| # import scanpy as sc | |
| # | |
| # file_path = '/scDifformer/data/240412_test/raw_h5ad/zheng68k_fold0_test.h5ad' | |
| # | |
| # adata = sc.read_h5ad(file_path) | |
| # adata[:3, :3].to_df().to_excel('/scDifformer/data/240412_test/data_info/h5ad_info.xlsx') | |
| # import loompy | |
| # | |
| # file_path = '/scDifformer/data/240412_test/looms/zheng68k_fold0_test.loom' | |
| # | |
| # # 使用loompy连接loom文件 | |
| # with loompy.connect(file_path) as ds: | |
| # | |
| # # 打印所有的列属性（column attributes, 即细胞元数据） | |
| # print("\nColumn:") | |
| # for key, val in ds.ca.items(): | |
| # print(f"{key}: {val}") | |
| # | |
| # # 打印所有的行属性（row attributes, 即基因元数据） | |
| # print("\nRow:") | |
| # for key, val in ds.ra.items(): | |
| # print(f"{key}: {val}") | |
| # | |
| # # 打印矩阵的一部分（例如，前5个基因和前5个细胞的表达量） | |
| # print("\nData matrix:") | |
| # matrix_slice = ds[:, :5] # 获取所有基因在前5个细胞中的表达量 | |
| # print(matrix_slice) | |
| # import pickle | |
| # | |
| # file_path = '/scDifformer/data/240412_test/material/gene_median_dictionary.pkl' | |
| # | |
| # with open(file_path, 'rb') as file: | |
| # data = pickle.load(file) | |
| # | |
| # print(data) | |
| # import pickle | |
| # | |
| # file_path = '/scDifformer/data/240412_test/material/token_dictionary.pkl' | |
| # | |
| # with open(file_path, 'rb') as file: | |
| # data = pickle.load(file) | |
| # | |
| # print(data) | |
| from datasets import load_from_disk | |
| file_path = '/scDifformer/data/240412_test/output_directory_run/geneformer_run.dataset' | |
| ds = load_from_disk(file_path) | |
| print(ds[:3]) |