import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

def plot_dqn_training_curve(csv_file):
    # 读取CSV文件
    data = pd.read_csv(csv_file)

    # 检查是否包含所需列
    if 'Step' not in data.columns or 'Value' not in data.columns:
        raise ValueError("CSV文件必须包含'step'和'value'列")

    # 提取数据
    steps = data['Step']
    rewards = data['Value']

    # Plot the curve
    plt.plot(steps, rewards, label='Reward', color='blue')

    # Set title and axis labels
    # plt.title("DQN Training Curve", fontsize=16)
    plt.xlabel("Training Steps (w)", fontsize=14)
    plt.ylabel("Reward", fontsize=14)

    # Adjust x-axis ticks dynamically based on step range
    step_min, step_max = steps.min(), steps.max()
    tick_interval = (step_max - step_min) // 10  # Divide into 10 intervals
    ticks = np.arange(step_min, step_max + tick_interval, tick_interval)
    plt.xticks(ticks=ticks, labels=[f"{x//10000}w" for x in ticks])

    # Add grid and legend
    plt.grid(True, linestyle='--', alpha=0.7)

    # Show the plot
    plt.show()

if __name__ == "__main__":
    # 替换为你的CSV文件路径
    csv_file = r"runs\DQN-PartEnv_S0_ 2025-04-02 20_13\DQN-PartEnv_S0_ 2025-04-02 20_13.csv"
    plot_dqn_training_curve(csv_file)