def __init__(self): self.heap = [] self.count = 0
时间: 2024-05-22 08:12:01 浏览: 14
As an AI language model, I can say that this code seems to be a constructor for a class.
The constructor initializes two variables: `self.heap` and `self.count`. `self.heap` is initialized as an empty list, which suggests that this class may be implementing a heap data structure. `self.count` is initialized as 0, which may be used to keep track of the number of elements in the heap.
Overall, without additional context or code, it is difficult to determine the purpose or functionality of this class.
相关问题
用python写一个麻将游戏
好的,这是一个麻将游戏的代码示例,使用Python语言编写:
```python
import random
# 麻将牌总数
MAHJONG_COUNT = 144
# 麻将牌的种类
MAHJONG_KINDS = ["万", "条", "饼", "风", "箭"]
# 麻将牌的数字
MAHJONG_NUMS = ["一", "二", "三", "四", "五", "六", "七", "八", "九"]
# 风牌的种类
MAHJONG_FENG_KINDS = ["东", "南", "西", "北"]
# 箭牌的种类
MAHJONG_JIAN_KINDS = ["中", "发", "白"]
# 玩家初始手牌数量
INIT_HAND_COUNT = 13
# 麻将牌的类
class Mahjong:
def __init__(self, kind, num):
self.kind = kind
self.num = num
def __str__(self):
return self.num + self.kind
# 麻将牌堆的类
class MahjongHeap:
def __init__(self):
self.heap = []
self.init_heap()
self.shuffle()
# 初始化麻将牌堆
def init_heap(self):
for kind in MAHJONG_KINDS:
if kind == "风":
for feng in MAHJONG_FENG_KINDS:
for i in range(4):
self.heap.append(Mahjong(feng, ""))
elif kind == "箭":
for jian in MAHJONG_JIAN_KINDS:
for i in range(4):
self.heap.append(Mahjong(jian, ""))
else:
for num in MAHJONG_NUMS:
for i in range(4):
self.heap.append(Mahjong(kind, num))
# 洗牌
def shuffle(self):
random.shuffle(self.heap)
# 摸牌
def draw(self):
if len(self.heap) > 0:
return self.heap.pop()
else:
return None
# 玩家类
class Player:
def __init__(self, name):
self.name = name
self.hand = []
# 摸牌
def draw(self, mahjong):
self.hand.append(mahjong)
# 打牌
def discard(self, index):
if index >= 0 and index < len(self.hand):
return self.hand.pop(index)
else:
return None
# 显示手牌
def show_hand(self):
print(self.name + "的手牌:")
for i, mahjong in enumerate(self.hand):
print(str(i+1) + ": " + str(mahjong))
# 游戏类
class Game:
def __init__(self):
self.players = []
self.mahjong_heap = MahjongHeap()
# 添加玩家
def add_player(self, player):
self.players.append(player)
# 开始游戏
def start(self):
# 发牌
for i in range(INIT_HAND_COUNT):
for player in self.players:
player.draw(self.mahjong_heap.draw())
# 显示玩家手牌
for player in self.players:
player.show_hand()
# 主循环
while True:
for player in self.players:
# 玩家摸牌
mahjong = self.mahjong_heap.draw()
player.draw(mahjong)
print(player.name + "摸了一张牌:" + str(mahjong))
# 显示玩家手牌
player.show_hand()
# 玩家打牌
while True:
index = input(player.name + "打哪张牌?")
if index.isdigit():
index = int(index) - 1
mahjong = player.discard(index)
if mahjong is not None:
print(player.name + "打出了:" + str(mahjong))
break
else:
print("无效的牌号!")
else:
print("无效的输入!")
# 判断是否有人胡牌、和牌、杠牌、碰牌等等
# 判断是否有人胡牌
# 判断是否有人和牌
# 判断是否有人杠牌
# 判断是否有人碰牌
# 判断是否流局
# 结束游戏
def end(self):
pass
# 测试代码
if __name__ == "__main__":
game = Game()
game.add_player(Player("张三"))
game.add_player(Player("李四"))
game.add_player(Player("王五"))
game.start()
game.end()
```
python可视化界面实现十大排序算法
可以使用 Python 的 tkinter 模块来实现可视化界面,使用 matplotlib 库来绘制排序过程中的图形。
以下是一个示例代码,实现了十大排序算法的可视化界面:
```python
import random
import time
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import tkinter as tk
class SortingVisualization:
def __init__(self, sort_algorithm, length=100):
self.length = length
self.data = [i+1 for i in range(length)]
random.shuffle(self.data)
self.sort_algorithm = sort_algorithm(self.data)
self.fig, self.ax = plt.subplots()
self.ax.set_title(self.sort_algorithm.__class__.__name__)
self.bar_rects = self.ax.bar(range(len(self.data)), self.data, align="edge")
self.ax.set_xlim(0, len(self.data))
self.ax.set_ylim(0, int(1.07 * length))
self.iteration = self.sort_algorithm.sort()
self.start_time = time.time()
def update(self, rects, iteration):
for rect, val in zip(rects, self.data):
rect.set_height(val)
try:
next(self.iteration)
except StopIteration:
self.ax.set_title(f"{self.sort_algorithm.__class__.__name__} ({time.time()-self.start_time:.2f}s)")
return False
return True
def animate(self, i):
return self.update(self.bar_rects, i)
def start(self):
anim = FuncAnimation(self.fig, self.animate, frames=range(len(self.data)), interval=1,
repeat=False, blit=True)
plt.show()
class BubbleSort:
def __init__(self, data):
self.data = data
def sort(self):
n = len(self.data)
for i in range(n):
for j in range(n-i-1):
if self.data[j] > self.data[j+1]:
self.data[j], self.data[j+1] = self.data[j+1], self.data[j]
yield
class SelectionSort:
def __init__(self, data):
self.data = data
def sort(self):
n = len(self.data)
for i in range(n):
min_idx = i
for j in range(i+1, n):
if self.data[min_idx] > self.data[j]:
min_idx = j
self.data[i], self.data[min_idx] = self.data[min_idx], self.data[i]
yield
class InsertionSort:
def __init__(self, data):
self.data = data
def sort(self):
n = len(self.data)
for i in range(1, n):
key = self.data[i]
j = i - 1
while j >= 0 and key < self.data[j]:
self.data[j+1] = self.data[j]
j -= 1
yield
self.data[j+1] = key
yield
class QuickSort:
def __init__(self, data):
self.data = data
def sort(self):
def _quick_sort(l, r):
if l < r:
p = self.partition(l, r)
yield from _quick_sort(l, p-1)
yield from _quick_sort(p+1, r)
yield from _quick_sort(0, len(self.data)-1)
def partition(self, l, r):
pivot = self.data[r]
i = l - 1
for j in range(l, r):
if self.data[j] < pivot:
i += 1
self.data[i], self.data[j] = self.data[j], self.data[i]
yield
self.data[i+1], self.data[r] = self.data[r], self.data[i+1]
yield
return i + 1
class MergeSort:
def __init__(self, data):
self.data = data
def sort(self):
def _merge_sort(l, r):
if l < r:
m = (l + r) // 2
yield from _merge_sort(l, m)
yield from _merge_sort(m+1, r)
yield from self.merge(l, m, r)
yield from _merge_sort(0, len(self.data)-1)
def merge(self, l, m, r):
L = self.data[l:m+1]
R = self.data[m+1:r+1]
i = j = 0
k = l
while i < len(L) and j < len(R):
if L[i] < R[j]:
self.data[k] = L[i]
i += 1
else:
self.data[k] = R[j]
j += 1
k += 1
yield
while i < len(L):
self.data[k] = L[i]
i += 1
k += 1
yield
while j < len(R):
self.data[k] = R[j]
j += 1
k += 1
yield
class HeapSort:
def __init__(self, data):
self.data = data
def sort(self):
n = len(self.data)
for i in range(n // 2 - 1, -1, -1):
yield from self.heapify(n, i)
for i in range(n-1, 0, -1):
self.data[0], self.data[i] = self.data[i], self.data[0]
yield
yield from self.heapify(i, 0)
def heapify(self, n, i):
largest = i
l = 2 * i + 1
r = 2 * i + 2
if l < n and self.data[largest] < self.data[l]:
largest = l
if r < n and self.data[largest] < self.data[r]:
largest = r
if largest != i:
self.data[i], self.data[largest] = self.data[largest], self.data[i]
yield
yield from self.heapify(n, largest)
class ShellSort:
def __init__(self, data):
self.data = data
def sort(self):
n = len(self.data)
gap = n // 2
while gap > 0:
for i in range(gap, n):
temp = self.data[i]
j = i
while j >= gap and self.data[j-gap] > temp:
self.data[j] = self.data[j-gap]
j -= gap
yield
self.data[j] = temp
yield
gap //= 2
class CountingSort:
def __init__(self, data):
self.data = data
def sort(self):
n = len(self.data)
output = [0] * n
count = [0] * (max(self.data) + 1)
for i in range(n):
count[self.data[i]] += 1
for i in range(1, len(count)):
count[i] += count[i-1]
for i in range(n-1, -1, -1):
output[count[self.data[i]]-1] = self.data[i]
count[self.data[i]] -= 1
yield
self.data = output
class RadixSort:
def __init__(self, data):
self.data = data
def sort(self):
def _counting_sort(exp):
n = len(self.data)
output = [0] * n
count = [0] * 10
for i in range(n):
idx = (self.data[i] // exp) % 10
count[idx] += 1
for i in range(1, len(count)):
count[i] += count[i-1]
for i in range(n-1, -1, -1):
idx = (self.data[i] // exp) % 10
output[count[idx]-1] = self.data[i]
count[idx] -= 1
yield
self.data = output
max_val = max(self.data)
exp = 1
while max_val // exp > 0:
yield from _counting_sort(exp)
exp *= 10
class GUI:
def __init__(self):
self.window = tk.Tk()
self.window.title("Sorting Visualization")
self.window.geometry("320x240")
self.sorts = {"Bubble Sort": BubbleSort, "Selection Sort": SelectionSort,
"Insertion Sort": InsertionSort, "Quick Sort": QuickSort,
"Merge Sort": MergeSort, "Heap Sort": HeapSort,
"Shell Sort": ShellSort, "Counting Sort": CountingSort,
"Radix Sort": RadixSort}
self.sort_var = tk.StringVar(self.window, sorted(self.sorts.keys())[0])
sort_menu = tk.OptionMenu(self.window, self.sort_var, *self.sorts.keys())
sort_menu.pack(pady=10)
length_var = tk.StringVar(self.window, "100")
length_entry = tk.Entry(self.window, textvariable=length_var)
length_entry.pack(pady=5)
start_button = tk.Button(self.window, text="Start", command=self.start)
start_button.pack(pady=10)
self.window.mainloop()
def start(self):
try:
length = int(length_var.get())
sort_algorithm = self.sorts[self.sort_var.get()]
SortingVisualization(sort_algorithm, length).start()
except ValueError:
return
if __name__ == "__main__":
GUI()
```
运行该代码,会弹出一个 GUI 界面,选择排序算法和数据长度后,点击 Start 按钮即可开始可视化排序过程。
注意:由于排序算法的实现方式不同,排序时间也会有所不同,因此排序过程中的动画时间也会有所不同。