41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
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import matplotlib.pyplot as plt
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import pandas as pd
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import numpy as np
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def plot_dqn_training_curve(csv_file):
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# 读取CSV文件
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data = pd.read_csv(csv_file)
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# 检查是否包含所需列
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if 'Step' not in data.columns or 'Value' not in data.columns:
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raise ValueError("CSV文件必须包含'step'和'value'列")
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# 提取数据
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steps = data['Step']
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rewards = data['Value']
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# Plot the curve
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plt.plot(steps, rewards, label='Reward', color='blue')
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# Set title and axis labels
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# plt.title("DQN Training Curve", fontsize=16)
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plt.xlabel("Training Steps (w)", fontsize=14)
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plt.ylabel("Reward", fontsize=14)
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# Adjust x-axis ticks dynamically based on step range
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step_min, step_max = steps.min(), steps.max()
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tick_interval = (step_max - step_min) // 10 # Divide into 10 intervals
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ticks = np.arange(step_min, step_max + tick_interval, tick_interval)
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plt.xticks(ticks=ticks, labels=[f"{x//10000}w" for x in ticks])
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# Add grid and legend
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plt.grid(True, linestyle='--', alpha=0.7)
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# Show the plot
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plt.show()
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if __name__ == "__main__":
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# 替换为你的CSV文件路径
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csv_file = r"runs\DQN-PartEnv_S0_ 2025-04-02 20_13\DQN-PartEnv_S0_ 2025-04-02 20_13.csv"
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plot_dqn_training_curve(csv_file)
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