File
File Management.
- the_utils.file.make_parent_dirs(target_path: PurePath) None [source]
make all the parent dirs of the target path.
- Parameters:
target_path (PurePath) – target path.
- the_utils.file.refresh_file(target_path: str | None = None) None [source]
clear target path
- Parameters:
target_path (str) – file path
- the_utils.file.csv2file(target_path: str, thead: List[str] | None = None, tbody: List[Any] | None = None, refresh: bool = False, is_dict_list: bool = False, sort_head: bool = False) None [source]
save data to target_path of a csv file.
- Parameters:
target_path (str) – target path
thead (List[str], optional) – csv table header, only written into the file when it is not None and file is empty. Defaults to None.
tbody (List, optional) – csv table content. Defaults to None.
refresh (bool, optional) – whether to clean the file first. Defaults to False.
is_dict_list (bool, optional) – whether the tbody is in the format of a list of dicts. Defaults to False.
sort_head (bool, optional) – whether to sort the head with lowercase before writing. Defaults to False.
Example
from the_utils import csv2file save_file = "./results/example.csv" final_params = { "dataset": "cora", "acc": "99.1", "NMI": "89.0", } thead=[] # list of values csv2file( target_path=save_file, thead=list(final_params.keys()), tbody=list(final_params.values()), refresh=False, is_dict_list=False, ) # list of dicts csv2file( target_path=save_file, tbody=[ { "a": 1, "b": 2 }, { "a": 2, "b": 1 }, ], is_dict_list=True, )
- the_utils.file.save_to_csv_files(results: dict, add_info: dict, csv_name: str, save_path='./results', sort_head: bool = False) None [source]
Save the evaluation results to a local csv file.
- Parameters:
results (dict) – Evaluation results document.
add_info (dict) – Additional information, such as data set name, method name.
csv_name (str) – csv file name to store.
save_path (str, optional) – Folder path to store. Defaults to ‘./results’.
sort_head (bool, optional) – whether to sort the head before writing. Defaults to False.
Example
from the_utils import evaluate_from_embed_file from the_utils import save_to_csv_files method_name='orderedgnn' data_name='texas' clustering_res, classification_res = evaluate_from_embed_file( f'{data_name}_{method_name}_embeds.pth', f'{data_name}_data.pth', save_path='./save/', ) add_info = {'data': data_name, 'method': method_name,} save_to_csv_files(clustering_res, add_info, 'clutering.csv') save_to_csv_files(classification_res, add_info, 'classification.csv')