diff --git a/src/g5505_file_reader.py b/src/g5505_file_reader.py index 58b98d2..136d6a9 100644 --- a/src/g5505_file_reader.py +++ b/src/g5505_file_reader.py @@ -181,14 +181,14 @@ def read_txt_files_as_dict(filename : str ): dataset['dtype'] = type(dataset['data']) file_dict['datasets'].append(dataset) - if 'timestamps' in categorical_variables: - dataset = {} - dataset['name'] = 'timestamps' - dataset['data'] = df_categorical_attrs['timestamps'].to_numpy().reshape((rows,1)) - dataset['shape'] = dataset['data'].shape - dataset['dtype'] = type(dataset['data']) - file_dict['datasets'].append(dataset) - categorical_variables.remove('timestamps') + #if 'timestamps' in categorical_variables: + # dataset = {} + # dataset['name'] = 'timestamps' + # dataset['data'] = df_categorical_attrs['timestamps'].to_numpy().reshape((rows,1)) + # dataset['shape'] = dataset['data'].shape + # dataset['dtype'] = type(dataset['data']) + # file_dict['datasets'].append(dataset) + # categorical_variables.remove('timestamps') if categorical_variables: dataset = {} diff --git a/src/g5505_utils.py b/src/g5505_utils.py index a204df6..b126046 100644 --- a/src/g5505_utils.py +++ b/src/g5505_utils.py @@ -50,7 +50,7 @@ def split_sample_col_into_sample_and_data_quality_cols(input_data: pd.DataFrame) return input_data -def make_file_copy(source_file_path): +def make_file_copy(source_file_path, output_folder_name : str = 'tmp_files'): pathtail, filename = os.path.split(source_file_path) #backup_filename = 'backup_'+ filename @@ -58,7 +58,7 @@ def make_file_copy(source_file_path): # Path ROOT_DIR = os.path.abspath(os.curdir) - tmp_dirpath = os.path.join(ROOT_DIR,'tmp_files') + tmp_dirpath = os.path.join(ROOT_DIR,output_folder_name) if not os.path.exists(tmp_dirpath): os.mkdir(tmp_dirpath) diff --git a/src/smog_chamber_file_reader.py b/src/smog_chamber_file_reader.py index ef31c92..083721c 100644 --- a/src/smog_chamber_file_reader.py +++ b/src/smog_chamber_file_reader.py @@ -103,17 +103,15 @@ def read_txt_files_as_dict(filename : str ): dataset['shape'] = dataset['data'].shape dataset['dtype'] = type(dataset['data']) file_dict['datasets'].append(dataset) - - - if 'timestamps' in categorical_variables: - dataset = {} - dataset['name'] = 'timestamps' - dataset['data'] = df_categorical_attrs['timestamps'].to_numpy().reshape((rows,1)) - dataset['shape'] = dataset['data'].shape - dataset['dtype'] = type(dataset['data']) - file_dict['datasets'].append(dataset) - categorical_variables.remove('timestamps') + #if 'timestamps' in categorical_variables: + # dataset = {} + # dataset['name'] = 'timestamps' + # dataset['data'] = df_categorical_attrs['timestamps'].to_numpy().reshape((rows,1)) + # dataset['shape'] = dataset['data'].shape + # dataset['dtype'] = type(dataset['data']) + # file_dict['datasets'].append(dataset) + # categorical_variables.remove('timestamps') if categorical_variables: dataset = {}