From fc18287091d4146822c5ff338d4108cada1702bc Mon Sep 17 00:00:00 2001
From: 2509165038 <2509165038@student.edu.cn>
Date: Tue, 21 Apr 2026 11:24:24 +0800
Subject: [PATCH] =?UTF-8?q?=E5=AE=8C=E6=88=90=E4=BD=9C=E4=B8=9A?=
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---
 1.py | 41 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 41 insertions(+)
 create mode 100644 1.py

diff --git a/1.py b/1.py
new file mode 100644
index 0000000..64ac279
--- /dev/null
+++ b/1.py
@@ -0,0 +1,41 @@
+s = "Hello"
+for char in s:
+    print(f"字符'{char}'的ASCII码为: {ord(char)}")
+
+
+print(f"ASCII码65对应的字符为: {chr(65)}")
+##图像是规则数值矩阵易处理，文本是离散符号序列，需理解语义更难
+# 题目3
+A = [3, 4]
+B = [1, 2]
+def vector_add(a, b):
+    return [x + y for x, y in zip(a, b)]
+
+def scalar_multiply(scalar, vector):
+    return [scalar * x for x in vector]
+
+def vector_norm(vector):
+    return sum(x**2 for x in vector) ** 0.5
+
+print("题目3:")
+print("A + B =", vector_add(A, B))
+print("2 × A =", scalar_multiply(2, A))
+print("|A| =", vector_norm(A))
+A4 = [1, 2, 3]
+B4 = [4, 5, 6]
+def dot_product(a, b):
+    return sum(x * y for x, y in zip(a, b))
+def cosine_similarity(a, b):
+    norm_a = vector_norm(a)
+    norm_b = vector_norm(b)
+    if norm_a == 0 or norm_b == 0:
+        return 0.0
+    return dot_product(a, b) / (norm_a * norm_b)
+
+print("\n题目4:")
+print("A · B =", dot_product(A4, B4))
+print("余弦相似度 =", cosine_similarity(A4, B4))
+A5 = [1, 0]
+B5 = [0, 1]
+print("\n题目4 第3问:")
+print("A = [1, 0], B = [0, 1] 的余弦相似度 =", cosine_similarity(A5, B5))
\ No newline at end of file