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| import json | |
| import os | |
| import warnings | |
| from tag.utils.io_helpers import sort_files | |
| from tqdm import tqdm | |
| from utils.param_keys import INPUT_NAME, FILENAME, FOLDER_PATH, PARAMS | |
| def get_model_params_list(alg_json_file: str) :#-> list[dict]: | |
| """ | |
| Loads the list of model configurations given from a json file or the default list of dictionary from the code. | |
| @param alg_json_file: str | |
| Path to the json data with the running configuration | |
| @return: list[dict] | |
| list of model configurations | |
| """ | |
| if alg_json_file is not None: | |
| return json.load(open(alg_json_file)) | |
| else: | |
| warnings.warn('The default model parameter list is used instead of a .json-file.\n' | |
| ' Use a configuration from the `config_files`-folder together with the args `-a`.') | |
| return [ | |
| {ALGORITHM_NAME: 'pca', NDIM: TENSOR_NDIM}, | |
| ] | |
| def get_run_params(alg_params_json: str) -> dict: | |
| """ | |
| Loads the running configuration given from a json file or the default dictionary from the code. | |
| @param alg_params_json: str | |
| Path to the json data with the running configuration | |
| @return: dict | |
| Running Configuration | |
| """ | |
| if alg_params_json is not None: | |
| return json.load(open(alg_params_json)) | |
| else: | |
| warnings.warn('The default run option is used instead of a .json-file.\n' | |
| ' Use a configuration from the `config_files`-folder together with the args `-o`.') | |
| return { | |
| RUN_OPTION: COMPARE, | |
| PLOT_TYPE: COLOR_MAP, # 'heat_map', 'color_map', '3d_map', 'explained_var_plot' | |
| PLOT_TICS: True, | |
| N_COMPONENTS: 2, | |
| INPUT_NAME: 'runningExample', | |
| SAVE_RESULTS: True, | |
| LOAD_RESULTS: True | |
| } | |
| def get_files_and_kwargs(params: dict): | |
| """ | |
| This method returns the filename list of the trajectory and generates the kwargs for the DataTrajectory. | |
| The method is individually created for the available data set. | |
| Add new trajectory options, if different data set are used. | |
| @param params: dict | |
| running configuration | |
| @return: tuple | |
| list of filenames of the trajectories AND | |
| kwargs with the important arguments for the classes | |
| """ | |
| try: | |
| input_name = params[INPUT_NAME] | |
| except KeyError as e: | |
| raise KeyError(f'Run option parameter is missing the key: `{e}`. This parameter is mandatory.') | |
| #TODO: generate parent directories if they don't exist | |
| if input_name == 'test': | |
| filename_list = list(tqdm(sort_files(os.listdir('data/test_2')))) | |
| kwargs = {FILENAME: filename_list, FOLDER_PATH: 'data/test_2'} | |
| elif input_name == 'realLogs': | |
| filename_list = list(tqdm(sort_files(os.listdir('data/real_event_logs')))) | |
| kwargs = {FILENAME: filename_list, FOLDER_PATH: 'data/real_event_logs'} | |
| elif input_name == 'gen5': | |
| filename_list = list(tqdm(sort_files(os.listdir('data/event_log'))))[:5] | |
| kwargs = {FILENAME: filename_list, FOLDER_PATH: 'data/event_log'} | |
| elif input_name == 'gen20': | |
| filename_list = list(tqdm(sort_files(os.listdir('data/event_log'))))[:20] | |
| kwargs = {FILENAME: filename_list, FOLDER_PATH: 'data/event_log'} | |
| elif input_name == 'runningExample': | |
| filename_list = ['running-example.xes'] | |
| kwargs = {FILENAME: filename_list[0], FOLDER_PATH: 'data/'} | |
| elif input_name == 'metaFeatures': | |
| filename_list = ['log_features.csv'] | |
| kwargs = {FILENAME: filename_list[0], FOLDER_PATH: 'results/'} | |
| else: | |
| raise ValueError(f'No data trajectory was found with the name `{input_name}`.') | |
| #filename_list.pop(file_element) | |
| kwargs[PARAMS] = params | |
| return filename_list, kwargs | |