用Python实现Cohen Sutherland算法 并给出图形

好的，以下是使用 Python 实现 Cohen-Sutherland 算法并给出图形的代码和图形：

import matplotlib.pyplot as plt

# 定义线段端点坐标
p1 = (10, 10)
p2 = (50, 50)

# 定义裁剪窗口
win_min = (20, 20)
win_max = (40, 40)

# 计算线段编码
def encode(p):
    x, y = p
    code = 0b0000
    if x < win_min[0]:
        code |= 0b0001
    elif x > win_max[0]:
        code |= 0b0010
    if y < win_min[1]:
        code |= 0b0100
    elif y > win_max[1]:
        code |= 0b1000
    return code

code1 = encode(p1)
code2 = encode(p2)

# 判断是否可见
def visible(code1, code2):
    if code1 & code2 != 0:
        return False  # 不可见
    elif code1 | code2 == 0:
        return True  # 可见
    else:
        return None  # 需要裁剪

vis = visible(code1, code2)

# 裁剪线段
def intersection(p1, p2, code):
    x1, y1 = p1
    x2, y2 = p2
    x, y = None, None
    if code & 0b0100:  # 下
        x = x1 + (x2 - x1) * (win_min[1] - y1) / (y2 - y1)
        y = win_min[1]
    elif code & 0b1000:  # 上
        x = x1 + (x2 - x1) * (win_max[1] - y1) / (y2 - y1)
        y = win_max[1]
    elif code & 0b0001:  # 左
        y = y1 + (y2 - y1) * (win_min[0] - x1) / (x2 - x1)
        x = win_min[0]
    elif code & 0b0010:  # 右
        y = y1 + (y2 - y1) * (win_max[0] - x1) / (x2 - x1)
        x = win_max[0]
    return (x, y)

if vis is None:
    new_p1 = p1
    new_p2 = p2
    while vis is None:
        code1 = encode(new_p1)
        code2 = encode(new_p2)
        vis = visible(code1, code2)
        if vis is None:
            if code1 != 0:
                new_p1 = intersection(new_p1, new_p2, code1)
            else:
                new_p2 = intersection(new_p1, new_p2, code2)
    p1, p2 = new_p1, new_p2

# 绘制线段和裁剪窗口
fig, ax = plt.subplots()
ax.set_xlim(0, 60)
ax.set_ylim(0, 60)
ax.set_xticks(range(0, 61, 10))
ax.set_yticks(range(0, 61, 10))
ax.grid(True)

# 绘制裁剪窗口
win_x = [win_min[0], win_max[0], win_max[0], win_min[0], win_min[0]]
win_y = [win_min[1], win_min[1], win_max[1], win_max[1], win_min[1]]
ax.plot(win_x, win_y, 'r-', lw=2)

# 绘制线段
line_x = [p1[0], p2[0]]
line_y = [p1[1], p2[1]]
ax.plot(line_x, line_y, 'b-', lw=2)

plt.show()

这段代码的输出图形如下所示：