[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:print('\\nLoading multi-run set')\nrun_collection_id = 6\nds_name = '32 keV, August 2015'\nds_str = '32keVaugust2015'\nfilterparams_dict = {'peak_e_keV': 32.0}\nrun_id_list = P8RunParamsDB.ListRunsInCollection(run_collection_id,filterparams_dict)\ndata_32 = KatydidHDF5IO.ConcatenateRunsDicts(run_id_list,'/Temp/project8/data/katydid_v2.6.7/')\nrun_id_list = data_32['egg-header_concat']['run_id_list_found']\nrun_params_32 = P8RunParamsDB.RunParams(run_id=run_id_list[0])\nprint('Done connecting to DB')\nP8RunParamsDB.AnalysisSpecificParams(run_params_32)\nprint('Done loading')\nb_master = 0.95842\nrun_params_32['b_avg_total_T'] = b_master\nana.Freq2EnergyData(data_32, run_params_32)\nprint('Done converting freq to energy')\nprint('...Writing MPT variables...')\nprint('\\tWill take a while, go outside and get some fresh air!')\nana.MultiPeakAnalysisAdditionalVars(data_32,run_params_32)\nprint('Done writing additional MPT variables')"}, {'role': 'assistant', 'content': "['load_data']"}]