# ========== 题目1：文本数据基础 ==========
# 1. 打印"Hello"每个字符的ASCII码
print("===== 题目1-1：打印Hello的ASCII码 =====")
s = "Hello"
for char in s:
    print(f"字符 '{char}' 的ASCII码：{ord(char)}")

# 2. 验证chr(65)是大写字母A
print("\n===== 题目1-2：chr(65)验证 =====")
print(f"ASCII码65对应的字符是：{chr(65)}")


# ========== 题目3：向量基础（A=[3,4], B=[1,2]） ==========
print("\n===== 题目3：向量A=[3,4], B=[1,2] =====")
A = [3, 4]
B = [1, 2]

# 1. A + B
add_result = [A[0]+B[0], A[1]+B[1]]
print(f"1. A + B = {add_result}")

# 2. 2 × A
mul_result = [2 * A[0], 2 * A[1]]
print(f"2. 2 × A = {mul_result}")

# 3. A的长度（模）
import math
norm_A = math.sqrt(A[0]**2 + A[1]**2)
print(f"3. A的长度（模） = {norm_A}")


# ========== 题目4：向量点积与余弦相似度 ==========
print("\n===== 题目4：向量A=[1,2,3], B=[4,5,6] =====")
A = [1, 2, 3]
B = [4, 5, 6]

# 1. 点积
dot_product = sum(a * b for a, b in zip(A, B))
print(f"1. 点积 A·B = {dot_product}")

# 2. 余弦相似度
norm_A = math.sqrt(sum(a**2 for a in A))
norm_B = math.sqrt(sum(b**2 for b in B))
cos_sim = dot_product / (norm_A * norm_B)
print(f"2. 余弦相似度 = {cos_sim:.3f}")

# 3. 特殊情况：A=[1,0], B=[0,1]的余弦相似度
print("\n===== 题目4-3：向量A=[1,0], B=[0,1] =====")
A = [1, 0]
B = [0, 1]
dot_product2 = sum(a * b for a, b in zip(A, B))
norm_A2 = math.sqrt(sum(a**2 for a in A))
norm_B2 = math.sqrt(sum(b**2 for b in B))
cos_sim2 = dot_product2 / (norm_A2 * norm_B2)
print(f"余弦相似度 = {cos_sim2}")
print("解释：两个向量互相垂直，夹角为90°，余弦值为0")