File size: 2,300 Bytes
eeabcff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | import numpy as np
from rdkit import Chem
# from IsoSpecPy import IsoSpec
import IsoSpecPy as iso
def generate_isotopic_pattern(mol_formula, charge=1):
"""生成理论同位素模式"""
# 初始化IsoSpec计算器
# calculator = IsoSpec.IsoTotalProb(formula=mol_formula,
# charge=charge,
# absolute_accuracy=0.9)
calculator = iso.IsoTotalProb(formula=mol_formula,
charge=charge,
absolute_accuracy=0.9)
# 获取峰列表 (m/z, 强度)
peaks = calculator.get_peaks()
# 归一化强度
intensities = np.array([p[1] for p in peaks])
intensities /= np.max(intensities)
return [(p[0], intensities[i]) for i, p in enumerate(peaks)]
def compare_isotopic_patterns(exp_pattern, theory_pattern, tolerance=0.01):
"""比较实验与理论同位素模式"""
score = 0.0
matched_peaks = 0
for exp_mz, exp_int in exp_pattern:
for theo_mz, theo_int in theory_pattern:
if abs(exp_mz - theo_mz) <= tolerance:
# 余弦相似度计算
score += exp_int * theo_int
matched_peaks += 1
break
# 归一化得分
if matched_peaks > 0:
score /= matched_peaks
return score
# 示例用法
if __name__ == "__main__":
# 实验数据 (示例值)
experimental_data = [
(151.063, 1.00), # 基峰
(152.066, 0.32),
(153.069, 0.05)
]
# 候选分子式
candidate_formulas = ["C8H10N2O2", "C7H10N4O", "C9H10O3"]
best_formula = None
best_score = -1
for formula in candidate_formulas:
# 生成理论同位素模式
theoretical_pattern = generate_isotopic_pattern(formula, charge=1)
# 比较相似度
score = compare_isotopic_patterns(experimental_data, theoretical_pattern)
print(f"Formula: {formula} | Score: {score:.4f}")
if score > best_score:
best_score = score
best_formula = formula
print(f"\nBest match: {best_formula} (Score: {best_score:.4f})")
|