besmnncorrect 0.1.1

A batch effect correction method for subregional radiomics dataset

if name == "main": # 示例用法 dataA = pd.read_csv('./dataA.csv', header=None).values dataB = pd.read_csv('./dataB.csv', header=None).values

aligner = BatchAlignerAdvanced(
    pca_components=0.99,
    init_strategy='mi_based',
    noise_scale='auto',
    max_iter=30,
    verbose_changes=True
)

batch1 = dataA[:, :-1].astype(np.float64)
batch2 = dataB[:, :-1].astype(np.float64)
final_weights, final_pairs = aligner.fit(batch1, batch2)
adjusted_B, used_pairs = aligner.adjust_batch(batch1, batch2)

print("\n=== 最终结果 ===")
print(f"匹配对数: {len(final_pairs)}")
print(f"权重范围: {np.min(final_weights):.2f}-{np.max(final_weights):.2f}")
print(f"权重中位数: {np.median(final_weights):.2f}")
print("前10个特征权重:", np.round(final_weights[:10], 2))
print(final_pairs)
pd.DataFrame(adjusted_B).to_csv('corrected_B02.csv', index=False, header=False)