calc—_v2

This commit is contained in:
2025-12-07 16:01:42 +08:00
parent b9da6d9592
commit 1d416d4dd8
2 changed files with 66 additions and 51 deletions

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@@ -6,11 +6,11 @@
# 1. 初始化设置
# 修改上一级目录权限
chmod -R u+w ../Screen
chmod -R u+w ../screen
# 启用 screen 环境 (Python 3.11)
source $(conda info --base)/etc/profile.d/conda.sh
conda activate screen
conda activate ~/anaconda3/envs/screen
# 设置当前目录为 PYTHONPATH
cd py/
@@ -31,7 +31,7 @@ python make_sh.py
# 2. 切换环境运行 Zeo++
echo "============ Stage 2: Zeo++ Calculations ============"
conda deactivate
conda activate zeo
conda activate ~/anaconda3/envs/zeo
# 进入数据目录执行所有生成的 shell 脚本
cd ../data/after_step1
@@ -46,7 +46,7 @@ fi
echo "============ Stage 3: Data Extraction & Advanced Screening ============"
# 切回 screen 环境
conda deactivate
conda activate screen
conda activate ~/anaconda3/envs/screen
cd ../../py
# 提取日志数据

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@@ -1,12 +1,10 @@
import os
import pandas as pd
import math
import shutil
# ================= 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},
@@ -16,7 +14,7 @@ THRESHOLDS = {
# 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)
DATA_SOURCE_DIR = "../data/after_step1" # 原始 CIF 文件所在的根目录
TARGET_DIR = "../data/after_screening" # 筛选后放置软链接的目标目录
@@ -26,28 +24,21 @@ 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
# 筛选逻辑
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
@@ -56,39 +47,56 @@ def check_requirements(row, anion_type):
return False
def create_symlink(group_name, anion_name, material_id):
def create_result_file(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
创建结果文件 (这里改为直接复制,软链接在跨文件系统或某些环境下可能不稳定,复制更稳妥)
如果确实需要软链接,可以将 shutil.copy 换回 os.symlink
"""
# 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
# 1. 构建源文件路径
# 正确路径: ../data/after_step1/Group/MaterialID/MaterialID.cif
# 例如: ../data/after_step1/S/195819/195819.cif
# 注意:如果原本结构是 S+O/S/ID... 这里会自动适配
# 这里的路径逻辑要非常小心,取决于 extract_data.py 是怎么生成 CSV 目录结构的
# 如果 CSV 在 output/S/S.csv -> 对应源文件在 after_step1/S/...
# 如果 CSV 在 output/S+O/S/S.csv -> 对应源文件在 after_step1/S+O/S/...
if group_name == anion_name:
# 单阴离子情况 (如 output/S/S.csv -> after_step1/S/ID/ID.cif)
rel_source_path = os.path.join(DATA_SOURCE_DIR, group_name, material_id, f"{material_id}.cif")
else:
# 混合阴离子情况 (如 output/S+O/S/S.csv -> after_step1/S+O/S/ID/ID.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
# 2. 构建目标文件夹路径 ../data/after_screening/Group/Anion
if group_name == anion_name:
target_subdir = os.path.join(TARGET_DIR, group_name)
else:
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")
# 3. 构建目标文件路径
target_file_path = os.path.join(target_subdir, f"{material_id}.cif")
# 4. 创建链接
# 4. 执行复制 (改为复制以确保结果独立)
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)
if os.path.exists(target_file_path):
os.remove(target_file_path)
shutil.copy(abs_source_path, target_file_path)
# 如果你非常确定要软链接,请注释上一行,解开下一行:
# os.symlink(abs_source_path, target_file_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}")
print(f"创建文件失败 {material_id}: {e}")
def process_all_csvs():
@@ -101,46 +109,53 @@ def process_all_csvs():
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
# --- 核心修正 1: 路径解析逻辑 ---
# 获取相对于 output 根目录的路径部分
# 例如 root = ../output/S -> rel_root = S
# 例如 root = ../output/S+O/S -> rel_root = S+O/S
rel_root = os.path.relpath(root, CSV_ROOT_DIR)
path_parts = rel_root.split(os.sep)
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]
# 解析 Group 和 Anion
if len(path_parts) == 1:
# 单层目录: output/S -> Group=S, Anion=S
group_name = path_parts[0]
anion_name = path_parts[0]
elif len(path_parts) >= 2:
# 双层目录: output/S+O/S -> Group=S+O, Anion=S
group_name = path_parts[0]
anion_name = path_parts[1]
else:
print(f"跳过路径结构异常的 CSV: {csv_path}")
# 根目录下直接有csv的情况 (不应该发生)
continue
# 确保这是一个有效的阴离子类型
if anion_name not in THRESHOLDS:
print(f"跳过不支持的阴离子类型: {anion_name}")
continue
print(f"正在处理: Group={group_name}, Anion={anion_name} ({file})")
# 读取 CSV
df = pd.read_csv(csv_path)
# --- 核心修正 2: 防止 Filename 被读取为浮点数 ---
# dtypeStr={'Filename': str} 强制将第一列读取为字符串
df = pd.read_csv(csv_path, dtype={'Filename': str})
pass_count = 0
total_count = len(df)
for index, row in df.iterrows():
material_id = str(row['Filename'])
# 去除可能存在的 .0 后缀 (以防万一 CSV 里已经写成了浮点格式)
material_id = str(row['Filename']).replace('.0', '')
if check_requirements(row, anion_name):
create_symlink(group_name, anion_name, material_id)
create_result_file(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")
print(f" - 完成: {pass_count}/{total_count} 个材料通过筛选并保存至 {TARGET_DIR}")
if __name__ == "__main__":