From 6af95d2b122bc30b91ae5089c9e51678bec4c7f7 Mon Sep 17 00:00:00 2001 From: Mengqi <2534671415@qq.com> Date: Wed, 24 Jan 2024 18:22:04 +0800 Subject: [PATCH] perf: improve the selection of inference data for transform pipeline. --- geochemistrypi/data_mining/cli_pipeline.py | 25 +++++++++++----------- 1 file changed, 12 insertions(+), 13 deletions(-) diff --git a/geochemistrypi/data_mining/cli_pipeline.py b/geochemistrypi/data_mining/cli_pipeline.py index 66b3ad71..eda6de6d 100644 --- a/geochemistrypi/data_mining/cli_pipeline.py +++ b/geochemistrypi/data_mining/cli_pipeline.py @@ -201,22 +201,21 @@ def cli_pipeline(training_data_path: str, application_data_path: Optional[str] = # <--- Built-in Application Data Loading ---> logger.debug("Built-in Application Data Loading") # If the user doesn't provide training data path and inference data path, then use the built-in inference data. - if is_built_in_inference_data: - print("-*-*- Built-in Application Data Option-*-*-") - num2option(TEST_DATA_OPTION) - built_in_inference_data_num = limit_num_input(TEST_DATA_OPTION, SECTION[0], num_input) - if built_in_inference_data_num == 1: - application_data_path = "InferenceData_Regression.xlsx" - elif built_in_inference_data_num == 2: - application_data_path = "InferenceData_Classification.xlsx" - elif built_in_inference_data_num == 3: - application_data_path = "InferenceData_Clustering.xlsx" - elif built_in_inference_data_num == 4: - application_data_path = "InferenceData_Decomposition.xlsx" + if is_built_in_inference_data and built_in_training_data_num == 1: + application_data_path = "InferenceData_Regression.xlsx" inference_data = read_data(file_path=application_data_path) print(f"Successfully loading the built-in inference data set '{application_data_path}'.") show_data_columns(inference_data.columns) - clear_output() + elif is_built_in_inference_data and built_in_training_data_num == 2: + application_data_path = "InferenceData_Classification.xlsx" + inference_data = read_data(file_path=application_data_path) + print(f"Successfully loading the built-in inference data set '{application_data_path}'.") + show_data_columns(inference_data.columns) + elif is_built_in_inference_data and built_in_training_data_num == 3: + inference_data = None + elif is_built_in_inference_data and built_in_training_data_num == 4: + inference_data = None + clear_output() # <--- World Map Projection ---> logger.debug("World Map Projection")