1.计算矩阵的面积和周长：

class Rectangle:def __init__(self, width, height):self.width = widthself.height = heightdef area(self):return self.width * self.heightdef perimeter(self):return 2 * (self.width + self.height)if __name__ == "__main__":rectangle = Rectangle(5, 10)print("矩形面积：", rectangle.area())print("矩形周长：", rectangle.perimeter())

2.将矩阵转置后，计算该矩阵与另一个矩阵的和并返回一个新的矩阵对象。

class Matrix:def __init__(self,data):self.data=data#矩阵转置def transpose(self):rows=len(self.data)cols=len(self.data[0])transpose_data=[[0 for _ in range(rows)]for _ in range(cols)]for i in range(rows):for j in range(cols):transpose_data[j][i]=self.data[i][j]return Matrix(transpose_data)#计算两矩阵之和def add(self,other_matrix):rows=len(self.data)cols=len(self.data[0])if rows !=len(other_matrix.data) or cols != len(other_matrix.data[0]):raise ValueError("两个矩阵维度不一致")result_data=[[0 for _ in range(cols)]for _ in range(rows)]for i in range(rows):for j in range(cols):result_data[i][j]=self.data[i][j]+other_matrix.data[i][j]return Matrix(result_data)if __name__ == "__main__":matrix1=Matrix([[1,2,3],[4,5,6]])matrix2=Matrix([[7,8,9],[10,11,12]])print("矩形1的转置:")transposed_matrix1=matrix1.transpose()for row in transposed_matrix1.data:print(row)print("矩阵1和矩阵2的和:")sum_matrix=matrix1.add(matrix2)for row in sum_matrix.data:print(row)

3.栈的基本操作

class Stack:def __init__(self):self.items = []def push(self, item):self.items.append(item)def pop(self):if self.is_empty():raise ValueError("栈为空")return self.items.pop()def is_empty(self):return len(self.items) == 0if __name__ == "__main__":stack = Stack()stack.push(1)stack.push(2)stack.push(3)while not stack.is_empty():print(stack.pop())

4.链表的基本操作

class Node:def __init__(self, value):self.value = valueself.next = Noneclass LinkedList:def __init__(self, head=None):self.head = headdef insert(self, value):new_node = Node(value)if self.head is None:self.head = new_nodeelse:current = self.headwhile current.next is not None:current = current.nextcurrent.next = new_nodedef delete(self, value):if self.head is None:returnif self.head.value == value:self.head = self.head.nextreturncurrent = self.headwhile current.next is not None:if current.next.value == value:current.next = current.next.nextreturncurrent = current.nextdef traverse(self):current = self.headwhile current is not None:print(current.value)current = current.nextif __name__ == "__main__":linked_list = LinkedList()linked_list.insert(1)linked_list.insert(2)linked_list.insert(3)linked_list.delete(2)linked_list.traverse()

5.队列的基本操作

class Queue:def __init__(self):self.items = []def is_empty(self):return len(self.items) == 0def enqueue(self, item):self.items.append(item)def dequeue(self):if not self.is_empty():return self.items.pop(0)#对于栈的操作为：self.items.pop()def size(self):return len(self.items)if __name__ == "__main__":q = Queue()print(q.is_empty())  # Trueq.enqueue(1)q.enqueue(2)q.enqueue(3)print(q.size())  # 3print(q.dequeue())  # 1print(q.dequeue())  # 2print(q.size())  # 1

6.Histogram类封装直方图

（1）定义带一个整数参数n的构造函数，用于初始化存储数据的列表，列表长度为n，列表各元素的初始值为0.

（2）定义实例对象方法addDataPoint(self,i)，用于增加一个数据点

（3）定义用于计算数据点个数之和、平均值、最大值、最小值的实例对象方法，即count()、mean()、max()、min()。

（4）定义用于绘制简单直方图的实例对象方法draw()

import randomclass Histogram:def __init__(self,n):self.__numlist=[]for i in range(n):self.__numlist.append(0)#print(self.__numlist)def addDataPoint(self,i):self.__numlist[i]+=1def count(self,data_account):return data_accountdef mean(self,data_account,List_account):a=data_account/List_accountreturn (a)def Max(self):return max(self.__numlist)def Min(self):return min(self.__numlist)def draw(self):for i in range(len(self.__numlist)):print("{}:".format(i),end="")for j in range(self.__numlist[i]):print("#".format(i),end="")print("")if __name__=="__main__":List_account=10#规定numlist的大小histogram=Histogram(List_account)Data_account=100for i in range(0,Data_account):#生成0~99一百个数字random_number=random.randint(0,9)#随机生成0~9histogram.addDataPoint(random_number)#将生成的随机数放到列表中print("数据点个数的个数:{}".format(Data_account))print("数据点个数的平均值:{}".format(histogram.mean(Data_account, List_account)))print("数据点个数的最大值{}".format(histogram.Max()))print("数据点个数的最小值{}".format(histogram.Min()))histogram.draw()

结果：