import json
import os
import random
from tiny_shuffle import random_swap_contiguous # type: ignore


file_path = "/vol/zhaoy/ds-ocr/data/CCI3-Data/data/part-00001-6f0afd98-d375-4d7f-8299-ac5e070bf4fc-c000.jsonl"
save_path = f"/vol/zhaoy/ds-ocr/data/CCI3-Data/random_sample100/input.json"

# 1. 读取 jsonl 文件
data = []
with open(file_path, "r", encoding="utf-8", errors="ignore") as f:
    for line in f:
        line = line.strip()
        if not line:
            continue
        try:
            data.append(json.loads(line))
        except json.JSONDecodeError:
            continue

print(f"✅ 已读取 {len(data)} 条样本")

# 2. 筛选满足条件的样本
filtered = [
    item for item in data
    if 100 <= item.get("meta_info", {}).get("words_count", 0) <= 10000
]
print(f"✅ 满足条件的样本数: {len(filtered)}")

# 3. 随机抽取 500 条
filtered = random.sample(filtered, min(200, len(filtered)))

# 4. 组织格式
processed = []
os.makedirs("images", exist_ok=True)

for i, item in enumerate(filtered, 1):
    sample_id = f"RS{i:03d}"
    image_path = f"images/{sample_id}.png"
    content = item.get("text", "") or item.get("content", "")
    content = content.replace("\n", "").replace(" ", "")  # 预处理的时候就把这些去掉

    # tiny_shuffled_content, spans = random_swap_contiguous(content, n_swaps=1)
    # shuffled_content = ''.join(random.sample(content, len(content)))

    processed.append({
        "id": sample_id,
        "data_source": "CCI3",
        "language": "zh",
        "image_path": image_path,
        "content": content,
        "length": len(content),
        # "tiny_shuffled_content": tiny_shuffled_content,
        # "spans": spans,
        # "shuffled_content": shuffled_content
    })

# 5. 保存为 JSON 文件
with open(save_path, "w", encoding="utf-8") as f:
    json.dump(processed, f, ensure_ascii=False, indent=2)

print(f"✅ 已生成 {len(processed)} 条样本，保存至：{save_path}")




# 6. 画 length 分布柱状图
import matplotlib.pyplot as plt
from collections import Counter
import numpy as np

lengths = [p["length"] for p in processed]
bin_width = 100                           # 每 50 字一个柱
max_len = max(lengths) if lengths else 0
bins = list(range(0, max_len + bin_width, bin_width))
hist, edges = np.histogram(lengths, bins=bins)

plt.figure(figsize=(10, 5))
plt.bar(edges[:-1], hist, width=bin_width, align="edge", color="skyblue", edgecolor="black")
plt.xticks(edges[::2], rotation=45)
plt.xlabel("Length (characters)")
plt.ylabel("Count")
plt.title("Random-Sample Length Distribution")
plt.tight_layout()
plt.savefig("/vol/zhaoy/ds-ocr/data/CCI3-Data/random_sample100/length_dist.png", dpi=300)
print("✅ 柱状图已保存为 length_dist.png")