[{'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:fbins_min = data_32['egg-header']['minimum_frequency'][0]/1e6\nfbins_max = data_32['egg-header']['maximum_frequency'][0]/1e6\nfbins_w = 0.5 # in MHz\nebins_w = 0.005 # in keV\nt_range_margins = np.array([-0.05,0.2]); # this will be the same for both sets\nt_range = (run_params_32['pretrigger_time']*1e3)+t_range_margins # this will be the same for both sets\nfdata_32 = data_32['candidate_tracks']['StartFrequency']/1e6+fbins_min # MHz\nedata_32 = data_32['candidate_tracks']['TrackE_keV']\npdata_32 = data_32['candidate_tracks']['TotalPower']*1e9 # nW/Hz\nsdata_32 = data_32['candidate_tracks']['Slope']/1e9 # MHz/ms\nuid_data_32 = data_32['candidate_tracks']['UniqueEventID']\nmpt_total_data_32 = data_32['candidate_tracks']['MultiPeakTracks_Total']\norderf_data_32 = data_32['candidate_tracks']['MultiPeakTracks_OrderByFreq']\ncut_t_32 = (data_32['candidate_tracks']['StartTimeInAcq']*1e3>=t_range[0]) & (data_32['candidate_tracks']['StartTimeInAcq']*1e3<=t_range[1])\ncut_track_seq0_32 = (data_32['candidate_tracks']['EventSequenceID']==0)\ncut_base_32 = cut_track_seq0_32 & cut_t_32\ncut_nb_track_1_32 = (mpt_total_data_32==1)\ncut_nb_track_2_32 = (mpt_total_data_32==2)\ncut_nb_track_3_32 = (mpt_total_data_32==3)\ncut1_32 = cut_base_32 & cut_nb_track_1_32\ncut2_32 = cut_base_32 & cut_nb_track_2_32\ncut3_32 = cut_base_32 & cut_nb_track_3_32\nfdata1_32 = fdata_32[cut1_32]\nfdata2_32 = fdata_32[cut2_32]\nfdata3_32 = fdata_32[cut3_32]\nsdata1_32 = sdata_32[cut1_32]\nsdata2_32 = sdata_32[cut2_32]\nsdata3_32 = sdata_32[cut3_32]\npdata1_32 = pdata_32[cut1_32]\npdata2_32 = pdata_32[cut2_32]\npdata3_32 = pdata_32[cut3_32]\norderf_data1_32 = orderf_data_32[cut1_32]\norderf_data2_32 = orderf_data_32[cut2_32]\norderf_data3_32 = orderf_data_32[cut3_32]\nuid_data1_32 = uid_data_32[cut1_32]\nuid_data2_32 = uid_data_32[cut2_32]\nuid_data3_32 = uid_data_32[cut3_32]\nedata1_32 = edata_32[cut1_32]\nedata2_32 = edata_32[cut2_32]\nedata3_32 = edata_32[cut3_32]"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]