59 lines
1.5 KiB
Python
59 lines
1.5 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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# # ==============================
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# # 1️⃣ 读取 CSV
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# # ==============================
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# csv_file = "convergence0119_data.csv"
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# df = pd.read_csv(csv_file)
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#
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# # ==============================
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# # 2️⃣ 选择一次完整 GA 运行
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# # ==============================
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# target_ts = "2026-01-26 22:30:22"
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# run_df = df[df["Timestamp"] == target_ts].copy()
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#
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# # 按代数排序，取前 50 代
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# run_df = run_df.sort_values("Generation").head(100)
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# 读取 CSV
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csv_file = "convergence0119_data.csv"
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df = pd.read_csv(csv_file)
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# 按 Generation 排序
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run_df = df.sort_values("Generation")
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# ==============================
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# 3️⃣ 提取数据
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# ==============================
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generations = run_df["Generation"].values
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best_fitness = run_df["Best_Fitness_Percentage"].values
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# ==============================
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# 4️⃣ 计算滑动平均（窗口=5，可调）
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# ==============================
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window_size = 5
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run_df["MA"] = run_df["Best_Fitness_Percentage"].rolling(
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window=window_size,
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min_periods=1
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).mean()
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# ==============================
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# 5️⃣ 绘图：点 + 连线 + 滑动平均
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# ==============================
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plt.figure(figsize=(10, 6))
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# 原始点
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plt.scatter(generations, best_fitness, s=30, alpha=0.6, label="Best Error")
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# 连线
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plt.plot(generations, best_fitness, linewidth=1, alpha=0.6)
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plt.xlabel("Generation")
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plt.ylabel("Best Error")
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plt.legend()
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plt.grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig("ga_convergence_me_.png", dpi=300)
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plt.show()
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