xuefliang

原版 ./sunny clientid 936abd06debec200 php版 php ./sunny.php --clientid=4ed377963456ee5a op版 opkg install coreutils-nohup nohup /ngrokc -SER[Shost:server.ngrok.cc,Sport:4443,Atoken:a045301f05a5b5f15402ea06fd0be0b8] -AddTun[Type:http,Lhost:127.0.0.1,Lport:80,Sdname:xuefliang] nohup /ngrokc -SER[Shost:server.ngrok.cc,Sport:4443,Atoken:a045301f05a5b5f15402ea06fd0be0b8] -AddTun[Type:tcp,Lhost:127.0.0.1,Lport:22,Rport:63541] python 版https://github.com/hauntek/python-ngrok/ 添入 host = 'server.ngrok.cc' # Ngrok服务器地址 port = 4443 # 端口 bufsize = 1024 # 吞吐量 Tunnels = list() # 全局渠道赋值 body = dict() body['protocol'] = 'http' body['hostname'] = '' body['subdomain'] = 'xuefengliang' body['rport'] = 0 body['lhost'] = '127.0.0.1' body['lport'] = 80 Tunnels.append(body) # 加入渠道队列 host和body['subdomain'] 然后运行 python3 python-ngrok.py 路由器开机启动，exit 0加入 nohup /ngrokc -SER[Shost:server.ng

运行 ”services.msc“ 把图中的Internet Connection Sharing禁用就行了

1 sudo apt install wget screen unzip -y 2 wget -O lamp.zip https://github.com/teddysun/lamp/archive/master.zip unzip lamp.zip cd lamp-master/ chmod +x *.sh 3 screen -S lamp sudo ./lamp.sh

方式一 library(RMySQL) con <- dbConnect(MySQL(),                  user='root',                  password='52332580',                  dbname='douban',                  host="127.0.0.1") dbListTables(con) # 设置编码格式 dbSendQuery(con, "SET NAMES utf8") # 查询数据 query <-  "SELECT * FROM movie" # 提取数据 data <-  dbGetQuery(con, query) # 关闭连接 dbDisconnect(con) 方式二 library(tidyverse) my_db <- src_mysql(dbname="douban",host = "127.0.0.1",port = 3306,user = "root",password = "52332580") my_tbl <- tbl(my_db,"movie") my_tbl%>%select(title,url) 乱码解决方式如下：  1、sudo vim /etc/mysql/my.cnf 添加：  [client] default-character-set=utf8 2、sudo service mysqld restart

sudo apt install libmysqlclient-dev sudo pip install mysql-python

import json fr = open ( "/home/xuefliang/PycharmProjects/Test/xyj.txt" , "r" ) characters = [] stat = {} for line in fr: line = line.split() if len (line) == 0 : continue # print type(line) temp = json.dumps(line, encoding = "UTF-8" , ensure_ascii = False ) result = [t for t in temp][ 2 :- 2 ] for x in xrange ( 0 , len (result)): if not result[x] in characters: characters.append(result[x]) if not stat.has_key(result[x]): stat[result[x]]= 0 stat[result[x]]+= 1 fr.close()

num=[123] b=repr(num) c=[] for x in xrange(1,len(b)-1):     c.append(b[x]) s = u'字符串' L= [c for c in s] import json char=[u'梁雪枫'] temp=json.dumps(char, encoding="UTF-8", ensure_ascii=False) result=[t for t in temp][2:-2]

Linux Mint 加入 IBus libpinyin輸入法 安裝好 Linux Mint 時, 要在 Linux Mint 加入拼音輸入法, 參考步驟如下 : 1) 點擊 選單 > 偏好設定 > 輸入法 : 2) Linux Mint 有提供多種輸入法, 我們選擇安裝 IBus, 所以, 點擊 " 為 IBus 加入支援 " : 3) 之後, 會出現如下畫面, 再同樣位置, 點擊 " 安裝選擇性組件 " : sudo apt install ibus-libpinyin 4) 選擇性組件安裝完畢後, 在輸入法選項中, 選擇 " IBus " : 5) 接下來的步驟, 就是要 在 IBus 裡面加入注音輸入法 , 點擊 選單 > 偏好設定 > iBus 偏好設定 : (p.s. 若安裝好 IBus, 在偏好設定中卻找不到 iBus 偏好設定, 則建議重新啟動 Linux) 6) IBus 因為剛安裝完成, 尚未正式執行, 這時會出現如下畫面, 點擊 " Yes " 啟動 IBus : 7) 開啟 IBus Preferences 畫面後, 切換到 " Input Method ", 然後點擊 " Add ", 選擇 " 漢語 " :

1 sudo proxychains apt-get install nautilus-dropbox 2 proxychains dropbox start -i &

1. Add R repository First, we’ve got to add a line to our /etc/apt/sources.list file. This can be accomplished with the following. Note the “xenial” in the line, indicating Ubuntu 16.04. If you have a different version, just change that. sudo echo "deb http://cran.rstudio.com/bin/linux/ubuntu xenial/" | sudo tee -a /etc/apt/sources.list 2. Add R to Ubuntu Keyring First: gpg --keyserver keyserver.ubuntu.com --recv-key E084DAB9 Then: gpg -a --export E084DAB9 | sudo apt-key add - 3. Install R-Base Most Linux users should be familiar with the old… sudo apt-get update sudo apt-get install r-base r-base-dev 4. sudo apt-get install libfuse-dev libcurl4-openssl-dev libxml++2.6-dev libssl-dev openjdk-8-* libglu1-mesa-dev libgeos-dev libgdal1-dev libproj-dev libfreetype6-dev libgmp-dev libmpfr-dev

sudo apt install python - dev

pythonpath manager 中添加 /usr/local/bin  #ipython 路经 /usr/bin  #python 路经

1 、删除anaconda文件 2、修改.bashrc文件 export PATH="/home/xuefliang/anaconda2/bin:$PATH" 中的/home/xuefliang/anaconda2/bin：删除

1、下载prce的makefile，放在SDK中package中 https://github.com/openwrt/packages/tree/master/libs/pcre 2、make menuconfig选中shadowsocks.保存退出再执行make V=s 即可

1、sudo sh ~/Downloads/crouton -r list 2 sudo sh ~/Downloads/crouton -r xenial -t core 3 sudo enter-chroot 4 sudo apt install vim git python bash-completion proxychains software-properties-common sudo enter-chroot 查看 sudo edit-chroot -a 删除 sudo delete-chroot kde

1、sudo sh ~/Downloads/crouton -r list 2 sudo sh ~/Downloads/crouton -r xenial -t core 3 sudo enter-chroot 4 sudo apt install vim git python bash-completion proxychains software-properties-common sudo enter-chroot 查看 sudo edit-chroot -a 删除 sudo delete-chroot kde

1、sudo atp update 2、sudo apt install hplip vim 3、sudo vim  /etc/cups/cupsd.conf 0.0.0.0:631 < Location  / > Order  allow , deny Allow from  @ Local < / Location >   # Restrict access to the admin pages… < Location  / admin > Order  allow , deny Allow from  @ Local < / Location >   # Restrict access to configuration files… < Location  / admin / conf > AuthType  Default Require  user  @ SYSTEM Order  allow , deny Allow from @ Local < / Location > 4、 sudo service cups start 5、 https://你的树莓派ip:631 6、添加 http://你的树莓派ip:631/printers/打印机名

1、raspberry sudo apt-get install xrdp 2、客户端 sudo apt-get install rdesktop  rdesktop 192.168.10.117

# -*- coding: utf-8 -*- import pandas as pd data = {'Country': ['Belgium', 'India', 'Brazil'],            'Capital': ['Brussels', 'New Delhi', 'Brasília'],            'Population': [11190846, 1303171035, 207847528]} df = pd.DataFrame(data, columns=['Country', 'Capital', 'Population']) s = pd.Series([3, -5, 7, 4], index=['a', 'b', 'c', 'd']) df['Country'] #By Position # Select single value by row & column df.iloc[0,0] df.iat[0,0] #By Label #Select single value by row &  column labels df.loc[0,'Country'] df.at[0, 'Country'] # By Label/Position # Select single row of subset of rows df.ix[2] #Select a single column of  subset of columns df.ix[:,'Capital'] # Select rows and columns df.ix[1,'Capital'] #Boolean Indexing # Series s   where value is not >1 s[~(s > 1)] #s where value i

Sys.setlocale(locale='Chinese') library(readxl) user <- read_excel("C:\\Users\\xuefliang\\Downloads\\vaccine_user_list.xls")

shell sudo enter - chroot sudo python shadowsocks/shadowsocks/local.py -c shadowsocks/ user-config.json -d start

1、git clone https://github.com/breakwa11/gfw_whitelist 2、proxyswither Automatic中填写 file:/home/xuefliang/shadowsocks/shadowsocks/whitelist.pac whitelist.pac中代理地址和端口和实际使用的需要一致

import pandas as pd import numpy as np from sklearn import preprocessing,linear_model,metrics data = pd.DataFrame({'pet': ['cat', 'dog', 'dog', 'fish', 'cat', 'dog', 'cat', 'fish'],                     'children': [4., 6, 3, 3, 2, 3, 5, 4],                     'salary': [90, 24, 44, 27, 32, 59, 36, 27]})                     lb = preprocessing.LabelBinarizer() #标签二值化（Label binarization） #LabelBinarizer通常用于通过一个多类标签（label）列表，创建一个label指示器矩阵 pdlb=pd.DataFrame(lb.fit_transform(data['pet']),columns=['cat','dog','fish']) #横向合并 data=pd.concat([data,pdlb],axis=1) #数据标准化(Standardization or Mean Removal and Variance Scaling) #scale进行标准化缩放的数据均值为0，具有单位方差。 data['children']=preprocessing.scale(data['children']) #数据规范化（Normalization） #把数据集中的每个样本所有数值缩放到(-1,1)之间。 #X_normalized = preprocessing.normalize(X, norm='l2') #二进制化（Binarization） #将数值型数据转化为布尔型的二值数据，可以设置一个阈值

a <- c(1,2,5,6,7) #中位数 median(a) #中位数绝对偏差(median absolute deviation) mad(a) mad() 函数的结果默认乘了一个常数,将constant = 1，就是不乘常数。 MAD就是先求出给定数据的中位数（注意并非均值），然后原数列的每个值与这个中位数求出绝对差，然后再求新数列的中位数，就是 MAD 。 例如 有数列 85 9 6 3 2 3 4 9 显然中位数是 5 ，然后求出绝对差后的数列80 4 1 2 3 2 1 4 所以 MAD 就是 2. 实际上计算mad的过程就是：给定一个向量，先求出中位数，再求出原向量的每一个元素与该中位数的距离，从而得到一个新向量（元素全为大于零的数）。再求这个新向量的中位数。

pip install scikit - learn == 0.18 . rc2   from sklearn.neural_network import MLPClassifier X = [[0., 0.], [1., 1.]] y = [0, 1] clf = MLPClassifier(solver='lbgfs',alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1) clf.fit(X, y) clf.predict([[2., 2.], [-1., -2.]]) 参考文献： http://scikit-learn.org/stable/modules/neural_networks_supervised.html

import numpy as np a = np.array([[1, 2, 3], [4, 5, 6]], float) a.flatten()

sudo vim /usr/share/vim/vimrc ### sudo find / -name '*vimrc' function! AutoPair(open, close)         let line = getline('.')         if col('.') > strlen(line) || line[col('.') - 1] == ' '                 return a:open.a:close."\<ESC>i"         else                 return a:open         endif endf function! ClosePair(char)         if getline('.')[col('.') - 1] == a:char                 return "\<Right>"         else                 return a:char         endif endf function! SamePair(char)         let line = getline('.')         if col('.') > strlen(line) || line[col('.') - 1] == ' '                 return a:char.a:char."\<ESC>i"         elseif line[col('.') - 1] == a:char                 return "\<Right>"         else                 return a:char         endif endf function! RemovePairs()     let l:line = getline(".&

library(caret) #等比例抽样,按照物种分类的变量抽取10%的样本 splitindex <- createDataPartition(iris$Species,times = 1,p = 0.1,list = FALSE) sample <- iris[splitindex,] #亚变量处理 cor(iris[,1:4]) dmy <-dummyVars(~Species,data=iris) result <- data.frame(predict(dmy,newdata = iris)) #Rattle library(rattle) rattle()

sudo apt install flashplugin-installer

forcats forcats 安装 # install.packages("devtools") devtools::install_github("hadley/forcats") ## Skipping install of 'forcats' from a github remote, the SHA1 (004279de) has not changed since last install. ## Use `force = TRUE` to force installation 使用 library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(ggplot2) library(forcats) head(gss_cat) ## # A tibble: 6 × 9 ## year marital age race rincome partyid ## <int> <fctr> <int> <fctr> <fctr> <fctr> ## 1 2000 Never married 26 White $8000 to 9999 Ind,near rep ## 2 2000 Divorced 48 White $8000 to 9999 Not str repub