* count.py
list.append(xxx) 再 list.reverse 等效 list.insert(0, xxx)
#!/usr/bin/python
# -*- coding: utf-8 -*-
count = 10 ** 5
nums = []
for i in range(count):
# nums.append(i)
nums.insert(0, i)
# nums.reverse()
print(nums)* Nodes.py
python 简单的链表创建
#!/usr/bin/python
# -*- coding: utf-8 -*-
class Node:
def __init__(self, value, next = None):
self.value = value
self.next = next
def toString(self):
p = self
s = p.value
p = p.next
while (p != None):
s += "," + p.value
p = p.next
return s
L = Node("a", Node("b", Node("c", Node("d"))))
# print(L.next.next.value)
print( L.toString() )
* graph.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
a, b, c, d, e, f, g, h = range(8)
N = [
{b, c, d, e, f}, # a
{c, e}, # b
{d}, # c
{e}, # d
{f}, # e
{c, g, h}, # f
{f, h}, # g
{f, g} # h
]
# Neighborhoold membership
print( b in N[a] ) # True
# Degree
print( len(N[f]) ) # 3
* matrix.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
a, b, c, d, e, f, g, h = range(8)
# Adjacency matrix
N = [[0,1,1,1,1,1,0,0], # a
[0,0,1,0,1,0,0,0], # b
[0,0,0,1,0,0,0,0], # c
[0,0,0,0,1,0,0,0], # d
[0,0,0,0,0,1,0,0], # e
[0,0,1,0,0,0,1,1], # f
[0,0,0,0,0,1,0,1], # g
[0,0,0,0,0,1,1,0]] # h
# Neighborhoold membership
print( N[a][b] ) # 1
# Degree
print( sum(N[f]) )
* inf.py
#!/usr/bin/python3
# -*- coding: utf-8 -*-
# A Weight Matrix with Infinite Weight for Missing Edges
a, b, c, d, e, f, g, h = range(8)
_ = float('inf')
# a b c d e f g h
W = [[0,2,1,3,9,4,_,_], # a
[_,0,4,_,3,_,_,_], # b
[_,_,0,8,_,_,_,_], # c
[_,_,_,0,7,_,_,_], # d
[_,_,_,_,0,5,_,_], # e
[_,_,2,_,_,0,2,2], # f
[_,_,_,_,_,1,0,6], # g
[_,_,_,_,_,9,8,0]] # h
# Neighborhoold membership
print( W[a][b] < _ ) # True
# Neighborhoold membership
print( W[c][e] < _ ) # False
# Degree
s = sum( 1 for w in W[a] if w < _ ) - 1
print( s ) # 5
Note that 1 is subtracted from the degree sum, because we don’t want to count the diagonal.
创建一个矩阵10*10，每个元素赋初值为0
sudo pip3 install numpy
* zeros.py
#!/usr/bin/python3
# -*- coding: utf-8 -*-
N = [ [0] * 10 for i in range(10) ]
print(N)
print("Using numpy...\n")
import numpy as np
N = np.zeros([10, 10])
print(N)
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
Using numpy...
[[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
最新版的numpy代码库: svn co http://svn.scipy.org/svn/numpy/trunk numpy
* simpleTree.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
T = [ ["a","b"], ["c"], ["d", ["e", "f"]] ]
print(T[0][1])
print(T[2][1][0])
A sample tree with a highlighted path from the root to a leaf
* BinaryTree.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
class BinaryTree:
def __init__(self, left, right):
self.left = left
self.right = right
t = BinaryTree(BinaryTree("a", "b"), BinaryTree("c", "d"))
print(t.right.left) # 'c'
* Tree.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
class Tree:
def __init__(self, kids, next = None):
self.kids = self.val = kids
self.next = next
t = Tree(Tree("a"), Tree("b", Tree("c", Tree("d"))))
print(t.kids.next.next.val) # c
* Bunch.py
#!/usr/bin/python3
# -*- coding: utf-8 -*-
# A flexible class that will allow you to specify arbitrary attributes in the constructor
# class Bunch extends dict
class Bunch(dict):
def __init__(self, *args, **kwds):
# super(Bunch, self).__init__(*args, **kwds)
dict.__init__(self, *args, **kwds)
self.__dict__ = self
x = Bunch(name="Jane Cobb", position="Public Relations")
print(x.name) # Jane Cobb
T = Bunch
t = T(left=T(left="a", right="b"), right=T(left="c"))
print(t.left) # {'right': 'b', 'left': 'a'}
print(t.left.right) # b
print(t['left']['right']) # b
print("left" in t.right) # True
print("right" in t.right) # False
