在上一篇博文中提到的伸展树(splay tree).其实自己也没怎么明白.在网上找了半天也没有看懂.最终找到了这个.这是加州大学伯克利分校的CS 61B数据结构的一个公开课视频.讲的清楚极了.现部分整理如下.

一.伸展树是一种平衡二叉搜索树.它可以快速的获得最近操作的项目.对于伸展树.最基本的策略是旋转(Rotation).旋转分为左旋和右旋.如下:

二.伸展树的基本操作:

1.查找(K):和普通的二叉树没什么区别.然后让查找结束的节点X成为根(splay)(不管是否找到目标K.)

2.伸展(splay X):有三种情况.

• Zig-zag:
  X是一个右节点的左节点.或者X是一个左节点的右节点.
  旋转X两次.
  
• Zig-zig:
  X是一个左节点的左节点.或者X是一个右节点的右节点.
  旋转两次.但和Zig-zag的旋转顺序有差异.先旋转X的父节点.在旋转X.
  
• Zig:
  X是根的子节点.
  那么就是一次旋转
  

   Zig-zag和Zig-zig都是对两层深度的操作.直到X成为根的子节点.就进行Zig操作.

下面是一个查找的例子.

首先.象普通的二叉搜索树一样.找到7.可见.7是一个右节点的右节点.那么就进行Zig-zig步骤.此时7是一个右节点的左节点.就进行Zig-zag步骤.再进行一个Zig步骤.一个查找7的操作就完成了.

3.插入(K):首先象普通的二叉搜索树一样将K插入.再将K伸展至根.

4.删除(K):象普通的二叉搜索树一样将K删除.然后将K的父节点X伸展至根.如果K没有在树内的话.那么就如同查找操作.即将最后一个访问的节点伸展至根.

这里有一个在线的示例：http://www.ibr.cs.tu-bs.de/courses/ss98/audii/applets/BST/SplayTree-Example.html

另一小段功能不全的测试代码..只能打印树的深度...(摊手)(摇头)

def inorder():
    d=dict()
    def inner_inorder(n,r):
        if n is None :
            return
        else:
            inner_inorder(n.left,r=r+1)
            if d.get(r) is None:
                d[r]=[n.key]
            else:
                d[r].append(n.key)
            inner_inorder(n.right,r=r+1)
    inner_inorder(t.root,0)
    return d

def print_tree():
    d=inorder()
    for i in d:
        print "%s"%d[i]

t=SplayTree()
for i in range(9):
    t.insert(i)

print_tree(t)

主程序是一个伸展树(Splay Tree).如下(链接):

class Node:
    def __init__(self, key):
        self.key = key
        self.left = self.right = None

    def equals(self, node):
        return self.key == node.key

class SplayTree:
    def __init__(self):
        self.root = None
        self.header = Node(None) #For splay()

    def insert(self, key):
        if (self.root == None):
            self.root = Node(key)
            return

        self.splay(key)
        if self.root.key == key:
            # If the key is already there in the tree, don't do anything.
            return

        n = Node(key)
        if key < self.root.key:
            n.left = self.root.left
            n.right = self.root
            self.root.left = None
        else:
            n.right = self.root.right
            n.left = self.root
            self.root.right = None
        self.root = n

    def remove(self, key):
        self.splay(key)
        if key != self.root.key:
            raise 'key not found in tree'

        # Now delete the root.
        if self.root.left== None:
            self.root = self.root.right
        else:
            x = self.root.right
            self.root = self.root.left
            self.splay(key)
            self.root.right = x

    def findMin(self):
        if self.root == None:
            return None
        x = self.root
        while x.left != None:
            x = x.left
        self.splay(x.key)
        return x.key

    def findMax(self):
        if self.root == None:
            return None
        x = self.root
        while (x.right != None):
            x = x.right
        self.splay(x.key)
        return x.key

    def find(self, key):
        if self.root == None:
            return None
        self.splay(key)
        if self.root.key != key:
            return None
        return self.root.key

    def isEmpty(self):
        return self.root == None
   
    def splay(self, key):
        l = r = self.header
        t = self.root
        self.header.left = self.header.right = None
        while True:
            if key < t.key:
                if t.left == None:
                    break
                if key < t.left.key:
                    y = t.left
                    t.left = y.right
                    y.right = t
                    t = y
                    if t.left == None:
                        break
                r.left = t
                r = t
                t = t.left
            elif key > t.key:
                if t.right == None:
                    break
                if key > t.right.key:
                    y = t.right
                    t.right = y.left
                    y.left = t
                    t = y
                    if t.right == None:
                        break
                l.right = t
                l = t
                t = t.right
            else:
                break
        l.right = t.left
        r.left = t.right
        t.left = self.header.right
        t.right = self.header.left
        self.root = t

测试如下(链接):

import unittest
from splay import SplayTree

class TestCase(unittest.TestCase):
    def setUp(self):
        self.keys = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
        self.t = SplayTree()
        for key in self.keys:
            self.t.insert(key)
       
    def testInsert(self):
        for key in self.keys:
            self.assertEquals(key, self.t.find(key))

    def testRemove(self):
        for key in self.keys:
            self.t.remove(key)
            self.assertEquals(self.t.find(key), None)

    def testLargeInserts(self):
        t = SplayTree()
        nums = 40000
        gap = 307
        i = gap
        while i != 0:
            t.insert(i)
            i = (i + gap) % nums

    def testIsEmpty(self):
        self.assertFalse(self.t.isEmpty())
        t = SplayTree()
        self.assertTrue(t.isEmpty())

    def testMinMax(self):
        self.assertEquals(self.t.findMin(), 0)
        self.assertEquals(self.t.findMax(), 9)

if __name__ == "__main__":
    unittest.main()

运行:

(rrandom)-(~/python-codes/udacity/RegehrCS258)-(07:27 下午 六 10月 06)
-> py splayTest.py 
.....
----------------------------------------------------------------------
Ran 5 tests in 1.454s

OK

但是否每一行代码都运行过了呢?代码覆盖律(code coverage)就是指测试中代码的运行的程度.如果代码覆盖律小于100%.那就意味着还有语句没有被执行.这时候就要coverage出场了.

(rrandom)-(~/python-codes/udacity/RegehrCS258)-(07:42 下午 六 10月 06)
-> coverage erase;coverage run splayTest.py;
.....
----------------------------------------------------------------------
Ran 5 tests in 2.294s

OK

erase是清空上次的数据.coverage 还可以生成html,方便查看

(rrandom)-(~/python-codes/udacity/RegehrCS258)-(07:50 下午 六 10月 06)
-> coverage erase;coverage run splayTest.py;coverage html -i
.....
----------------------------------------------------------------------
Ran 5 tests in 2.298s

OK

得到结果:

查看详细.是那些语句没有被执行:

excluded表示你告诉coverage忽略的代码.

现在尝试修改测试代码.删除一个不在树里的节点:

    def testRemove(self):
        for key in self.keys:
            self.t.remove(key)
            self.assertEquals(self.t.find(key), None)
        self.t.remove(-999)

再次运行coverage:

(rrandom)-(~/python-codes/udacity/RegehrCS258)-(07:50 下午 六 10月 06)
-> coverage erase;coverage run splayTest.py;coverage html -i
....E
======================================================================
ERROR: testRemove (__main__.TestCase)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "splayTest.py", line 22, in testRemove
    self.t.remove(-999)
  File "/home/rrandom/python-codes/udacity/RegehrCS258/splay.py", line 39, in remove
    self.splay(key)
  File "/home/rrandom/python-codes/udacity/RegehrCS258/splay.py", line 86, in splay
    if key < t.key:
AttributeError: 'NoneType' object has no attribute 'key'

----------------------------------------------------------------------
Ran 5 tests in 2.382s

FAILED (errors=1)

这是一个不在预期内的错误.但是这一行却没有被执行.

那么错误应该在self.splay(key)内.

参考:Udacity CS258 unit2

git,基本命令的思维导图

大图 freemind文件

参考:

Pro Git

http://www.mindmeister.com/61349574/git

呃...从哪里说起呢.

扇贝是一个背单词的网站.它对每一个用户建立了一个词库.词库里就是你要背的单词.

接着.扇贝有chrome扩展而没有.而我从chrome'叛逃'到firefox后.就一直有自己写一个火狐扩展的想法.

开学来终于把想法付诸行动了...

我想就算我写出来没人用.我也可以自己用..就算我写不出来.那我也可以学一点javascript..

然后发现其实真的也没有想像中难.反而还写的自己挺嗨的.

安装:

https://addons.mozilla.org/en-US/firefox/addon/a-shanbay-firefox-extension/

bitbucket:

https://bitbucket.org/rrandom/a-shanbay-firefox-extension

功能:查单词...

to-do:例句添加.修改右键查词.

In python,a decorators starts with @,such as:

@myDecorator
def func1():
    print "inside func1()"

It means:

func1=myDecorator(func1)

Here is a useful decorator.

from functools import update_wrapper

def decorator(d):
    "Make function d a decorator: d wraps a function fn."
    def _d(fn):
        return update_wrapper(d(fn), fn)
    update_wrapper(_d, d)
    return _d

@decorator
def memo(f):
    """Decorator that caches the return value for each call to f(args).
    Then when called again with same args, we can just look it up."""
    cache = {}
    def _f(*args):
        try:
            return cache[args]
        except KeyError:
            cache[args] = result = f(*args)
            return result
        except TypeError:
            # some element of args can't be a dict key
            return f(*args)
    _f.cache = cache
    return _f

Then,implement it on fib

@memo
def fib(n):
    if n == 0 or n == 1:
        return 1
    else:
        return fib(n-1) + fib(n-2)

print fib(100)

参考:

udacity cs212 unit3 note

udacity cs212 unit5 note