get step2 yaml from step3 result

dance/pipeline.py

@@ -940,3 +940,50 @@ def generate_subsets(path, tune_mode, save_directory, file_path, log_dir, requir
         config_dir = os.path.relpath(os.path.dirname(save_path), os.path.dirname(os.path.join(root_path, file_path)))
         command_str = command_str + f"python {file_path} --config_dir={config_dir}/subset_{index}_ --count={count} > {log_dir}/{index}.log 2>&1 &\n"
     return command_str, configs
+
+
+def get_step3_yaml(conf_save_path="examples/tuning/cta_svm/config_yamls/params/",
+                   conf_load_path="examples/tuning/cta_svm/cell_type_annotation_default_params.yaml",
+                   result_load_path="examples/tuning/cta_svm/results/pipeline/best_test_acc.csv",
+                   required_funs=["SetConfig"], required_indexes=[-1], root_path=None):
+    """Generate the configuration file of step 3 based on the results of step 2.
+
+    Parameters
+    ----------
+    conf_save_path
+        Storage directory of the configuration file generated in step 3
+    conf_load_path
+        Parameter search range of all preprocessing functions under a specific algorithm task
+    result_load_path
+        The storage path of the result of step 2
+    required_funs
+        Required functions in step 3
+    required_indexes
+        Location of required functions in step 3
+    root_path
+        root path of all paths
+
+    """
+    DANCEDIR = Path(__file__).resolve().parent.parent
+    root_path = DANCEDIR if root_path is None else root_path
+    conf_save_path = os.path.join(root_path, conf_save_path)
+    conf_load_path = os.path.join(root_path, conf_load_path)
+    result_load_path = os.path.join(root_path, result_load_path)
+    conf = OmegaConf.load(conf_load_path)
+    result = pd.read_csv(result_load_path)
+    columns = sorted([col for col in result.columns if col.startswith("pipeline")])
+    pipeline_names = result.loc[:, columns].values
+    count = 0
+    for row in pipeline_names:
+        pipeline = []
+        row = [i for i in row]
+        for i, f in zip(required_indexes, required_funs):
+            row.insert(i, f)
+        for x in row:
+            for k in conf.pipeline:
+                if k["target"] == x:
+                    pipeline.append(k)
+        temp_conf = conf.copy()
+        temp_conf.pipeline = pipeline
+        count += 1
+        OmegaConf.save(temp_conf, f"{conf_save_path}/{count}_test_acc_params_tuning_config.yaml")