import os
import pandas as pd
import math

# ================= 配置区域 =================
# 定义各阴离子的筛选阈值
# perc: Percolation diameter (对应 Step 2, 大于此值)
# min_d: Minimum of d (对应 Step 3, 小于此值)
# node: Maximum node length (对应 Step 4, 大于此值)
THRESHOLDS = {
    "O": {"perc": 0.50, "min_d": 3.0, "node": 2.2},
    "S": {"perc": 0.55, "min_d": 3.0, "node": 2.2},
    "Cl": {"perc": 0.45, "min_d": 3.0, "node": 2.0},
    "Br": {"perc": 0.45, "min_d": 3.0, "node": 2.0}
}

# 路径配置
CSV_ROOT_DIR = "../output"  # CSV 所在的根目录
DATA_SOURCE_DIR = "../data/after_step1"  # 原始 CIF 文件所在的根目录 (用于创建链接源)
TARGET_DIR = "../data/after_screening"  # 筛选后放置软链接的目标目录


# ===========================================

def check_requirements(row, anion_type):
    """
    检查单行数据是否符合要求
    """
    # 获取该阴离子类型的阈值配置
    config = THRESHOLDS.get(anion_type)
    if not config:
        print(f"Warning: 未知的阴离子类型 {anion_type}，跳过筛选。")
        return False

    try:
        # 获取数值 (处理可能的空值或非数字情况)
        perc = float(row["Percolation Diameter (A)"])
        min_d = float(row["Minimum of d"])
        node = float(row["Maximum Node Length (A)"])

        # 检查是否为 NaN
        if math.isnan(perc) or math.isnan(min_d) or math.isnan(node):
            return False

        # --- 筛选逻辑 ---
        # Step 2: 连通孔径 > 阈值
        c1 = perc > config["perc"]
        # Step 3: 最短距离 < 3.0 (所有元素目前都是3.0)
        c2 = min_d < config["min_d"]
        # Step 4: 扩大锂离子节点 > 阈值
        c3 = node > config["node"]

        return c1 and c2 and c3

    except (ValueError, TypeError):
        return False


def create_symlink(group_name, anion_name, material_id):
    """
    创建软链接
    源: ../data/after_step1/Group/Anion/ID/ID.cif
    目: ../data/after_screening/Group/Anion/ID.cif
    """
    # 1. 构建源文件路径 (必须使用绝对路径以确保软链接在任何地方都有效)
    # 注意：根据你修改后的 step1，文件在 ID 文件夹内，如 141/141.cif
    rel_source_path = os.path.join(DATA_SOURCE_DIR, group_name, anion_name, material_id, f"{material_id}.cif")
    abs_source_path = os.path.abspath(rel_source_path)

    if not os.path.exists(abs_source_path):
        print(f"源文件不存在: {abs_source_path}")
        return

    # 2. 构建目标文件夹路径
    target_subdir = os.path.join(TARGET_DIR, group_name, anion_name)
    if not os.path.exists(target_subdir):
        os.makedirs(target_subdir)

    # 3. 构建目标链接路径
    target_link_path = os.path.join(target_subdir, f"{material_id}.cif")

    # 4. 创建链接
    try:
        # 如果目标已经存在（可能是旧的链接），先删除
        if os.path.exists(target_link_path) or os.path.islink(target_link_path):
            os.remove(target_link_path)

        os.symlink(abs_source_path, target_link_path)
        # print(f"Link: {material_id} -> Passed")
    except OSError as e:
        print(f"创建软链接失败 {material_id}: {e}")


def process_all_csvs():
    """
    遍历 output 文件夹下的所有 CSV 并处理
    """
    if not os.path.exists(CSV_ROOT_DIR):
        print(f"CSV 目录不存在: {CSV_ROOT_DIR}")
        return

    print("开始执行 Step 2-4 联合筛选...")

    # 遍历 output 目录
    # 结构预期: ../output/Group/Anion/Anion.csv (例如 ../output/O+S/O/O.csv 或 ../output/O/O.csv)
    for root, dirs, files in os.walk(CSV_ROOT_DIR):
        for file in files:
            if file.endswith(".csv"):
                csv_path = os.path.join(root, file)

                # 推断 Group 和 Anion
                # root 的末尾应该是 .../Group/Anion
                # 例如 root = ../output/O+S/O

                path_parts = os.path.normpath(root).split(os.sep)
                # 倒数第一级是 Anion (O), 倒数第二级是 Group (O+S)
                if len(path_parts) >= 2:
                    anion_name = path_parts[-1]
                    group_name = path_parts[-2]
                else:
                    print(f"跳过路径结构异常的 CSV: {csv_path}")
                    continue

                # 确保这是一个有效的阴离子类型
                if anion_name not in THRESHOLDS:
                    continue

                print(f"正在处理: Group={group_name}, Anion={anion_name} ({file})")

                # 读取 CSV
                df = pd.read_csv(csv_path)

                pass_count = 0
                total_count = len(df)

                for index, row in df.iterrows():
                    material_id = str(row['Filename'])

                    if check_requirements(row, anion_name):
                        create_symlink(group_name, anion_name, material_id)
                        pass_count += 1

                print(f"  - 完成: {pass_count}/{total_count} 个材料通过筛选并建立链接。")


if __name__ == "__main__":
    process_all_csvs()