nFeatures)
svd.dump("cache")
svd.train_all(options.nepochs)
return 0
if __name__ == "__main__":
import sys
sys.exit( main( sys.argv ) )
| [
"pbutler@killertux.org"
] | pbutler@killertux.org |
8e71cd84c2bbcff8e95707bae8659fcf81742ad1 | 9fccc0a13c381288d7e3df08a8cb628832e35564 | /rmotr_todo/assignment_4/fixtures/url_overrides/test_able_to_add_items_to_existing_list.py | 49419211e1aed89f402e64ffe713d4e4ef493d38 | [] | no_license | ine-rmotr-projects/wdc-w1-todo-lists | aa2321879a44ed679f0141037c1744f5f130bdb3 | d1a4c291368a7c0d5c9e7de0578705c75d50fea8 | refs/heads/master | 2021-06-18T07:41:06.156750 | 2018-04-06T18:15:14 | 2018-04-06T18:15:14 | 201,114,300 | 0 | 0 | null | 2021-04-20T18:41:26 | 2019-08-07T19:23:56 | Python | UTF-8 | Python | false | false | 279 | py | from django.urls import path
from assignment_4.fixtures import views
urlpatterns = [path('', views.home, name='home'),
path('lists/new', views.new_list, name='new_list'),
path('lists/<list_id>/', views.view_list_doesnt_add_items, name='view_list')] | [
"jason.symons@gmail.com"
] | jason.symons@gmail.com |
40be0ddf55f39cfcc4482a4bd777e333af9190e2 | 8ef8e6818c977c26d937d09b46be0d748022ea09 | /cv/distiller/CWD/pytorch/mmrazor/tests/test_models/test_losses/test_distillation_losses.py | 77233b81fce0cffa1c0bce23a3ba60bdeed31133 | [
"Apache-2.0"
] | permissive | Deep-Spark/DeepSparkHub | eb5996607e63ccd2c706789f64b3cc0070e7f8ef | 9d643e88946fc4a24f2d4d073c08b05ea693f4c5 | refs/heads/master | 2023-09-01T11:26:49.648759 | 2023-08-25T01:50:18 | 2023-08-25T01:50:18 | 534,133,249 | 7 | 6 | Apache-2.0 | 2023-03-28T02:54:59 | 2022-09-08T09:07:01 | Python | UTF-8 | Python | false | false | 8,154 | py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import torch
from mmengine.structures import BaseDataElement
from mmrazor import digit_version
from mmrazor.models import (ABLoss, ActivationLoss, ATLoss, CRDLoss, DKDLoss,
FBKDLoss, FTLoss, InformationEntropyLoss,
KDSoftCELoss, MGDLoss, OFDLoss, OnehotLikeLoss,
PKDLoss)
class TestLosses(TestCase):
@classmethod
def setUpClass(cls):
cls.feats_1d = torch.randn(5, 6)
cls.feats_2d = torch.randn(5, 2, 3)
cls.feats_3d = torch.randn(5, 2, 3, 3)
num_classes = 6
cls.labels = torch.randint(0, num_classes, [5])
def test_ofd_loss(self):
ofd_loss = OFDLoss()
self.normal_test_1d(ofd_loss)
self.normal_test_3d(ofd_loss)
# test the calculation
s_feat_0 = torch.Tensor([[1, 1], [2, 2], [3, 3]])
t_feat_0 = torch.Tensor([[0, 0], [1, 1], [2, 2]])
ofd_loss_num_0 = ofd_loss.forward(s_feat_0, t_feat_0)
assert ofd_loss_num_0 != torch.tensor(0.0)
s_feat_1 = torch.Tensor([[1, 1], [2, 2], [3, 3]])
t_feat_1 = torch.Tensor([[2, 2], [3, 3], [4, 4]])
ofd_loss_num_1 = ofd_loss.forward(s_feat_1, t_feat_1)
assert ofd_loss_num_1 != torch.tensor(0.0)
s_feat_2 = torch.Tensor([[-3, -3], [-2, -2], [-1, -1]])
t_feat_2 = torch.Tensor([[-2, -2], [-1, -1], [0, 0]])
ofd_loss_num_2 = ofd_loss.forward(s_feat_2, t_feat_2)
assert ofd_loss_num_2 == torch.tensor(0.0)
def normal_test_1d(self, loss_instance, labels=False):
args = tuple([self.feats_1d, self.feats_1d])
if labels:
args += (self.labels, )
loss_1d = loss_instance.forward(*args)
self.assertTrue(loss_1d.numel() == 1)
def normal_test_2d(self, loss_instance, labels=False):
args = tuple([self.feats_2d, self.feats_2d])
if labels:
args += (self.labels, )
loss_2d = loss_instance.forward(*args)
self.assertTrue(loss_2d.numel() == 1)
def normal_test_3d(self, loss_instance, labels=False):
args = tuple([self.feats_3d, self.feats_3d])
if labels:
args += (self.labels, )
loss_3d = loss_instance.forward(*args)
self.assertTrue(loss_3d.numel() == 1)
def test_ab_loss(self):
ab_loss_cfg = dict(loss_weight=1.0, margin=1.0)
ab_loss = ABLoss(**ab_loss_cfg)
self.normal_test_1d(ab_loss)
self.normal_test_2d(ab_loss)
self.normal_test_3d(ab_loss)
def _mock_crd_data_sample(self, sample_idx_list):
data_samples = []
for _idx in sample_idx_list:
data_sample = BaseDataElement()
data_sample.set_data(dict(sample_idx=_idx))
data_samples.append(data_sample)
return data_samples
def test_crd_loss(self):
crd_loss = CRDLoss(**dict(neg_num=5, sample_n=10, dim_out=6))
sample_idx_list = torch.tensor(list(range(5)))
data_samples = self._mock_crd_data_sample(sample_idx_list)
loss = crd_loss.forward(self.feats_1d, self.feats_1d, data_samples)
self.assertTrue(loss.numel() == 1)
# test the calculation
s_feat_0 = torch.randn((5, 6))
t_feat_0 = torch.randn((5, 6))
crd_loss_num_0 = crd_loss.forward(s_feat_0, t_feat_0, data_samples)
assert crd_loss_num_0 != torch.tensor(0.0)
s_feat_1 = torch.randn((5, 6))
t_feat_1 = torch.rand((5, 6))
sample_idx_list_1 = torch.tensor(list(range(5)))
data_samples_1 = self._mock_crd_data_sample(sample_idx_list_1)
crd_loss_num_1 = crd_loss.forward(s_feat_1, t_feat_1, data_samples_1)
assert crd_loss_num_1 != torch.tensor(0.0)
def test_dkd_loss(self):
dkd_loss_cfg = dict(loss_weight=1.0)
dkd_loss = DKDLoss(**dkd_loss_cfg)
# dkd requires label logits
self.normal_test_1d(dkd_loss, labels=True)
def test_ft_loss(self):
ft_loss_cfg = dict(loss_weight=1.0)
ft_loss = FTLoss(**ft_loss_cfg)
assert ft_loss.loss_weight == 1.0
self.normal_test_1d(ft_loss)
self.normal_test_2d(ft_loss)
self.normal_test_3d(ft_loss)
def test_dafl_loss(self):
dafl_loss_cfg = dict(loss_weight=1.0)
ac_loss = ActivationLoss(**dafl_loss_cfg, norm_type='abs')
oh_loss = OnehotLikeLoss(**dafl_loss_cfg)
ie_loss = InformationEntropyLoss(**dafl_loss_cfg, gather=False)
# normal test with only one input
loss_ac = ac_loss.forward(self.feats_1d)
self.assertTrue(loss_ac.numel() == 1)
loss_oh = oh_loss.forward(self.feats_1d)
self.assertTrue(loss_oh.numel() == 1)
loss_ie = ie_loss.forward(self.feats_1d)
self.assertTrue(loss_ie.numel() == 1)
with self.assertRaisesRegex(AssertionError,
'"norm_type" must be "norm" or "abs"'):
_ = ActivationLoss(**dafl_loss_cfg, norm_type='random')
# test gather_tensors
ie_loss = InformationEntropyLoss(**dafl_loss_cfg, gather=True)
ie_loss.world_size = 2
if digit_version(torch.__version__) >= digit_version('1.8.0'):
with self.assertRaisesRegex(
RuntimeError,
'Default process group has not been initialized'):
loss_ie = ie_loss.forward(self.feats_1d)
else:
with self.assertRaisesRegex(
AssertionError,
'Default process group is not initialized'):
loss_ie = ie_loss.forward(self.feats_1d)
def test_kdSoftce_loss(self):
kdSoftce_loss_cfg = dict(loss_weight=1.0)
kdSoftce_loss = KDSoftCELoss(**kdSoftce_loss_cfg)
# kd soft ce loss requires label logits
self.normal_test_1d(kdSoftce_loss, labels=True)
def test_at_loss(self):
at_loss_cfg = dict(loss_weight=1.0)
at_loss = ATLoss(**at_loss_cfg)
assert at_loss.loss_weight == 1.0
self.normal_test_1d(at_loss)
self.normal_test_2d(at_loss)
self.normal_test_3d(at_loss)
def test_fbkdloss(self):
fbkdloss_cfg = dict(loss_weight=1.0)
fbkdloss = FBKDLoss(**fbkdloss_cfg)
spatial_mask = torch.randn(1, 1, 3, 3)
channel_mask = torch.randn(1, 4, 1, 1)
channel_pool_adapt = torch.randn(1, 4)
relation_adpt = torch.randn(1, 4, 3, 3)
s_input = (spatial_mask, channel_mask, channel_pool_adapt,
spatial_mask, channel_mask, relation_adpt)
t_input = (spatial_mask, channel_mask, spatial_mask, channel_mask,
relation_adpt)
fbkd_loss = fbkdloss(s_input, t_input)
self.assertTrue(fbkd_loss.numel() == 1)
def test_pkdloss(self):
pkd_loss = PKDLoss(loss_weight=1.0)
feats_S, feats_T = torch.rand(2, 256, 4, 4), torch.rand(2, 256, 4, 4)
loss = pkd_loss(feats_S, feats_T)
self.assertTrue(loss.numel() == 1)
self.assertTrue(0. <= loss <= 1.)
num_stages = 4
feats_S = (torch.rand(2, 256, 4, 4) for _ in range(num_stages))
feats_T = (torch.rand(2, 256, 4, 4) for _ in range(num_stages))
loss = pkd_loss(feats_S, feats_T)
self.assertTrue(loss.numel() == 1)
self.assertTrue(0. <= loss <= num_stages * 1.)
feats_S, feats_T = torch.rand(2, 256, 2, 2), torch.rand(2, 256, 4, 4)
loss = pkd_loss(feats_S, feats_T)
self.assertTrue(loss.numel() == 1)
self.assertTrue(0. <= loss <= 1.)
pkd_loss = PKDLoss(loss_weight=1.0, resize_stu=False)
feats_S, feats_T = torch.rand(2, 256, 2, 2), torch.rand(2, 256, 4, 4)
loss = pkd_loss(feats_S, feats_T)
self.assertTrue(loss.numel() == 1)
self.assertTrue(0. <= loss <= 1.)
def test_mgd_loss(self):
mgd_loss = MGDLoss(alpha_mgd=0.00002)
feats_S, feats_T = torch.rand(2, 256, 4, 4), torch.rand(2, 256, 4, 4)
loss = mgd_loss(feats_S, feats_T)
self.assertTrue(loss.numel() == 1)
| [
"mingjiang.li@iluvatar.ai"
] | mingjiang.li@iluvatar.ai |
1b4a03e0afdaba82763c5ba5b2a63532512388f7 | f38dbe8bcfea76701a6e2759f47b74df07d89a38 | /제01일차/operatorTest01.py | 0aed32af7552d9df0245cce0943e667d632a4751 | [] | no_license | wooowsol/start-Python | 1cd742114d18a2a6639d26d4588f8b64eb40b378 | 8129d85b20dd48ed35f3e3e048f3af8664124e55 | refs/heads/master | 2023-01-23T11:21:02.495162 | 2020-11-22T14:48:23 | 2020-11-22T14:48:23 | 312,837,137 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 963 | py | # operatorTest01.py
# + = * 기호들을 연산라고 합니다.
# 변수 su는 연산의 대상이 되는 것(피연산자)
su = 2 + 3 * 5
print(su)
su = (2 + 3) * 5
print(su)
# =는 대입 연산자라고 합니다.(우선 순위가 꼴찌)
# 비교(관계) 연산자 : > >= < <= ==(같음) !=(다름)
# 연산의 결과 물은 반드시 True 또는 False가 된다.
# 제어문(if, for 구문 등등)에서 많이 사용되므로 중요!!
a = 10
b = 20
result = a >= b
print(result)
result = a < b
print(result)
result = a == b
print(result)
result = a != b
print(result)
# 논리 연산자 : and, or, not
a = 10
b = 20
first = a >= b # False
second = a != b # True
result = first and second # False and True
print(result)
# 연산자 우선 순위 : (), * 또는 /, + 또는 -, 관계 연산, not, and, or, ...대입
third = a == b # False
result = first and second or third
print(result)
result = not(result) # 진위 값 반전
print(result) | [
"71619744+wooowsol@users.noreply.github.com"
] | 71619744+wooowsol@users.noreply.github.com |
b18dd172330c48b377b607fcc29c58bb6995b0b6 | 5334a6e60851087f4eafc1eaf6c2f06c1ac91c7f | /6th_tests/code.py | 5402a3cd76704b72e8520b4951cd453b1b52ee18 | [
"MIT"
] | permissive | zkhodzhaev/fiz_analysis_fitting | fa591f1db02757a09f3ec652a262c499d98386d6 | 1f02d825485e41c7571e62c84719bcd60b711848 | refs/heads/master | 2021-10-26T04:53:26.833652 | 2019-04-10T17:50:04 | 2019-04-10T17:50:04 | 180,633,115 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,629 | py | #!/usr/bin/env python
# coding: utf-8
#Zulfidin Khodzhaev/ zulfidin@inbox.ru
"""For this to work, first 2 lines are deleted,
because the number of column is less than number columns
Example:
Reading Grams weight
2019:4:3
"""
import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
from scipy import stats
df = pd.read_csv("ChocoWeightden6d.txt", delim_whitespace=True)
df.columns = ['time','weight','temp_inside','temp_top','pressure']
df = df.reset_index(drop=True)
df.time = pd.to_timedelta(df.time)
l_array=len(df)
time_array=np.arange(l_array)
n=0
for i in time_array:
time_array[n]=datetime.timedelta.total_seconds(df.time[n]-df.time[0])
n=n+1
time_array=pd.DataFrame(data=time_array)
df_array=pd.concat([time_array,df],axis=1)
df_array = df_array.drop("time", axis=1)
df_array.columns = ['time','weight','temp_inside','temp_top','pressure']
# create the plot space upon which to plot the data
fig, ax = plt.subplots(figsize = (8,8))
slope, intercept, r_value, p_value, std_err = stats.linregress(df_array.time,df_array['weight'])
line = slope*df_array.time+intercept
# add the x-axis and the y-axis to the plot
ax.plot(df_array.time, df_array['weight'],'o', label='original data')
ax.plot(df_array.time, line, label='$y=%.3fx + (%.2f$), [$R^2=%.2f$]' % (slope, intercept, r_value**2))
# rotate tick labels
plt.setp(ax.get_xticklabels(), rotation=45)
# set title and labels for axes
ax.set(xlabel="Time[s]",
ylabel="Weight[g]",
title="ChocoWeightden6d.txt");
ax.legend(loc='best')
plt.savefig('ChocoWeightden6d.png', dpi=600) | [
"noreply@github.com"
] | noreply@github.com |
7979017666ab0ad68c04d752577df8dbe5fcfd11 | 8f273f7499eaf8ad432928714d51cf88a76b0323 | /pa/img.py | f797e9e8412bd1fb6c7feac69156e84f93e71bd4 | [] | no_license | FanNotFan/Python_momgodb | 4abce4a60da36d582947620d604c9cb463722aa5 | 20dc48e38db546b09950af6a2a1bf79578d8a44a | refs/heads/master | 2020-04-28T14:21:16.113631 | 2018-07-13T09:12:39 | 2018-07-13T09:12:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 682 | py | # -*- coding: UTF-8 -*-
# python读取网页的库
import urllib.request
# 正则表达式有关模块
from bs4 import BeautifulSoup
import re
import os
def getHTML(url):
page = urllib.request.urlopen(url)
html = page.read()
return html
def getImag(html):
reg = '<img class="BDE_Image".*?"(.*?)"'
pattern = re.compile(reg)
html = html.decode('utf-8')
imags = re.findall(pattern, html)
t = 1
for img in imags:
urllib.request.urlretrieve(img,r'C:\Users\Administrator\Desktop\go\%s.jpg' % t)
t += 1
print(u'开始保存：', '保存成功')
url = 'https://tieba.baidu.com/p/5629017987'
html = getHTML(url)
getImag(html)
| [
"y1wanghui@163.com"
] | y1wanghui@163.com |
9905b137698c4c8f41b452623054c57528b70709 | f09dc121f213f2881df3572288b7ee5b39246d73 | /aliyun-python-sdk-ddoscoo/aliyunsdkddoscoo/request/v20200101/DeleteAsyncTaskRequest.py | 55e30bb35da17abec88db8989a885f42142441d6 | [
"Apache-2.0"
] | permissive | hetw/aliyun-openapi-python-sdk | 2f31378ad6be0896fb8090423f607e9c7d3ae774 | 7443eacee9fbbaa93c7975c6dbec92d3c364c577 | refs/heads/master | 2023-01-19T22:42:36.214770 | 2020-12-04T10:55:14 | 2020-12-04T10:55:14 | 318,689,093 | 1 | 0 | NOASSERTION | 2020-12-05T03:03:03 | 2020-12-05T03:03:03 | null | UTF-8 | Python | false | false | 1,620 | py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
from aliyunsdkcore.request import RpcRequest
from aliyunsdkddoscoo.endpoint import endpoint_data
class DeleteAsyncTaskRequest(RpcRequest):
def __init__(self):
RpcRequest.__init__(self, 'ddoscoo', '2020-01-01', 'DeleteAsyncTask')
self.set_method('POST')
if hasattr(self, "endpoint_map"):
setattr(self, "endpoint_map", endpoint_data.getEndpointMap())
if hasattr(self, "endpoint_regional"):
setattr(self, "endpoint_regional", endpoint_data.getEndpointRegional())
def get_ResourceGroupId(self):
return self.get_query_params().get('ResourceGroupId')
def set_ResourceGroupId(self,ResourceGroupId):
self.add_query_param('ResourceGroupId',ResourceGroupId)
def get_TaskId(self):
return self.get_query_params().get('TaskId')
def set_TaskId(self,TaskId):
self.add_query_param('TaskId',TaskId) | [
"sdk-team@alibabacloud.com"
] | sdk-team@alibabacloud.com |
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