6.00 Introduction to Computer Science and Programming Lec 9: Lecture 9: Memory and Search Methods
2013-02-20 22:42
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这个lec主要讲排序算法,首先从list的实现开始。Python中的list显然是可变的,可以自由地向其中添加、删除各种类型的元素,然后有可以使用下标来查找,有些类似于Java中的list。Python中的List显然不能用连续的内存空间来实现,因为存储在list中的元素可以类型不同,使用链表的方式可以解决这个问题,但存在效率问题,例如查找list aList中的第199个元素aList[198],则需要链接198次才能得到。如果纯数组和纯链表不能解决这个问题,那么将二者结合起来,则可以形成一个比较好的解决方案。Python中List的实现如下图所示:
此lec的其他部分主要集中在常用排序算法的讲解上,贴代码看看就好了:
Python 支持一种有趣的语法,它允许你快速定义单行的最小函数。这些叫做 lambda 的函数,是从 Lisp 借用来的,可以用在任何需要函数的地方。
总的来说,lambda 函数可以接收任意多个参数 (包括可选参数) 并且返回单个表达式的值。lambda 函数不能包含命令,包含的表达式不能超过一个。不要试图向 lambda 函数中塞入太多的东西;如果你需要更复杂的东西,应该定义一个普通函数,然后想让它多长就多长。
此lec的其他部分主要集中在常用排序算法的讲解上,贴代码看看就好了:
def bSearch(L, e, low, high): if high - low < 2: return L[low] == e or L[high] == e mid = low + int((high - low)/2) if L[mid] == e: return True if L[mid] > e: return bSearch(L, e, low, mid - 1) else: return bSearch(L, e, mid + 1, high) def selSort(L): """Assumes that L is a list of elements that can be compared using >. Sorts L in ascending order""" for i in range(len(L) - 1): #Invariant: the list L[:i] is sorted minIndx = i minVal= L[i] j = i + 1 while j < len(L): if minVal > L[j]: minIndx = j minVal= L[j] j += 1 temp = L[i] L[i] = L[minIndx] L[minIndx] = temp print 'Partially sorted list =', L ##L = [35, 4, 5, 29, 17, 58, 0] ##selSort(L) ##print 'Sorted list =', L def merge(left, right, lt): """Assumes left and right are sorted lists. lt defines an ordering on the elements of the lists. Returns a new sorted(by lt) list containing the same elements as (left + right) would contain.""" result = [] i,j = 0, 0 while i < len(left) and j < len(right): if lt(left[i], right[j]): result.append(left[i]) i += 1 else: result.append(right[j]) j += 1 while (i < len(left)): result.append(left[i]) i += 1 while (j < len(right)): result.append(right[j]) j += 1 return result def sort(L, lt = lambda x,y: x < y): """Returns a new sorted list containing the same elements as L""" if len(L) < 2: return L[:] else: middle = int(len(L)/2) left = sort(L[:middle], lt) right = sort(L[middle:], lt) print 'About to merge', left, 'and', right return merge(left, right, lt) ##L = [35, 4, 5, 29, 17, 58, 0] ##newL = sort(L) ##print 'Sorted list =', newL ##L = [1.0, 2.25, 24.5, 12.0, 2.0, 23.0, 19.125, 1.0] ##newL = sort(L, float.__lt__) ##print 'Sorted list =', newL def lastNameFirstName(name1, name2): import string name1 = string.split(name1, ' ') name2 = string.split(name2, ' ') if name1[1] != name2[1]: return name1[1] < name2[1] else: return name1[0] < name2[0] def firstNameLastName(name1, name2): import string name1 = string.split(name1, ' ') name2 = string.split(name2, ' ') if name1[0] != name2[0]: return name1[0] < name2[0] else: return name1[1] < name2[1] ##L = ['John Guttag', 'Tom Brady', 'Chancellor Grimson', 'Gisele Brady', ## 'Big Julie'] ##newL = sort(L, lastNameFirstName) ##print 'Sorted list =', newL ##newL = sort(L, firstNameLastName) ##print 'Sorted list =', newL在上面的代码中,有一个很有趣的代码段:
def sort(L, lt = lambda x,y: x < y):其中,lt = xxxx的意思是lt参数的默认值为lambda x, y: x < y。这里的lambda是Python函数式编程风格的一个体现,下面这段关于lambda的介绍是从这里节选过来的:http://woodpecker.org.cn/diveintopython/power_of_introspection/lambda_functions.html
Python 支持一种有趣的语法,它允许你快速定义单行的最小函数。这些叫做 lambda 的函数,是从 Lisp 借用来的,可以用在任何需要函数的地方。
例 4.20. lambda 函数介绍
>>> def f(x): ... return x*2 ... >>> f(3) 6 >>> g = lambda x: x*2 >>> g(3) 6 >>> (lambda x: x*2)(3) 6
这是一个 lambda 函数,完成同上面普通函数相同的事情。注意这里的简短的语法:在参数列表周围没有括号,而且忽略了 return 关键字 (隐含存在,因为整个函数只有一行)。而且,该函数没有函数名称,但是可以将它赋值给一个变量进行调用。 | |
使用 lambda 函数时甚至不需要将它赋值给一个变量。这可能不是世上最有用的东西,它只是展示了 lambda 函数只是一个内联函数。 |
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