42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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plt.rcParams["font.sans-serif"] = ["SimHei"]
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plt.rcParams["axes.unicode_minus"] = False
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# ---------------------- 图1：Loss曲线（训练loss） ----------------------
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loss_df = pd.read_csv("loss.csv")
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plt.figure(figsize=(10,4))
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plt.plot(loss_df["epoch"], loss_df["loss"], color="#e74c3c", linewidth=2, label="训练Loss")
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plt.xlabel("Epoch 训练轮次")
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plt.ylabel("Loss 损失值")
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plt.title("MLP训练Loss变化曲线")
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plt.legend()
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plt.grid(alpha=0.3)
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plt.tight_layout()
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# 创建images文件夹存放图片
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import os
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if not os.path.exists("images"):
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os.mkdir("images")
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plt.savefig("images/loss_curve.png", dpi=300)
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plt.close()
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# ---------------------- 图2：10类别预测分布柱状图 ----------------------
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label_df = pd.read_csv("my_labels.csv")
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cate_count = label_df["label"].value_counts().sort_index()
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cate_names = ["剧情","喜剧","科幻","悬疑","动作","爱情","动画","犯罪","奇幻","记录"]
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plt.figure(figsize=(10,4))
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bars = plt.bar([str(i) for i in range(10)], cate_count.values, color="#3498db")
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plt.xlabel("类别编号")
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plt.ylabel("样本数量")
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plt.title("10个电影类别样本分布柱状图")
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plt.xticks(range(10), cate_names, rotation=30)
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plt.grid(axis="y", alpha=0.3)
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plt.tight_layout()
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plt.savefig("images/category_bar.png", dpi=300)
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plt.close()
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print("可视化绘图完成，图片保存在 images/ 文件夹") |