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

plt.rcParams["font.sans-serif"] = ["SimHei"]
plt.rcParams["axes.unicode_minus"] = False

# ---------------------- 图1：Loss曲线（训练loss） ----------------------
loss_df = pd.read_csv("loss.csv")
plt.figure(figsize=(10,4))
plt.plot(loss_df["epoch"], loss_df["loss"], color="#e74c3c", linewidth=2, label="训练Loss")
plt.xlabel("Epoch 训练轮次")
plt.ylabel("Loss 损失值")
plt.title("MLP训练Loss变化曲线")
plt.legend()
plt.grid(alpha=0.3)
plt.tight_layout()

# 创建images文件夹存放图片
import os
if not os.path.exists("images"):
    os.mkdir("images")
plt.savefig("images/loss_curve.png", dpi=300)
plt.close()

# ---------------------- 图2：10类别预测分布柱状图 ----------------------
label_df = pd.read_csv("my_labels.csv")
cate_count = label_df["label"].value_counts().sort_index()
cate_names = ["剧情","喜剧","科幻","悬疑","动作","爱情","动画","犯罪","奇幻","记录"]

plt.figure(figsize=(10,4))
bars = plt.bar([str(i) for i in range(10)], cate_count.values, color="#3498db")
plt.xlabel("类别编号")
plt.ylabel("样本数量")
plt.title("10个电影类别样本分布柱状图")
plt.xticks(range(10), cate_names, rotation=30)
plt.grid(axis="y", alpha=0.3)
plt.tight_layout()
plt.savefig("images/category_bar.png", dpi=300)
plt.close()

print("可视化绘图完成，图片保存在 images/ 文件夹")