Git 基本用法與矩陣

Posted on 2017-03-31 by 蕭博元

Git的基本使用

參考來源：

http://gogojimmy.net/2012/01/17/how-to-use-git-1-git-basic/

建立 git user name & email

gitconfig --global user.name "your name"
git config --global user.email "your email"

1 2	gitconfig --global user.name "your name" git config --global user.email "your email"

改顏色

gitconfig --global color.ui true

1	gitconfig --global color.ui true

git clone "https://github.com/mauriceHsiao/untitled2.git"

1	git clone "https://github.com/mauriceHsiao/untitled2.git"

查看 git 狀態

git status

1	git status

(紅色字是第一階段)

gita dd .

gita dd .

把資料add上去

再去看git狀態

(綠色是第二階段)

最後

 gitcommit -v -m "備註"

1	gitcommit -v -m "備註"

就可以成功commit上去

最後查看git狀態

可去查看紀錄

git log

git log

可開啟gui介面

gitk --all

1	gitk --all

看到有哪些 branch

git branch

1	git branch

新增 cat branch

git branch cat

1	git branch cat

切換至cat branch

git checkout cat

1	git checkout cat

切換至 cat後，去修改檔案

查看 git狀態，知道有東西被修改

git add .
git commit -v -m "cat test"

1 2	git add . git commit -v -m "cat test"

commit上去

在cat上看 git log看到 cat test有被commit上去

將某一支 branch 基於另一支 branch 的內容合併起來

git rebase master

1	git rebase master

看 cat與master的差異

git diff cat master

1	git diff cat master

切換至 master

git checkout master

1	git checkout master

將cat所修改的內容 merge到 master

git merge cat

1	git merge cat

所以就可以用 git log 看到 cat test 已經被 merge至 master上

Github:

https://github.com/mauriceHsiao/untitled2/blob/master/0330.py

#coding: utf-8
from __future__ import division
A = [[1, 2, 3], [4, 5, 6]]
B = [[1, 2], [3, 4], [5, 6]]

#coding: utf-8

from __future__ import division

A = [[1, 2, 3], [4, 5, 6]]

B = [[1, 2], [3, 4], [5, 6]]

print "---矩陣---"
def shape(A):
    num_rows = len(A)
    num_cols = len(A[0]) if A else 0
    return num_rows, num_cols

print "---矩陣---"

def shape(A):

num_rows = len(A)

num_cols = len(A[0]) if A else 0

return num_rows, num_cols

defget_row(A, i):
    return A[i]

1 2	defget_row(A, i): return A[i]

defget_column(A, j):
    return [A_i[j] for A_i in A]
&gt;print shape(A)
print get_row(A,0)
print get_column(A,1)

defget_column(A, j):

return [A_i[j] for A_i in A]

>print shape(A)

print get_row(A,0)

print get_column(A,1)

print "---矩陣---"
def make_matrix(num_rows, num_cols, entry_fn):
     return [[entry_fn(i, j) for j in range(num_cols)]
                  for i in range(num_rows)]
defmyfun(i,j):
    return i * j
print make_matrix(3,5,myfun)

print "---矩陣---"

def make_matrix(num_rows, num_cols, entry_fn):

return [[entry_fn(i, j) for j in range(num_cols)]

for i in range(num_rows)]

defmyfun(i,j):

return i * j

print make_matrix(3,5,myfun)

print "---對角矩陣---"
defis_diagonal(i, j):
    return 1 if i == j else 0
identity_matrix = make_matrix(5, 5, is_diagonal)
print identity_matrix

print "---對角矩陣---"

defis_diagonal(i, j):

return 1 if i == j else 0

identity_matrix = make_matrix(5, 5, is_diagonal)

print identity_matrix

print "---5號朋友有哪些---"
friendships = [[0, 1, 1, 0, 0, 0, 0, 0, 0, 0], # user 0
 [1, 0, 1, 1, 0, 0, 0, 0, 0, 0], # user 1
 [1, 1, 0, 1, 0, 0, 0, 0, 0, 0], # user 2
 [0, 1, 1, 0, 1, 0, 0, 0, 0, 0], # user 3
 [0, 0, 0, 1, 0, 1, 0, 0, 0, 0], # user 4
 [0, 0, 0, 0, 1, 0, 1, 1, 0, 0], # user 5
 [0, 0, 0, 0, 0, 1, 0, 0, 1, 0], # user 6
 [0, 0, 0, 0, 0, 1, 0, 0, 1, 0], # user 7
 [0, 0, 0, 0, 0, 0, 1, 1, 0, 1], # user 8
 [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]] # user 9

friends_of_five = [i 
                                for i, is_friend in enumerate(friendships[5]) 
                                if is_friend] 
print friends_of_five

print "---5號朋友有哪些---"

friendships = [[0, 1, 1, 0, 0, 0, 0, 0, 0, 0], # user 0

[1, 0, 1, 1, 0, 0, 0, 0, 0, 0], # user 1

[1, 1, 0, 1, 0, 0, 0, 0, 0, 0], # user 2

[0, 1, 1, 0, 1, 0, 0, 0, 0, 0], # user 3

[0, 0, 0, 1, 0, 1, 0, 0, 0, 0], # user 4

[0, 0, 0, 0, 1, 0, 1, 1, 0, 0], # user 5

[0, 0, 0, 0, 0, 1, 0, 0, 1, 0], # user 6

[0, 0, 0, 0, 0, 1, 0, 0, 1, 0], # user 7

[0, 0, 0, 0, 0, 0, 1, 1, 0, 1], # user 8

[0, 0, 0, 0, 0, 0, 0, 0, 1, 0]] # user 9

friends_of_five = [i

for i, is_friend in enumerate(friendships[5])

if is_friend]

print friends_of_five

print "---兩矩陣相加---"
A1 = [[1, 2, 3], [4, 5, 6]]
B2 = [[7,8,9],[10,11,12]]
defmatrix_add(A, B):
     if shape(A) != shape(B):
         raise ArithmeticError("cannot add matrices with different shapes")
    num_rows, num_cols = shape(A)
    defentry_fn(i, j):
         return A[i][j] + B[i][j]
     return make_matrix(num_rows, num_cols, entry_fn)
print matrix_add(A1,B2)

print "---兩矩陣相加---"

A1 = [[1, 2, 3], [4, 5, 6]]

B2 = [[7,8,9],[10,11,12]]

defmatrix_add(A, B):

if shape(A) != shape(B):

raise ArithmeticError("cannot add matrices with different shapes")

num_rows, num_cols = shape(A)

defentry_fn(i, j):

return A[i][j] + B[i][j]

return make_matrix(num_rows, num_cols, entry_fn)

print matrix_add(A1,B2)

print "---兩矩陣繪圖---"
defdot(v, w):
    return sum(v_i * w_i for v_i, w_i in zip(v, w))
defscalar_multiply(c, v):
    return [c * v_i for v_i in v]
defmake_graph_dot_product_as_vector_projection(plt):
    v = [2, 1]
     w = [math.sqrt(.25), math.sqrt(.75)]
     c = dot(v, w)
    vonw = scalar_multiply(c, w)
     o = [0, 0]
    plt.arrow(0, 0, v[0], v[1],
     width=0.002, head_width=.1, length_includes_head=True)
    plt.annotate("v", v, xytext=[v[0] + 0.1, v[1]])
    plt.arrow(0, 0, w[0], w[1],
     width=0.002, head_width=.1, length_includes_head=True)
    plt.annotate("w", w, xytext=[w[0] - 0.1, w[1]])
    plt.arrow(0, 0, vonw[0], vonw[1], length_includes_head=True)
    plt.annotate(u"(vâ¢w)w", vonw, xytext=[vonw[0] - 0.1, vonw[1] + 0.1])
    plt.arrow(v[0], v[1], vonw[0] - v[0], vonw[1] - v[1],
    linestyle='dotted', length_includes_head=True)
    plt.scatter(*zip(v, w, o), marker='.')
    plt.axis('equal')
    plt.show()
print make_graph_dot_product_as_vector_projection(plt)

print "---兩矩陣繪圖---"

defdot(v, w):

return sum(v_i * w_i for v_i, w_i in zip(v, w))

defscalar_multiply(c, v):

return [c * v_i for v_i in v]

defmake_graph_dot_product_as_vector_projection(plt):

v = [2, 1]

w = [math.sqrt(.25), math.sqrt(.75)]

c = dot(v, w)

vonw = scalar_multiply(c, w)

o = [0, 0]

plt.arrow(0, 0, v[0], v[1],

width=0.002, head_width=.1, length_includes_head=True)

plt.annotate("v", v, xytext=[v[0] + 0.1, v[1]])

plt.arrow(0, 0, w[0], w[1],

width=0.002, head_width=.1, length_includes_head=True)

plt.annotate("w", w, xytext=[w[0] - 0.1, w[1]])

plt.arrow(0, 0, vonw[0], vonw[1], length_includes_head=True)

plt.annotate(u"(vâ¢w)w", vonw, xytext=[vonw[0] - 0.1, vonw[1] + 0.1])

plt.arrow(v[0], v[1], vonw[0] - v[0], vonw[1] - v[1],

linestyle='dotted', length_includes_head=True)

plt.scatter(*zip(v, w, o), marker='.')

plt.axis('equal')

plt.show()

print make_graph_dot_product_as_vector_projection(plt)

print "---ch04課堂報告---"
print "---矩陣相加---"
x = [1,2,3]
y = [4,5,6]
print x+y

 import numpy as np
a = np.array([1, 2, 3])
b = np.array([2, 4, 6])
print a+b

print "---ch04課堂報告---"

print "---矩陣相加---"

x = [1,2,3]

y = [4,5,6]

print x+y

import numpy as np

a = np.array([1, 2, 3])

b = np.array([2, 4, 6])

print a+b

print("---計算向量長度---")
import numpy as np
a=np.array([1,3,2])
b=np.array([-2,1,-1])
la=np.sqrt(a.dot(a))
lb=np.sqrt(b.dot(b))
print (la,lb)

print("---計算向量長度---")

import numpy as np

a=np.array([1,3,2])

b=np.array([-2,1,-1])

la=np.sqrt(a.dot(a))

lb=np.sqrt(b.dot(b))

print (la,lb)

print("---計算cos---")
cos_angle=a.dot(b)/(la*lb)
print (cos_angle)

print("---計算cos---")

cos_angle=a.dot(b)/(la*lb)

print (cos_angle)

print("---計算夾角(單位為π)---")
angle=np.arccos(cos_angle)
print (angle)

print("---計算夾角(單位為π)---")

angle=np.arccos(cos_angle)

print (angle)

angle2=angle*360/2/np.pi
print("----轉換單位為角度----")
print (angle2)

angle2=angle*360/2/np.pi

print("----轉換單位為角度----")

print (angle2)

# 第三個範例
print("----乘法運算----")
print("----矩陣相乘----")
import numpy as np

# 第三個範例

print("----乘法運算----")

print("----矩陣相乘----")

import numpy as np

a = np.array([[3, 4], [2, 3]])
b = np.array([[1, 2], [3, 4]])
c = np.mat([[3, 4], [2, 3]])
d = np.mat([[1, 2], [3, 4]])
e = np.dot(a, b)
f = np.dot(c, d)
print (a * b)
print (c * d)
print (e)
print (f)

a = np.array([[3, 4], [2, 3]])

b = np.array([[1, 2], [3, 4]])

c = np.mat([[3, 4], [2, 3]])

d = np.mat([[1, 2], [3, 4]])

e = np.dot(a, b)

f = np.dot(c, d)

print (a * b)

print (c * d)

print (e)

print (f)

# 第四個範例
print "---亂數產生---"
import numpy as np
a = np.random.randint(1, 10, (3, 5))
print (a)

# 第四個範例

print "---亂數產生---"

import numpy as np

a = np.random.randint(1, 10, (3, 5))

print (a)

# 第五個範例
print "---計算矩陣行列式---"
from numpy import *
a = mat([[1, 2, -1], [3, 0, 1], [4, 2, 1]])
print linalg.det(a)

# 第五個範例

print "---計算矩陣行列式---"

from numpy import *

a = mat([[1, 2, -1], [3, 0, 1], [4, 2, 1]])

print linalg.det(a)

# 第六個範例
print "---矩陣畫圖---"
import numpy as np
from matplotlib import pyplot
x = np.arange(0, 10, 0.1)
y = np.sin(x)
pyplot.plot(x, y)
pyplot.show()

# 第六個範例

print "---矩陣畫圖---"

import numpy as np

from matplotlib import pyplot

x = np.arange(0, 10, 0.1)

y = np.sin(x)

pyplot.plot(x, y)

pyplot.show()

備註：2017/03/30 計算方法與設計-課堂筆記

Protected: Oracle資料庫系統管理 – Oracle環境安裝教學 (OS on Ubuntu)

Posted on 2017-03-22 by 高聖帆

Protected: Oracle資料庫系統管理 – Oracle指令介紹

Posted on 2017-03-22 by 高聖帆

Protected: Oracle資料庫系統管理 – Ubuntu中連線docker環境與Oracle指令

Posted on 2017-03-22 by 高聖帆

建立自己的docker registry

Posted on 2017-03-20 by 小胡

ref: http://www.informit.com/articles/article.aspx?p=2464012
01. Private Docker Hub
sudo docker run -d -p 5000:5000 registry
sudo docker tag hu/oracle localhost:5000/ora11g:latest
sudo docker push localhost:5000/ora11g:latest

02.
sudo docker ps -a (list all container)
sudo docker stop (container-id)
sudo docker rm (stop container id)
sudo docker images (list all images)
sudo docker rmi (image-id)

Python 基本語法-3與matplotlib應用

Posted on 2017-03-20 by 蕭博元

#python2

# coding=utf-8 # 讓python轉型成utf-8，支援中文

# Set應用，查詢快、不重複
 print "---Set應用---"
 s = set()
 s.add(1)
 s.add(2)
 s.add(2)
 x = len(s)
 y = 2 in s
 z = 3 in s
 print "x = " + str(x) # 2
 print "y = " + str(y) # True
 print "z = " + str(z) # False

# coding=utf-8 # 讓python轉型成utf-8，支援中文

# Set應用，查詢快、不重複

print "---Set應用---"

s = set()

s.add(1)

s.add(2)

x = len(s)

y = 2 in s

z = 3 in s

print "x = " + str(x) # 2

print "y = " + str(y) # True

print "z = " + str(z) # False

stopwords_list = ["a","an","at"] + ["yet", "you"] + ["yet", "you"]
 # list 可用來比對每一個值
 print "zip in stopwords_list = "+str(zip in stopwords_list)
 stopwords_set = set(stopwords_list)
 # Set 速度較快，若要測驗裡面有沒有，用set比較快
 print "zip in stopwords_set = "+str(zip in stopwords_set)

stopwords_list = ["a","an","at"] + ["yet", "you"] + ["yet", "you"]

# list 可用來比對每一個值

print "zip in stopwords_list = "+str(zip in stopwords_list)

stopwords_set = set(stopwords_list)

# Set 速度較快，若要測驗裡面有沒有，用set比較快

print "zip in stopwords_set = "+str(zip in stopwords_set)

print "---list與Set個數不同---"
 item_list = [1, 2, 3, 1, 2, 3]
 num_items = len(item_list) # 6
 item_set = set(item_list) # {1, 2, 3}
 num_distinct_items = len(item_set) # 3
 distinct_item_list = list(item_set) # [1, 2, 3]
 print "num_items = "+str(num_items) # 用list個數為6個
 print "item_set = "+str(item_set)
 print "num_distinct_items = " + str(num_distinct_items) # Set個數為3個，因為set不重復
 print "distinct_item_list = " + str(distinct_item_list)

print "---list與Set個數不同---"

item_list = [1, 2, 3, 1, 2, 3]

num_items = len(item_list) # 6

item_set = set(item_list) # {1, 2, 3}

num_distinct_items = len(item_set) # 3

distinct_item_list = list(item_set) # [1, 2, 3]

print "num_items = "+str(num_items) # 用list個數為6個

print "item_set = "+str(item_set)

print "num_distinct_items = " + str(num_distinct_items) # Set個數為3個，因為set不重復

print "distinct_item_list = " + str(distinct_item_list)

 # Control Flow
 print "---判斷機偶數，if寫法---"
 x=2
 parity = "even" if x % 2 == 0 else "odd"
 print "x =" +str(x)+", and parity = "+parity

# Control Flow

print "---判斷機偶數，if寫法---"

x=2

parity = "even" if x % 2 == 0 else "odd"

print "x =" +str(x)+", and parity = "+parity

# while。倘若說網路連線、email等等，建議不要用，會占用CPU
 # 假如跑資料迴圈可以，因為會在記憶體中執行
 print "---while迴圈---"
 x = 0
 while x &lt; 10:
 print x, "is less than 10"
 x += 1

# while。倘若說網路連線、email等等，建議不要用，會占用CPU

# 假如跑資料迴圈可以，因為會在記憶體中執行

print "---while迴圈---"

x = 0

while x < 10:

print x, "is less than 10"

x += 1

print "---for迴圈---"
 for x in range(10):
 print x, "is less than 10"

print "---for迴圈---"

for x in range(10):

print x, "is less than 10"

# sorted 或 sort基本上依樣，但sorted(x) x內容不會改變，x.sort()才會改變
 print "---sorted排序---"
 x = [4,1,2,3]
 print x
 y = sorted(x) # is [1,2,3,4], x is unchanged
 x.sort() # now x is [1,2,3,4]
 print y

# sorted 或 sort基本上依樣，但sorted(x) x內容不會改變，x.sort()才會改變

print "---sorted排序---"

x = [4,1,2,3]

print x

y = sorted(x) # is [1,2,3,4], x is unchanged

x.sort() # now x is [1,2,3,4]

print y

# list應用
 print "---list應用---"
 even_numbers = [x for x in range(5) if x % 2 == 0] # [0, 2, 4]
 squares = [x * x for x in range(5)] # [0, 1, 4, 9, 16]
 even_squares = [x * x for x in even_numbers] # [0, 4, 16]
 print even_numbers,",",squares,",",even_squares

# list應用

print "---list應用---"

even_numbers = [x for x in range(5) if x % 2 == 0] # [0, 2, 4]

squares = [x * x for x in range(5)] # [0, 1, 4, 9, 16]

even_squares = [x * x for x in even_numbers] # [0, 4, 16]

print even_numbers,",",squares,",",even_squares

square_dict = { x : x * x for x in range(5) } # { 0:0, 1:1, 2:4, 3:9, 4:16 }
 square_set = { x * x for x in [1, -1] } # { 1 }
 print square_dict,",",square_set

square_dict = { x : x * x for x in range(5) } # { 0:0, 1:1, 2:4, 3:9, 4:16 }

square_set = { x * x for x in [1, -1] } # { 1 }

print square_dict,",",square_set

# Generators 產生器
 print "---Generators and Iterators---"
 import time
 def lazy_range(n):
     i = 0
     while i &lt; n:
         time.sleep(i/2)
         yield i
         i += 1
 for i in lazy_range(10):
     print (i)

# Generators 產生器

print "---Generators and Iterators---"

import time

def lazy_range(n):

i = 0

while i < n:

time.sleep(i/2)

yield i

i += 1

for i in lazy_range(10):

print (i)

# 亂數應用
 print "---random亂數---"
 import random
 four_uniform_randoms = [random.random() for _ in range(4)]
 print four_uniform_randoms

# 亂數應用

print "---random亂數---"

import random

four_uniform_randoms = [random.random() for _ in range(4)]

print four_uniform_randoms

# 用日期給予seed值，讓亂數每次跑的都不一樣
 print "---亂數seed種子---"
 import datetime
 random.seed(datetime.datetime.now())
 print random.random()
 random.seed(10)
 print random.random()

# 用日期給予seed值，讓亂數每次跑的都不一樣

print "---亂數seed種子---"

import datetime

random.seed(datetime.datetime.now())

print random.random()

random.seed(10)

print random.random()

# 用randrange固定亂數的範圍
 print "---randrange固定亂數---"
 print random.randrange(10)

# 用randrange固定亂數的範圍

print "---randrange固定亂數---"

print random.randrange(10)

# 用shuffle讓他跑出不重複的亂數值
 print "---shuffle不重複的亂數值---"
 up_to_ten = range(5,11)
 random.shuffle(up_to_ten)
 print up_to_ten

# 用shuffle讓他跑出不重複的亂數值

print "---shuffle不重複的亂數值---"

up_to_ten = range(5,11)

random.shuffle(up_to_ten)

print up_to_ten

print "---choice---"
 my_lunch = random.choice(["7-11","KFC","Macdonald"])
 print my_lunch

print "---choice---"

my_lunch = random.choice(["7-11","KFC","Macdonald"])

print my_lunch

print "---rand取多個---"
 lottery_numbers = range(60)
 winning_numbers = random.sample(lottery_numbers, 6)
 print winning_numbers

print "---rand取多個---"

lottery_numbers = range(60)

winning_numbers = random.sample(lottery_numbers, 6)

print winning_numbers

print "---取多個，但會重複---"
 four_with_replacement = [random.choice(range(10))
 for _ in range(4)]
 print four_with_replacement

print "---取多個，但會重複---"

four_with_replacement = [random.choice(range(10))

for _ in range(4)]

print four_with_replacement

print "---Regular Expressions正規表達式---"
 import re
 print all([ # all of these are true, because
 not re.match("a", "cat"), # * 'cat' doesn't start with 'a'
 re.search("a", "cat"), # * 'cat' has an 'a' in it
 not re.search("c", "dog"), # * 'dog' doesn't have a 'c' in it
 3 == len(re.split("[ab]", "carbs")), # a,b做切割['c','r','s']
 "R-D-" == re.sub("[0-9]", "*", "R2D2") # 做取代
 ]) # prints True

print "---Regular Expressions正規表達式---"

import re

print all([ # all of these are true, because

not re.match("a", "cat"), # * 'cat' doesn't start with 'a'

re.search("a", "cat"), # * 'cat' has an 'a' in it

not re.search("c", "dog"), # * 'dog' doesn't have a 'c' in it

3 == len(re.split("[ab]", "carbs")), # a,b做切割['c','r','s']

"R-D-" == re.sub("[0-9]", "*", "R2D2") # 做取代

]) # prints True

print "---Line Chart---"
 from matplotlib import pyplot as plt
 years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]
 gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]
 # create a line chart, years on x-axis, gdp on y-axis
 plt.plot(years, gdp, color='green', marker='o', linestyle='solid')
 # add a title
 plt.title("Nominal GDP")
 # add a label to the y-axis
 plt.ylabel("Billions of $")
 plt.show()

print "---Line Chart---"

from matplotlib import pyplot as plt

years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]

gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]

# create a line chart, years on x-axis, gdp on y-axis

plt.plot(years, gdp, color='green', marker='o', linestyle='solid')

# add a title

plt.title("Nominal GDP")

# add a label to the y-axis

plt.ylabel("Billions of $")

plt.show()

print "---Bar Chart---"
 movies = ["Annie Hall", "Ben-Hur", "Casablanca", "Gandhi", "West Side Story"]
 num_oscars = [5, 11, 3, 8, 10]
 # bars are by default width 0.8, so we'll add 0.1 to the left coordinates
 # so that each bar is centered
 xs = [i + 0.1 for i, _ in enumerate(movies)]
 # plot bars with left x-coordinates [xs], heights [num_oscars]
 plt.bar(xs, num_oscars)
 plt.ylabel("# of Academy Awards")
 plt.title("My Favorite Movies")
 # label x-axis with movie names at bar centers
 plt.xticks([i + 0.5 for i, _ in enumerate(movies)], movies)
 plt.show()

print "---Bar Chart---"

movies = ["Annie Hall", "Ben-Hur", "Casablanca", "Gandhi", "West Side Story"]

num_oscars = [5, 11, 3, 8, 10]

# bars are by default width 0.8, so we'll add 0.1 to the left coordinates

# so that each bar is centered

xs = [i + 0.1 for i, _ in enumerate(movies)]

# plot bars with left x-coordinates [xs], heights [num_oscars]

plt.bar(xs, num_oscars)

plt.ylabel("# of Academy Awards")

plt.title("My Favorite Movies")

# label x-axis with movie names at bar centers

plt.xticks([i + 0.5 for i, _ in enumerate(movies)], movies)

plt.show()

print "---Bar Chart---"
 from collections import Counter
 grades = [83,95,91,87,70,0,85,82,100,67,73,77,0]
 decile = lambda grade: grade // 10 * 10
 histogram = Counter(decile(grade) for grade in grades)
 plt.bar([x for x in histogram.keys()], # shift each bar to the left by 4
 histogram.values(), # give each bar its correct height
 8) # give each bar a width of 8
 plt.axis([-5, 105, 0, 5]) # x-axis from -5 to 105,
 # y-axis from 0 to 5
 plt.xticks([10 * i for i in range(11)]) # x-axis labels at 0, 10, ..., 100
 plt.xlabel("Decile")
 plt.ylabel("# of Students")
 plt.title("Distribution of Exam 1 Grades")
 plt.show()

print "---Bar Chart---"

from collections import Counter

grades = [83,95,91,87,70,0,85,82,100,67,73,77,0]

decile = lambda grade: grade // 10 * 10

histogram = Counter(decile(grade) for grade in grades)

plt.bar([x for x in histogram.keys()], # shift each bar to the left by 4

histogram.values(), # give each bar its correct height

8) # give each bar a width of 8

plt.axis([-5, 105, 0, 5]) # x-axis from -5 to 105,

# y-axis from 0 to 5

plt.xticks([10 * i for i in range(11)]) # x-axis labels at 0, 10, ..., 100

plt.xlabel("Decile")

plt.ylabel("# of Students")

plt.title("Distribution of Exam 1 Grades")

plt.show()

print "---Bar Chart---"
 mentions = [500, 505]
 years = [2013, 2014]
 plt.bar(years, mentions, 0.8)
 plt.xticks(years)
 plt.ylabel("# of times I heard someone say 'data science'")
 # if you don't do this, matplotlib will label the x-axis 0, 1
 # and then add a +2.013e3 off in the corner (bad matplotlib!)
 plt.ticklabel_format(useOffset=False)
 # misleading y-axis only shows the part above 500
 plt.axis([2012.5,2014.5,499,506]) # 刻度要設小一點才看得比較明顯
 plt.title("Look at the 'Huge' Increase!")
 plt.show()

print "---Bar Chart---"

mentions = [500, 505]

years = [2013, 2014]

plt.bar(years, mentions, 0.8)

plt.xticks(years)

plt.ylabel("# of times I heard someone say 'data science'")

# if you don't do this, matplotlib will label the x-axis 0, 1

# and then add a +2.013e3 off in the corner (bad matplotlib!)

plt.ticklabel_format(useOffset=False)

# misleading y-axis only shows the part above 500

plt.axis([2012.5,2014.5,499,506]) # 刻度要設小一點才看得比較明顯

plt.title("Look at the 'Huge' Increase!")

plt.show()

print "---Line Chart---"
 variance = [1, 2, 4, 8, 16, 32, 64, 128, 256]
 bias_squared = [256, 128, 64, 32, 16, 8, 4, 2, 1]
 total_error = [x + y for x, y in zip(variance, bias_squared)]
 xs = [i for i, _ in enumerate(variance)]
 # we can make multiple calls to plt.plot
 # to show multiple series on the same chart
 plt.plot(xs, variance, 'g-', label='variance') # green solid line
 plt.plot(xs, bias_squared, 'r-.', label='bias^2') # red dot-dashed line
 plt.plot(xs, total_error, 'b:', label='total error') # blue dotted line
 # because we've assigned labels to each series
 # we can get a legend for free
 # loc=9 means "top center"
 plt.legend(loc=9)
 plt.xlabel("model complexity")
 plt.title("The Bias-Variance Tradeoff")
 plt.show()

print "---Line Chart---"

variance = [1, 2, 4, 8, 16, 32, 64, 128, 256]

bias_squared = [256, 128, 64, 32, 16, 8, 4, 2, 1]

total_error = [x + y for x, y in zip(variance, bias_squared)]

xs = [i for i, _ in enumerate(variance)]

# we can make multiple calls to plt.plot

# to show multiple series on the same chart

plt.plot(xs, variance, 'g-', label='variance') # green solid line

plt.plot(xs, bias_squared, 'r-.', label='bias^2') # red dot-dashed line

plt.plot(xs, total_error, 'b:', label='total error') # blue dotted line

# because we've assigned labels to each series

# we can get a legend for free

# loc=9 means "top center"

plt.legend(loc=9)

plt.xlabel("model complexity")

plt.title("The Bias-Variance Tradeoff")

plt.show()

print "---Scatterplots散點圖---"
 friends = [ 70, 65, 72, 63, 71, 64, 60, 64, 67]
 minutes = [175, 170, 205, 120, 220, 130, 105, 145, 190]
 labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i']
 plt.scatter(friends, minutes)
 # label each point
 for label, friend_count, minute_count in zip(labels, friends, minutes):
 plt.annotate(label,
 xy=(friend_count, minute_count), # put the label with its point
 xytext=(5, -5), # but slightly offset
 textcoords='offset points')
 plt.title("Daily Minutes vs. Number of Friends")
 plt.xlabel("# of friends")
 plt.ylabel("daily minutes spent on the site")
 #plt.axis('equal') # 轉橫式
 plt.show()

print "---Scatterplots散點圖---"

friends = [ 70, 65, 72, 63, 71, 64, 60, 64, 67]

minutes = [175, 170, 205, 120, 220, 130, 105, 145, 190]

labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i']

plt.scatter(friends, minutes)

# label each point

for label, friend_count, minute_count in zip(labels, friends, minutes):

plt.annotate(label,

xy=(friend_count, minute_count), # put the label with its point

xytext=(5, -5), # but slightly offset

textcoords='offset points')

plt.title("Daily Minutes vs. Number of Friends")

plt.xlabel("# of friends")

plt.ylabel("daily minutes spent on the site")

#plt.axis('equal') # 轉橫式

plt.show()

備註：2017/03/16 計算方法分析與設計-課程筆記

Python基本語法-2

Posted on 2017-03-20 by 蕭博元

#python2

# coding=utf-8 # 讓python轉型成utf-8，支援中文
from collections import Counter
from collections import defaultdict

# coding=utf-8 # 讓python轉型成utf-8，支援中文

from collections import Counter

from collections import defaultdict

salaries_and_tenures資料集

salaries_and_tenures = [(83000, 8.7), (88000, 8.1),
 (48000, 0.7), (76000, 6),
 (69000, 6.5), (76000, 7.5),
 (60000, 2.5), (83000, 10),
 (48000, 1.9), (63000, 4.2),(100000,2.5)]

salaries_and_tenures = [(83000, 8.7), (88000, 8.1),

(48000, 0.7), (76000, 6),

(69000, 6.5), (76000, 7.5),

(60000, 2.5), (83000, 10),

(48000, 1.9), (63000, 4.2),(100000,2.5)]

# 從salaries_and_tenures中取出salary與tenure
 print "---salary_by_tenure---"
 salary_by_tenure = defaultdict(list)
 for salary, tenure in salaries_and_tenures:
 salary_by_tenure[tenure].append(salary)
 print salary_by_tenure

# 從salaries_and_tenures中取出salary與tenure

print "---salary_by_tenure---"

salary_by_tenure = defaultdict(list)

for salary, tenure in salaries_and_tenures:

salary_by_tenure[tenure].append(salary)

print salary_by_tenure

# 從salaries_and_tenures中取出薪資與筆數，並算出平均
 print "---average_salary_by_tenure---"
 average_salary_by_tenure = {
                             tenure : sum(salaries) / len(salaries)
                             for tenure, salaries in salary_by_tenure.items()
                            }
 print average_salary_by_tenure

# 從salaries_and_tenures中取出薪資與筆數，並算出平均

print "---average_salary_by_tenure---"

average_salary_by_tenure = {

tenure : sum(salaries) / len(salaries)

for tenure, salaries in salary_by_tenure.items()

}

print average_salary_by_tenure

# 將資料做分群，小於2，小於5，大於5
 # 用迴圈去跑這兩個門檻值(2,5)
 print "---tenure_bucket---"
 def tenure_bucket(tenure):
     if tenure &lt; 2:
         return "less than two"
     elif tenure &lt; 5:
         return "between two and five"
     else:
         return "more than five"
 print tenure_bucket(5.5)

# 將資料做分群，小於2，小於5，大於5

# 用迴圈去跑這兩個門檻值(2,5)

print "---tenure_bucket---"

def tenure_bucket(tenure):

if tenure < 2:

return "less than two"

elif tenure < 5:

return "between two and five"

else:

return "more than five"

print tenure_bucket(5.5)

# 把資料讀出來並做分群
 print "---salary_by_tenure_bucket---"
 salary_by_tenure_bucket = defaultdict(list)
 for salary, tenure in salaries_and_tenures:
     bucket = tenure_bucket(tenure)
     salary_by_tenure_bucket[bucket].append(salary) # {tennure_bucket:[salary]}
 print salary_by_tenure_bucket

# 把資料讀出來並做分群

print "---salary_by_tenure_bucket---"

salary_by_tenure_bucket = defaultdict(list)

for salary, tenure in salaries_and_tenures:

bucket = tenure_bucket(tenure)

salary_by_tenure_bucket[bucket].append(salary) # {tennure_bucket:[salary]}

print salary_by_tenure_bucket

# 將剛剛分群後的資料取出來做平均
 print "---average_salary_by_bucket---"
 average_salary_by_bucket = {
                             tenure_bucket : sum(salaries) / len(salaries)
                             for tenure_bucket, salaries in salary_by_tenure_bucket.iteritems()
                            }
 print average_salary_by_bucket

# 將剛剛分群後的資料取出來做平均

print "---average_salary_by_bucket---"

average_salary_by_bucket = {

tenure_bucket : sum(salaries) / len(salaries)

for tenure_bucket, salaries in salary_by_tenure_bucket.iteritems()

}

print average_salary_by_bucket

interests資料集

interests = [
 (0, "Hadoop"), (0, "Big Data"), (0, "HBase"), (0, "Java"),
 (0, "Spark"), (0, "Storm"), (0, "Cassandra"),
 (1, "NoSQL"), (1, "MongoDB"), (1, "Cassandra"), (1, "HBase"),
 (1, "Postgres"), (2, "Python"), (2, "scikit-learn"), (2, "scipy"),
 (2, "numpy"), (2, "statsmodels"), (2, "pandas"), (3, "R"), (3, "Python"),
 (3, "statistics"), (3, "regression"), (3, "probability"),
 (4, "machine learning"), (4, "regression"), (4, "decision trees"),
 (4, "libsvm"), (5, "Python"), (5, "R"), (5, "Java"), (5, "C++"),
 (5, "Haskell"), (5, "programming languages"), (6, "statistics"),
 (6, "probability"), (6, "mathematics"), (6, "theory"),
 (7, "machine learning"), (7, "scikit-learn"), (7, "Mahout"),
 (7, "neural networks"), (8, "neural networks"), (8, "deep learning"),
 (8, "Big Data"), (8, "artificial intelligence"), (9, "Hadoop"),
 (9, "Java"), (9, "MapReduce"), (9, "Big Data")
 ]

interests = [

(0, "Hadoop"), (0, "Big Data"), (0, "HBase"), (0, "Java"),

(0, "Spark"), (0, "Storm"), (0, "Cassandra"),

(1, "NoSQL"), (1, "MongoDB"), (1, "Cassandra"), (1, "HBase"),

(1, "Postgres"), (2, "Python"), (2, "scikit-learn"), (2, "scipy"),

(2, "numpy"), (2, "statsmodels"), (2, "pandas"), (3, "R"), (3, "Python"),

(3, "statistics"), (3, "regression"), (3, "probability"),

(4, "machine learning"), (4, "regression"), (4, "decision trees"),

(4, "libsvm"), (5, "Python"), (5, "R"), (5, "Java"), (5, "C++"),

(5, "Haskell"), (5, "programming languages"), (6, "statistics"),

(6, "probability"), (6, "mathematics"), (6, "theory"),

(7, "machine learning"), (7, "scikit-learn"), (7, "Mahout"),

(7, "neural networks"), (8, "neural networks"), (8, "deep learning"),

(8, "Big Data"), (8, "artificial intelligence"), (9, "Hadoop"),

(9, "Java"), (9, "MapReduce"), (9, "Big Data")

]

# 把interests指派成user,interest，再轉成英文字小寫在做split()切割
 print "---words_and_counts---"
 words_and_counts = Counter(word
                            for user, interest in interests
                            for word in interest.lower().split())
 # 將剛剛words_and_counts的key,value取出來，並計算次數
 for word, count in words_and_counts.most_common():
     if count &gt; 1:
         print word, count

# 把interests指派成user,interest，再轉成英文字小寫在做split()切割

print "---words_and_counts---"

words_and_counts = Counter(word

for user, interest in interests

for word in interest.lower().split())

# 將剛剛words_and_counts的key,value取出來，並計算次數

for word, count in words_and_counts.most_common():

if count > 1:

print word, count

“—————————-第二章—————————-“

from __future__ import division

# 計算1-5與1-5做相加
 print "---計算相加---"
 for i in [1, 2, 3, 4, 5]:
     for j in [1, 2, 3, 4, 5]:
         print i, " + ", j," = ",(i + j)
 print "done looping"

from __future__ import division

# 計算1-5與1-5做相加

print "---計算相加---"

for i in [1, 2, 3, 4, 5]:

for j in [1, 2, 3, 4, 5]:

print i, " + ", j," = ",(i + j)

print "done looping"

# 正規表達式
 # https://dotblogs.com.tw/johnny/2010/01/25/13301

1 2	# 正規表達式 # https://dotblogs.com.tw/johnny/2010/01/25/13301

# 加入division，可以改變預設計算方式
 print "---division or not---"
 print "division =",5/2 # 2.5
 print "no division =",5//2 # 2 (default)

# 加入division，可以改變預設計算方式

print "---division or not---"

print "division =",5/2 # 2.5

print "no division =",5//2 # 2 (default)

# 宣告函式，並呼叫
 print "---declare def---"
 def double(x):
     return x * 2

# 宣告函式，並呼叫

print "---declare def---"

def double(x):

return x * 2

def apply_to_one(f):
     return f(1)
     my_double = double # 呼叫前面的函式
     x = apply_to_one(my_double) # 2
 print x

def apply_to_one(f):

return f(1)

my_double = double # 呼叫前面的函式

x = apply_to_one(my_double) # 2

print x

# 建立lamda並做計算
 print "---lamda---"
 y = apply_to_one(lambda x: x + 4) # 5
 print y

# 建立lamda並做計算

print "---lamda---"

y = apply_to_one(lambda x: x + 4) # 5

print y

# 建立def並帶參數給他
 print "---def帶參數---"
 def my_print(message="my default message"):
     print message
 my_print('Hello')

# 建立def並帶參數給他

print "---def帶參數---"

def my_print(message="my default message"):

print message

my_print('Hello')

# 呼叫def給予參數，沒給參數已預設為主
 print "---呼叫def並給予參數---"
 def subtract(a=0, b=0):
     return a - b
 print subtract(10, 5) # 5
 print subtract(0, 5) # -5
 print subtract(b=5) # -5

# 呼叫def給予參數，沒給參數已預設為主

print "---呼叫def並給予參數---"

def subtract(a=0, b=0):

return a - b

print subtract(10, 5) # 5

print subtract(0, 5) # -5

print subtract(b=5) # -5

print "---String 處理---"
 single_quoted_string = 'data science'
 double_quoted_string = "data science"
 # tab
 tab_string = "\t"
 print len(tab_string) # 1

print "---String 處理---"

single_quoted_string = 'data science'

double_quoted_string = "data science"

# tab

tab_string = "\t"

print len(tab_string) # 1

# 呈現\ and t
 not_tab_string = r"\t" # represents the characters '\' and 't'
 print len(not_tab_string) # is 2

# 呈現\ and t

not_tab_string = r"\t" # represents the characters '\' and 't'

print len(not_tab_string) # is 2

# 註解
 multi_line_string = """This is the first line.
 and this is the second line
 and this is the third line"""

# 註解

multi_line_string = """This is the first line.

and this is the second line

and this is the third line"""

# 例外處理，當跑出例外時print "cannot divide by zero"
 print "---try catch例外處理---"
 try:
     print 0 / 0
 except ZeroDivisionError:
     print "cannot divide by zero"

# 例外處理，當跑出例外時print "cannot divide by zero"

print "---try catch例外處理---"

try:

print 0 / 0

except ZeroDivisionError:

print "cannot divide by zero"

# list應用
 print "---list---"
 x = range(10)
 zero = x[0]
 print zero
 one = x[1]
 print one
 nine = x[-1]
 print nine
 eight = x[-2]
 print eight
 x[0] = -1
 print x[0]

# list應用

print "---list---"

x = range(10)

zero = x[0]

print zero

one = x[1]

print one

nine = x[-1]

print nine

eight = x[-2]

print eight

x[0] = -1

print x[0]

# in應用
 print "---in---"
 print 1 in [1, 2, 3] # True
 print 0 in [1, 2, 3] # False

# in應用

print "---in---"

print 1 in [1, 2, 3] # True

print 0 in [1, 2, 3] # False

# tuple應用
 print "---tuple---"
 my_list = [1, 2]
 my_tuple = (1, 2)
 other_tuple = 3, 4
 my_list[1] = 3

# tuple應用

print "---tuple---"

my_list = [1, 2]

my_tuple = (1, 2)

other_tuple = 3, 4

my_list[1] = 3

# try except應用
 try:
     my_tuple[1] = 3
 except TypeError:
     print "cannot modify a tuple"

# try except應用

try:

my_tuple[1] = 3

except TypeError:

print "cannot modify a tuple"

備註：2017/03/09 計算方法分析與設計-課程筆記

Python基本語法-1

Posted on 2017-03-20 by 蕭博元

#python2

# coding=utf-8 # 讓python轉型成utf-8，支援中文
 from __future__ import division
 from collections import Counter # not loaded by default
 from collections import defaultdict

# coding=utf-8 # 讓python轉型成utf-8，支援中文

from __future__ import division

from collections import Counter # not loaded by default

from collections import defaultdict

新增資料集

users = [
 { "id": 0, "name": "Hero" },
 { "id": 1, "name": "Dunn" },
 { "id": 2, "name": "Sue" },
 { "id": 3, "name": "Chi" },
 { "id": 4, "name": "Thor" },
 { "id": 5, "name": "Clive" },
 { "id": 6, "name": "Hicks" },
 { "id": 7, "name": "Devin" },
 { "id": 8, "name": "Kate" },
 { "id": 9, "name": "Klein" }
 ]

friendships = [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3), (3, 4),
 (4, 5), (5, 6), (5, 7), (6, 8), (7, 8), (8, 9)]

users = [

{ "id": 0, "name": "Hero" },

{ "id": 1, "name": "Dunn" },

{ "id": 2, "name": "Sue" },

{ "id": 3, "name": "Chi" },

{ "id": 4, "name": "Thor" },

{ "id": 5, "name": "Clive" },

{ "id": 6, "name": "Hicks" },

{ "id": 7, "name": "Devin" },

{ "id": 8, "name": "Kate" },

{ "id": 9, "name": "Klein" }

]

friendships = [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3), (3, 4),

(4, 5), (5, 6), (5, 7), (6, 8), (7, 8), (8, 9)]

# 將users的資料取出來
 for user in users:
     user["friends"] = []

# 將users的資料取出來

for user in users:

user["friends"] = []

#將friendships取出來後分成兩類
 for i, j in friendships:
     # this works because users[i] is the user whose id is i
     users[i]["friends"].append(users[j]) # add i as a friend of j
     users[j]["friends"].append(users[i]) # add j as a friend of i

#將friendships取出來後分成兩類

for i, j in friendships:

# this works because users[i] is the user whose id is i

users[i]["friends"].append(users[j]) # add i as a friend of j

users[j]["friends"].append(users[i]) # add j as a friend of i

#計算其user['friend']的個數
 print "---計算朋友個數---"
 def number_of_friends(user):
     """how many friends does _user_ have?"""
     return len(user["friends"]) # length of friend_ids list
 total_connections = sum(number_of_friends(user) for user in users) # 24
 print ("total_connections = " + str(total_connections))

#計算其user['friend']的個數

print "---計算朋友個數---"

def number_of_friends(user):

"""how many friends does _user_ have?"""

return len(user["friends"]) # length of friend_ids list

total_connections = sum(number_of_friends(user) for user in users) # 24

print ("total_connections = " + str(total_connections))

print "---平均有幾個朋友---"
 num_users = len(users)
 avg_connections = total_connections / num_users
 print ("avg_connections = " + str(avg_connections))

print "---平均有幾個朋友---"

num_users = len(users)

avg_connections = total_connections / num_users

print ("avg_connections = " + str(avg_connections))

 # 建立list存放user_id,number_of_friends
print "---每個id有幾個朋友---"
num_friends_by_id = [(user["id"], number_of_friends(user)) for user in users]
print ("num_friends_by_id = " + str(num_friends_by_id))

# 建立list存放user_id,number_of_friends

print "---每個id有幾個朋友---"

num_friends_by_id = [(user["id"], number_of_friends(user)) for user in users]

print ("num_friends_by_id = " + str(num_friends_by_id))

# 依照id做朋友的排序
 print "---做排序---"
 sorted_num_friends_by_id = sorted(num_friends_by_id, # get it sorted
                                   key=lambda (user_id, num_friends): num_friends, # by num_friends
                                   reverse=True) # largest to smallest
 print ("sorted_num_friends_by_id = " + str(sorted_num_friends_by_id))

# 依照id做朋友的排序

print "---做排序---"

sorted_num_friends_by_id = sorted(num_friends_by_id, # get it sorted

key=lambda (user_id, num_friends): num_friends, # by num_friends

reverse=True) # largest to smallest

print ("sorted_num_friends_by_id = " + str(sorted_num_friends_by_id))

# 朋友的朋友的關係
print "---哪些人有哪些朋友---"
 def friends_of_friend_ids_bad(user):
     # "foaf" is short for "friend of a friend"
     return [foaf["id"]
            for friend in user["friends"] # for each of user's friends
            for foaf in friend["friends"]] # get each of _their_ friends

print [friend["id"] for friend in users[0]["friends"]] # [1, 2]
print [friend["id"] for friend in users[1]["friends"]] # [0, 2, 3]
print [friend["id"] for friend in users[2]["friends"]] # [0, 1, 3]
print friends_of_friend_ids_bad(users[0])

# 朋友的朋友的關係

print "---哪些人有哪些朋友---"

def friends_of_friend_ids_bad(user):

# "foaf" is short for "friend of a friend"

return [foaf["id"]

for friend in user["friends"] # for each of user's friends

for foaf in friend["friends"]] # get each of _their_ friends

print [friend["id"] for friend in users[0]["friends"]] # [1, 2]

print [friend["id"] for friend in users[1]["friends"]] # [0, 2, 3]

print [friend["id"] for friend in users[2]["friends"]] # [0, 1, 3]

print friends_of_friend_ids_bad(users[0])

 # 朋友的朋友
 print "---朋友的朋友---"
 def not_the_same(user, other_user):
     <em>"""two users are not the same if they have different ids"""
     </em>return user["id"] != other_user["id"]

# 朋友的朋友

print "---朋友的朋友---"

def not_the_same(user, other_user):

<em>"""two users are not the same if they have different ids"""

</em>return user["id"] != other_user["id"]

def not_friends(user, other_user):
     """other_user is not a friend if he's not in user["friends"];
     that is, if he's not_the_same as all the people in user["friends"]"""
     return all(not_the_same(friend, other_user)
                for friend in user["friends"])

def not_friends(user, other_user):

"""other_user is not a friend if he's not in user["friends"];

that is, if he's not_the_same as all the people in user["friends"]"""

return all(not_the_same(friend, other_user)

for friend in user["friends"])

def friends_of_friend_ids(user):
     return Counter(foaf["id"]
                    for friend in user["friends"] # for each of my friends
                    for foaf in friend["friends"] # count *their* friends
                    if not_the_same(user, foaf) # who aren't me
                    and not_friends(user, foaf)) # and aren't my friends
 print friends_of_friend_ids(users[3]) # Counter({0: 2, 5: 1})

def friends_of_friend_ids(user):

return Counter(foaf["id"]

for friend in user["friends"] # for each of my friends

for foaf in friend["friends"] # count *their* friends

if not_the_same(user, foaf) # who aren't me

and not_friends(user, foaf)) # and aren't my friends

print friends_of_friend_ids(users[3]) # Counter({0: 2, 5: 1})

 # 相同的興趣
print "---哪些人有相同的興趣---"
 interests = [
 (0, "Hadoop"), (0, "Big Data"), (0, "HBase"), (0, "Java"),
 (0, "Spark"), (0, "Storm"), (0, "Cassandra"),
 (1, "NoSQL"), (1, "MongoDB"), (1, "Cassandra"), (1, "HBase"),
 (1, "Postgres"), (2, "Python"), (2, "scikit-learn"), (2, "scipy"),
 (2, "numpy"), (2, "statsmodels"), (2, "pandas"), (3, "R"), (3, "Python"),
 (3, "statistics"), (3, "regression"), (3, "probability"),
 (4, "machine learning"), (4, "regression"), (4, "decision trees"),
 (4, "libsvm"), (5, "Python"), (5, "R"), (5, "Java"), (5, "C++"),
 (5, "Haskell"), (5, "programming languages"), (6, "statistics"),
 (6, "probability"), (6, "mathematics"), (6, "theory"),
 (7, "machine learning"), (7, "scikit-learn"), (7, "Mahout"),
 (7, "neural networks"), (8, "neural networks"), (8, "deep learning"),
 (8, "Big Data"), (8, "artificial intelligence"), (9, "Hadoop"),
 (9, "Java"), (9, "MapReduce"), (9, "Big Data")
 ]

# 相同的興趣

print "---哪些人有相同的興趣---"

interests = [

(0, "Hadoop"), (0, "Big Data"), (0, "HBase"), (0, "Java"),

(0, "Spark"), (0, "Storm"), (0, "Cassandra"),

(1, "NoSQL"), (1, "MongoDB"), (1, "Cassandra"), (1, "HBase"),

(1, "Postgres"), (2, "Python"), (2, "scikit-learn"), (2, "scipy"),

(2, "numpy"), (2, "statsmodels"), (2, "pandas"), (3, "R"), (3, "Python"),

(3, "statistics"), (3, "regression"), (3, "probability"),

(4, "machine learning"), (4, "regression"), (4, "decision trees"),

(4, "libsvm"), (5, "Python"), (5, "R"), (5, "Java"), (5, "C++"),

(5, "Haskell"), (5, "programming languages"), (6, "statistics"),

(6, "probability"), (6, "mathematics"), (6, "theory"),

(7, "machine learning"), (7, "scikit-learn"), (7, "Mahout"),

(7, "neural networks"), (8, "neural networks"), (8, "deep learning"),

(8, "Big Data"), (8, "artificial intelligence"), (9, "Hadoop"),

(9, "Java"), (9, "MapReduce"), (9, "Big Data")

]

def data_scientists_who_like(target_interest):
     return [user_id
            for user_id, user_interest in interests
            if user_interest == target_interest]
 print data_scientists_who_like("Python")

def data_scientists_who_like(target_interest):

return [user_id

for user_id, user_interest in interests

if user_interest == target_interest]

print data_scientists_who_like("Python")

# 將user id 與 興趣 取出來並加入user_ids_by_interest
print "---那些人跟誰有相同的興趣---"
 user_ids_by_interest = defaultdict(list)
for user_id, interest in interests:
     user_ids_by_interest[interest].append(user_id)

# 將user id 與興趣取出來並加入user_ids_by_interest

print "---那些人跟誰有相同的興趣---"

user_ids_by_interest = defaultdict(list)

for user_id, interest in interests:

user_ids_by_interest[interest].append(user_id)

# 將user id 與 興趣 取出來並加入interests_by_user_id
 interests_by_user_id = defaultdict(list)
for user_id, interest in interests:
     interests_by_user_id[user_id].append(interest)

# 將user id 與興趣取出來並加入interests_by_user_id

interests_by_user_id = defaultdict(list)

for user_id, interest in interests:

interests_by_user_id[user_id].append(interest)

# 那些人跟誰有相同的興趣
 def most_common_interests_with(user):
     return Counter(interested_user_id
                    for interest in interests_by_user_id[user["id"]]
                    for interested_user_id in user_ids_by_interest[interest]
                    if interested_user_id != user["id"])
 print most_common_interests_with(users[3])

# 那些人跟誰有相同的興趣

def most_common_interests_with(user):

return Counter(interested_user_id

for interest in interests_by_user_id[user["id"]]

for interested_user_id in user_ids_by_interest[interest]

if interested_user_id != user["id"])

print most_common_interests_with(users[3])

備註：2017/03/02 計算方法分析與設計-課程筆記

透過docker安裝wnameless/oracle-xe-11g

Posted on 2017-03-20 by 小胡

01. 下載wnameless/oracle-xe-11g映像檔
(ref: https://hub.docker.com/r/wnameless/oracle-xe-11g/)

sudo docker pull wnameless/oracle-xe-11g
sudo docker run -d -p 49160:22 -p 49161:1521 wnameless/oracle-xe-11g
(docker run -d -p 49160:22 -p 49161:1521 -e ORACLE_ALLOW_REMOTE=true wnameless/oracle-xe-11g)

sudo docker pull wnameless/oracle-xe-11g

sudo docker run -d -p 49160:22 -p 49161:1521 wnameless/oracle-xe-11g

(docker run -d -p 49160:22 -p 49161:1521 -e ORACLE_ALLOW_REMOTE=true wnameless/oracle-xe-11g)

02.這份wnameless/oracle-xe-11g的相關設定如下：

主機： localhost
port: 49161
sid: xe
sys, system 密碼： oracle
root密碼：admin

主機： localhost

port: 49161

sid: xe

sys, system 密碼： oracle

root密碼：admin

03.測試oracle

sudo ssh localhost -p 49160  (root密碼：admin)
sqlplus system@xe (密碼：oracle)
exit
apt-get install nano (安裝nano)

sudo ssh localhost -p 49160 (root密碼：admin)

sqlplus system@xe (密碼：oracle)

exit

apt-get install nano (安裝nano)

04. 寫回映像檔

如果要重複運用這份內容（例如Private DockerHub)，可把異動的部份寫回映像檔

sudo docker commit 1341c004c22c hu/oracle

1	sudo docker commit 1341c004c22c hu/oracle

在UBuntu 16.04安裝Docker CE

Posted on 2017-03-20 by 小胡

在UBuntu安裝Docker CE – INSTALL DOCKER CE ON UBUNTU

參考資料: https://docs.docker.com/engine/installation/linux/ubuntu/#install-docker

01.先安裝UBuntu 16.04 TLS 桌面版

02.更新套件清單

sudo apt-get update

1	sudo apt-get update

03.安裝下列套件，讓docker可以支援aufs

sudo apt-get install \
linux-image-extra-$(uname -r) \
linux-image-extra-virtual

sudo apt-get install \

linux-image-extra-$(uname -r) \

linux-image-extra-virtual

04.安裝下列套件，以讓儲存區Respotory支援HTTPS

sudo apt-get install \
apt-transport-https \
ca-certificates \
curl \
software-properties-common

sudo apt-get install \

apt-transport-https \

ca-certificates \

curl \

software-properties-common

5. 安裝下列套件，在docker中加入官方的GPG金鑰:

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

1	curl -fsSL https://download.docker.com/linux/ubuntu/gpg \| sudo apt-key add -

6.確認金鑰的可信度

sudo apt-key fingerprint 0EBFCD88

1	sudo apt-key fingerprint 0EBFCD88

7. 更新套件並安裝docker

sudo apt-get update
sudo apt-get install docker-ce

1 2	sudo apt-get update sudo apt-get install docker-ce

Artificial Intelligence & Big Data LAB

人工智慧暨巨量資料實驗室

Monthly Archives: March 2017

Git 基本用法與矩陣

Protected: Oracle資料庫系統管理 – Oracle環境安裝教學 (OS on Ubuntu)

Protected: Oracle資料庫系統管理 – Oracle指令介紹

Protected: Oracle資料庫系統管理 – Ubuntu中連線docker環境與Oracle指令

建立自己的docker registry

Python 基本語法-3與matplotlib應用

#python2

Python基本語法-2

Python基本語法-1

#python2

透過docker安裝wnameless/oracle-xe-11g

在UBuntu 16.04安裝Docker CE

在UBuntu安裝Docker CE – INSTALL DOCKER CE ON UBUNTU