43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
# 1. 输出 "Hello" 每个字符的 ASCII 码
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text = "Hello"
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print([ord(c) for c in text])
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# 2. chr() 验证 65 = A
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print(chr(65))
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# 3. 向量运算
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A = (3, 4)
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B = (1, 2)
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print("A+B =", (A[0]+B[0], A[1]+B[1]))
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print("2*A =", (2*A[0], 2*A[1]))
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print("A的模长 =", (A[0]**2 + A[1]**2)**0.5)
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# 4. 点积与余弦相似度
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import math
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A = [1,2,3]
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B = [4,5,6]
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dot = sum(a*b for a,b in zip(A,B))
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print("点积 =", dot)
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normA = math.sqrt(sum(x**2 for x in A))
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normB = math.sqrt(sum(x**2 for x in B))
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cos_sim = dot / (normA * normB)
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print("余弦相似度 =", round(cos_sim, 4))
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# 垂直向量余弦相似度
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A2, B2 = [1,0], [0,1]
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dot2 = sum(a*b for a,b in zip(A2,B2))
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normA2 = math.sqrt(sum(x**2 for x in A2))
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normB2 = math.sqrt(sum(x**2 for x in B2))
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cos_sim2 = dot2 / (normA2 * normB2)
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print("垂直向量余弦相似度 =", cos_sim2)
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# 5. 词袋模型向量
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vocab = ['java','python','编程','语言']
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doc1 = [0,1,1,1]
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doc2 = [1,0,1,1]
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doc3 = [0,3,0,0]
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print("词表:", vocab)
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print("Doc1:", doc1)
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print("Doc2:", doc2)
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print("Doc3:", doc3) |