feat(toolkit): ship macro_lactone_toolkit package
Unify macrolactone detection, numbering, fragmentation, and splicing under the installable macro_lactone_toolkit package. - replace legacy src.* modules with the new package layout - add analyze/number/fragment CLI entrypoints and pixi tasks - migrate tests, README, and scripts to the new package API
This commit is contained in:
421
scripts/batch_process_multi_rings.py
Executable file → Normal file
421
scripts/batch_process_multi_rings.py
Executable file → Normal file
@@ -1,423 +1,10 @@
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#!/usr/bin/env python3
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"""
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批量处理12-20元环大环内酯分子
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处理文件: data/ring12_20/temp.csv
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输出文件夹: output/ring{N}_fragments/ (N=12,13,14...20)
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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# 添加项目根目录到 Python 路径
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# 获取脚本所在目录的父目录（项目根目录）
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script_dir = Path(__file__).resolve().parent
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project_root = script_dir.parent
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sys.path.insert(0, str(project_root))
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from rdkit import Chem
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import pandas as pd
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import json
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from tqdm import tqdm
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from datetime import datetime
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from collections import defaultdict
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from src.ring_numbering import get_ring_atoms
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from src.fragment_cleaver import cleave_side_chains
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from macro_lactone_toolkit.cli import main
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def find_lactone_carbons(mol, ring_size):
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"""
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找到指定环大小的环上的内酯羰基碳原子
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返回所有环上内酯碳的索引列表
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"""
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# 获取指定环大小的所有环原子
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ring_pattern = Chem.MolFromSmarts(f"[r{ring_size}]")
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if ring_pattern is None:
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return []
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ring_matches = mol.GetSubstructMatches(ring_pattern)
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ring_atoms = list(set([match[0] for match in ring_matches]))
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if len(ring_atoms) == 0:
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return []
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# 使用更严格的SMARTS模式：环上的氧连接到环上的羰基碳
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# [r{ring_size};#8] 环上的氧，连接到 [r{ring_size};#6] 环上的碳，该碳有双键氧 (=O)
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lactone_pattern = Chem.MolFromSmarts(f"[r{ring_size};#8][r{ring_size};#6](=[#8])")
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if lactone_pattern is None:
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return []
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matches = mol.GetSubstructMatches(lactone_pattern)
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# 提取环上的内酯碳索引 (match[1]是羰基碳)
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lactone_carbons = []
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for match in matches:
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if len(match) >= 2:
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carbonyl_carbon = match[1] # 羰基碳
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# 确保这个碳确实在指定大小的环上
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if carbonyl_carbon in ring_atoms:
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lactone_carbons.append(carbonyl_carbon)
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return list(set(lactone_carbons)) # 去重
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def order_ring_atoms_clockwise(mol, ring_atoms, start_atom):
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"""顺时针排列环原子"""
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if start_atom not in ring_atoms:
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raise ValueError("Start atom is not in the ring")
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ordered = [start_atom]
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visited = {start_atom}
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current = start_atom
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while len(ordered) < len(ring_atoms):
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atom = mol.GetAtomWithIdx(current)
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# 找到下一个环原子
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next_atom = None
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for neighbor in atom.GetNeighbors():
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neighbor_idx = neighbor.GetIdx()
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if neighbor_idx in ring_atoms and neighbor_idx not in visited:
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next_atom = neighbor_idx
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break
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if next_atom is None:
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# 尝试从起点反向遍历
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if len(ordered) < len(ring_atoms):
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atom = mol.GetAtomWithIdx(start_atom)
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for neighbor in atom.GetNeighbors():
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neighbor_idx = neighbor.GetIdx()
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if neighbor_idx in ring_atoms and neighbor_idx not in visited:
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ordered.insert(0, neighbor_idx)
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visited.add(neighbor_idx)
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current = neighbor_idx
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break
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else:
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break
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else:
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break
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else:
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ordered.append(next_atom)
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visited.add(next_atom)
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current = next_atom
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return ordered
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def assign_ring_numbering_general(mol, ring_size):
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"""
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为任意大小的环分配编号
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返回: (numbering_dict, lactone_carbon) 或 (None, None) 或 ('multiple_lactones', lactone_list)
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"""
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# 找到内酯碳
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lactone_carbons = find_lactone_carbons(mol, ring_size)
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if len(lactone_carbons) == 0:
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return None, None
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if len(lactone_carbons) > 1:
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return 'multiple_lactones', lactone_carbons
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lactone_c = lactone_carbons[0]
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# 获取环原子
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ring_atoms = get_ring_atoms(mol)
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# 如果环原子数不匹配
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if len(ring_atoms) != ring_size:
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return None, None
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# 排列环原子
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try:
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ordered_atoms = order_ring_atoms_clockwise(mol, ring_atoms, lactone_c)
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except Exception:
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return None, None
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# 创建编号字典
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numbering = {}
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for position, atom_idx in enumerate(ordered_atoms, start=1):
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numbering[atom_idx] = position
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return numbering, lactone_c
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def validate_numbering_general(numbering, ring_size):
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"""验证编号是否正确"""
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if numbering is None or numbering == 'multiple_lactones':
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return False
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if len(numbering) != ring_size:
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return False
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positions = set(numbering.values())
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if positions != set(range(1, ring_size + 1)):
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return False
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return True
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def get_ring_size_from_smiles(smiles):
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"""从SMILES获取分子中的环大小"""
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mol = Chem.MolFromSmiles(smiles)
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if mol is None:
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return []
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ring_sizes = set()
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for ring_size in range(12, 21): # 12-20
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pattern = Chem.MolFromSmarts(f"[r{ring_size}]")
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if pattern is not None:
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matches = mol.GetSubstructMatches(pattern)
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if matches:
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unique_atoms = list(set([match[0] for match in matches]))
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if len(unique_atoms) == ring_size:
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ring_sizes.add(ring_size)
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return sorted(list(ring_sizes))
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def process_single_molecule(idx, row, ring_size, output_base_dir, log_file, error_log_file, multiple_lactone_log):
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"""处理单个分子"""
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try:
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# 获取分子信息
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molecule_id = row.get('IDs', f'mol_{idx}')
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molecule_name = row.get('molecule_pref_name', 'Unknown')
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smiles = row['smiles']
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parent_id = f"ring{ring_size}_mol_{idx}"
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# 解析SMILES
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mol = Chem.MolFromSmiles(smiles)
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if mol is None:
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log_message(f"分子 {idx} ({molecule_id}) SMILES解析失败", error_log_file, 'error')
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return None, 'parse_failed'
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# 分配编号
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numbering, lactone_c = assign_ring_numbering_general(mol, ring_size)
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# 检查环上是否有多个内酯键
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if numbering == 'multiple_lactones':
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log_message(
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f"分子 {idx} ({molecule_id}, {molecule_name}) 环上有{len(lactone_c)}个内酯键，已剔除。环上内酯碳索引: {lactone_c}",
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multiple_lactone_log,
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'info'
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)
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return None, 'multiple_lactones'
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if numbering is None:
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log_message(f"分子 {idx} ({molecule_id}) 编号失败", error_log_file, 'error')
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return None, 'numbering_failed'
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# 验证编号
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if not validate_numbering_general(numbering, ring_size):
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log_message(f"分子 {idx} ({molecule_id}) 编号验证失败", error_log_file, 'error')
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return None, 'validation_failed'
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# 侧链断裂
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try:
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mol_fragments = cleave_side_chains(mol, smiles, parent_id, numbering)
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except Exception as e:
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log_message(f"分子 {idx} ({molecule_id}) 裂解失败: {str(e)}", error_log_file, 'error')
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return None, 'cleavage_failed'
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# 创建分子专属文件夹
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mol_output_dir = output_base_dir / parent_id
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mol_output_dir.mkdir(parents=True, exist_ok=True)
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# 保存整个MoleculeFragments对象
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mol_fragments_path = mol_output_dir / f"{parent_id}_all_fragments.json"
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mol_fragments.to_json_file(str(mol_fragments_path))
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# 保存每个碎片
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for frag in mol_fragments.fragments:
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frag_path = mol_output_dir / f"{frag.fragment_id}.json"
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frag.to_json_file(str(frag_path))
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# 保存分子信息到metadata
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metadata = {
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'parent_id': parent_id,
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'molecule_id': molecule_id,
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'molecule_name': molecule_name,
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'smiles': smiles,
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'ring_size': ring_size,
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'num_fragments': len(mol_fragments.fragments),
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'processing_date': datetime.now().isoformat()
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}
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metadata_path = mol_output_dir / 'metadata.json'
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with open(metadata_path, 'w', encoding='utf-8') as f:
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json.dump(metadata, f, indent=2, ensure_ascii=False)
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return len(mol_fragments.fragments), 'success'
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except Exception as e:
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log_message(f"分子 {idx} 未预期错误: {str(e)}", error_log_file, 'error')
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return None, 'unexpected_error'
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def log_message(message, log_file, log_type='info'):
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"""记录日志信息"""
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timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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log_entry = f"[{timestamp}] {message}\n"
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with open(log_file, 'a', encoding='utf-8') as f:
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f.write(log_entry)
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if log_type == 'error':
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tqdm.write(f"❌ {message}")
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elif log_type == 'info' and 'multiple' not in log_file.name:
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tqdm.write(f"✓ {message}")
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def main():
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print("="*80)
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print("12-20元环大环内酯批量处理程序")
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print("="*80)
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print()
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# 读取数据
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input_file = Path('data/ring12_20/temp.csv')
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if not input_file.exists():
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print(f"❌ 错误: 找不到输入文件 {input_file}")
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return
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df = pd.read_csv(input_file)
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print(f"✓ 读取数据集: {len(df)} 个分子")
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print(f" 文件: {input_file}")
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print()
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# 第一步：按环大小分类
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print("步骤 1: 按环大小分类分子...")
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print()
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ring_size_groups = defaultdict(list)
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for idx in tqdm(range(len(df)), desc="分类进度"):
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smiles = df.iloc[idx]['smiles']
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ring_sizes = get_ring_size_from_smiles(smiles)
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for ring_size in ring_sizes:
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if 12 <= ring_size <= 20:
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ring_size_groups[ring_size].append(idx)
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print()
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print("分类结果:")
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for ring_size in sorted(ring_size_groups.keys()):
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print(f" {ring_size}元环: {len(ring_size_groups[ring_size])} 个分子")
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print()
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# 第二步：对每种环大小分别处理
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print("步骤 2: 处理各环大小分子...")
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print()
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all_stats = {}
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for ring_size in sorted(ring_size_groups.keys()):
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indices = ring_size_groups[ring_size]
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print(f"\n处理 {ring_size}元环 ({len(indices)} 个分子)...")
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print("-" * 60)
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# 创建输出文件夹
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output_base_dir = Path(f'output/ring{ring_size}_fragments')
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output_base_dir.mkdir(parents=True, exist_ok=True)
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# 创建日志文件
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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log_file = output_base_dir / f'processing_log_{timestamp}.txt'
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error_log_file = output_base_dir / f'error_log_{timestamp}.txt'
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multiple_lactone_log = output_base_dir / f'multiple_lactone_log_{timestamp}.txt'
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# 统计信息
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stats = {
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'ring_size': ring_size,
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'total': len(indices),
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'success': 0,
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'failed_parse': 0,
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'failed_numbering': 0,
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'failed_validation': 0,
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'failed_cleavage': 0,
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'failed_unexpected': 0,
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'multiple_lactones': 0,
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'total_fragments': 0
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}
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log_message(f"开始处理 {len(indices)} 个{ring_size}元环分子", log_file)
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# 处理每个分子
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for idx in tqdm(indices, desc=f"Ring-{ring_size}"):
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num_fragments, status = process_single_molecule(
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idx, df.iloc[idx], ring_size,
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output_base_dir, log_file, error_log_file, multiple_lactone_log
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)
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if status == 'success':
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stats['success'] += 1
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stats['total_fragments'] += num_fragments
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elif status == 'parse_failed':
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stats['failed_parse'] += 1
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elif status == 'numbering_failed':
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stats['failed_numbering'] += 1
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elif status == 'validation_failed':
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stats['failed_validation'] += 1
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elif status == 'cleavage_failed':
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stats['failed_cleavage'] += 1
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elif status == 'multiple_lactones':
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stats['multiple_lactones'] += 1
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else:
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stats['failed_unexpected'] += 1
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# 保存统计结果
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stats_file = output_base_dir / 'processing_statistics.json'
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with open(stats_file, 'w', encoding='utf-8') as f:
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json.dump(stats, f, indent=2)
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all_stats[ring_size] = stats
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# 打印该环大小的统计
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print()
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print(f"{ring_size}元环处理结果:")
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print(f" 成功: {stats['success']}/{stats['total']} ({stats['success']/stats['total']*100:.1f}%)")
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print(f" 碎片数: {stats['total_fragments']}")
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if stats['success'] > 0:
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print(f" 平均碎片: {stats['total_fragments']/stats['success']:.2f} 个/分子")
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print(f" 多个内酯键: {stats['multiple_lactones']}")
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log_message(f"处理完成: 成功 {stats['success']}/{stats['total']}", log_file)
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# 第三步：总结
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print()
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print("="*80)
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print("所有环大小处理完成！")
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print("="*80)
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print()
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print("总体统计:")
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total_molecules = 0
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total_success = 0
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total_fragments = 0
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total_multiple_lactones = 0
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for ring_size, stats in sorted(all_stats.items()):
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total_molecules += stats['total']
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total_success += stats['success']
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total_fragments += stats['total_fragments']
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total_multiple_lactones += stats['multiple_lactones']
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print(f" 总分子数: {total_molecules}")
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print(f" 总成功数: {total_success} ({total_success/total_molecules*100:.1f}%)")
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print(f" 总碎片数: {total_fragments}")
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if total_success > 0:
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print(f" 平均碎片: {total_fragments/total_success:.2f} 个/分子")
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print(f" 多内酯键分子: {total_multiple_lactones}")
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print()
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print("各环大小输出文件夹:")
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for ring_size in sorted(all_stats.keys()):
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output_dir = Path(f'output/ring{ring_size}_fragments')
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print(f" {ring_size}元环: {output_dir}")
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print()
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if __name__ == '__main__':
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if __name__ == "__main__":
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sys.argv = ["macro-lactone-toolkit", "fragment", *sys.argv[1:]]
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main()
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Block a user