diff --git "a/notebooks/benchmarking_process_discovery.ipynb" "b/notebooks/benchmarking_process_discovery.ipynb" deleted file mode 100644--- "a/notebooks/benchmarking_process_discovery.ipynb" +++ /dev/null @@ -1,1438 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 102, - "id": "b7408494", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "from scipy import spatial\n", - "from sklearn.metrics.pairwise import cosine_similarity\n", - "TEST='kendalltau'\n", - "DATA_SOURCE = 'Real'\n", - "EXP_BASELINE = False\n", - "IMPUTE = False #If False Nan lines are dropped" - ] - }, - { - "cell_type": "code", - "execution_count": 103, - "id": "ee0f1487", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Real\n", - "kendalltau_BaselineED_nanDropped\n" - ] - } - ], - "source": [ - "def get_output_file_name(test, data_source, exp_baseline, impute): \n", - " print(data_source)\n", - " if data_source=='Real':\n", - " data_source = 'BaselineED'\n", - " else:\n", - " if EXP_BASELINE:\n", - " data_source = 'GenBaselineED'\n", - " else:\n", - " data_source = 'GenED'\n", - " impute = 'imputed' if impute else 'nanDropped'\n", - " return (\"_\".join([test, data_source, impute]))\n", - "print(get_output_file_name(TEST, DATA_SOURCE, EXP_BASELINE, IMPUTE))" - ] - }, - { - "cell_type": "code", - "execution_count": 104, - "id": "4ff27cb8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(467, 8) (26, 8)\n", - "(493, 9)\n", - "['BPIC12' 'BPIC13cp' 'BPIC13inc' 'BPIC13op' 'BPIC14dc_p' 'BPIC14di_p'\n", - " 'BPIC14dia_p' 'BPIC15f1' 'BPIC15f2' 'BPIC15f3' 'BPIC15f4' 'BPIC15f5'\n", - " 'BPIC16c_p' 'BPIC16wm_p' 'BPIC17' 'BPIC17ol' 'BPIC19' 'BPIC20a' 'BPIC20b'\n", - " 'BPIC20c' 'BPIC20d' 'BPIC20e' 'HD' 'RTFMP' 'RWABOCSL' 'SEPSIS'\n", - " '2_rmcv_rt10v_genELtask_40_03_06' '2_enself_rutpt_genELtask_25_02_02'\n", - " '2_rt10v_rutpt_genELtask_39_03_05' '2_ense_rt10v_genELtask_32_02_09'\n", - " '2_enseef_rt10v_genELtask_41_03_07' '2_enseef_rt10v_genELtask_18_01_06'\n", - " '2_ense_rt10v_genELtask_40_03_06' '2_enve_rt10v_genELtask_45_04_00'\n", - " '2_ense_rt10v_genELtask_21_01_09' '2_enself_rt10v_genELtask_10_00_09'\n", - " '2_enseef_rt10v_genELtask_20_01_08' '2_enself_enve_genELtask_42_03_08'\n", - " '2_enself_rmcv_genELtask_36_03_02' '2_ense_enseef_genELtask_60_05_04'\n", - " '2_enseef_rmcv_genELtask_6_00_05' '2_enself_rutpt_genELtask_5_00_04'\n", - " '2_enve_rt10v_genELtask_69_06_02' '2_enve_rutpt_genELtask_53_04_08'\n", - " '2_enself_rt10v_genELtask_22_01_10' '2_enseef_enve_genELtask_63_05_07'\n", - " '2_enseef_rutpt_genELtask_26_02_03' '2_enself_rutpt_genELtask_20_01_08'\n", - " '2_enseef_rt10v_genELtask_30_02_07' '2_enseef_enself_genELtask_60_05_04'\n", - " '2_enve_rmcv_genELtask_48_04_03' '2_enve_rutpt_genELtask_74_06_07'\n", - " '2_ense_rt10v_genELtask_45_04_00' '2_rmcv_rutpt_genELtask_56_05_00'\n", - " '2_enself_rt10v_genELtask_20_01_08' '2_ense_enself_genELtask_82_07_04'\n", - " '2_ense_enself_genELtask_70_06_03' '2_ense_enseef_genELtask_24_02_01'\n", - " '2_enself_enve_genELtask_17_01_05' '2_enve_rmcv_genELtask_69_06_02'\n", - " '2_ense_rutpt_genELtask_72_06_05' '2_ense_enve_genELtask_65_05_09'\n", - " '2_ense_enseef_genELtask_82_07_04' '2_rmcv_rt10v_genELtask_14_01_02'\n", - " '2_ense_rt10v_genELtask_53_04_08' '2_enseef_rutpt_genELtask_25_02_02'\n", - " '2_enseef_rt10v_genELtask_57_05_01' '2_rt10v_rutpt_genELtask_82_07_04'\n", - " '2_rt10v_rutpt_genELtask_27_02_04' '2_enve_rt10v_genELtask_47_04_02'\n", - " '2_enself_rutpt_genELtask_22_01_10' '2_ense_enve_genELtask_2_00_01'\n", - " '2_enseef_rutpt_genELtask_14_01_02' '2_enve_rutpt_genELtask_64_05_08'\n", - " '2_enve_rt10v_genELtask_77_06_10' '2_enve_rmcv_genELtask_49_04_04'\n", - " '2_enseef_enve_genELtask_3_00_02' '2_enseef_enself_genELtask_13_01_01'\n", - " '2_enve_rmcv_genELtask_6_00_05' '2_enve_rt10v_genELtask_96_08_07'\n", - " '2_ense_enseef_genELtask_58_05_02' '2_enself_rutpt_genELtask_19_01_07'\n", - " '2_enseef_enself_genELtask_2_00_01' '2_enself_rt10v_genELtask_31_02_08'\n", - " '2_ense_enve_genELtask_75_06_08' '2_enve_rmcv_genELtask_47_04_02'\n", - " '2_enseef_rt10v_genELtask_42_03_08' '2_enseef_rmcv_genELtask_56_05_00'\n", - " '2_enve_rutpt_genELtask_79_07_01' '2_enseef_enve_genELtask_28_02_05'\n", - " '2_ense_enself_genELtask_2_00_01' '2_ense_enself_genELtask_46_04_01'\n", - " '2_ense_rmcv_genELtask_59_05_03' '2_enseef_rutpt_genELtask_38_03_04'\n", - " '2_ense_enseef_genELtask_71_06_04' '2_enseef_rutpt_genELtask_16_01_04'\n", - " '2_enve_rt10v_genELtask_17_01_05' '2_enve_rmcv_genELtask_68_06_01'\n", - " '2_enseef_rmcv_genELtask_15_01_03' '2_enseef_rutpt_genELtask_40_03_06'\n", - " '2_ense_rt10v_genELtask_71_06_04' '2_rt10v_rutpt_genELtask_51_04_06'\n", - " '2_enseef_rmcv_genELtask_7_00_06' '2_ense_enve_genELtask_27_02_04'\n", - " '2_enseef_rmcv_genELtask_26_02_03' '2_enseef_enve_genELtask_42_03_08'\n", - " '2_enseef_rt10v_genELtask_22_01_10' '2_enve_rutpt_genELtask_3_00_02'\n", - " '2_ense_rutpt_genELtask_48_04_03' '2_enseef_rmcv_genELtask_24_02_01'\n", - " '2_rmcv_rt10v_genELtask_43_03_09' '2_ense_enve_genELtask_17_01_05'\n", - " '2_enve_rmcv_genELtask_57_05_01' '2_ense_enve_genELtask_41_03_07'\n", - " '2_ense_enve_genELtask_31_02_08' '2_enve_rutpt_genELtask_88_07_10'\n", - " '2_enseef_rt10v_genELtask_19_01_07' '2_rmcv_rutpt_genELtask_27_02_04'\n", - " '2_rmcv_rutpt_genELtask_38_03_04' '2_ense_enself_genELtask_58_05_02'\n", - " '2_ense_enve_genELtask_74_06_07' '2_enself_enve_genELtask_19_01_07'\n", - " '2_ense_rutpt_genELtask_49_04_04' '2_ense_rt10v_genELtask_55_04_10'\n", - " '2_enve_rmcv_genELtask_35_03_01' '2_enve_rutpt_genELtask_77_06_10'\n", - " '2_ense_rt10v_genELtask_49_04_04' '2_ense_enve_genELtask_37_03_03'\n", - " '2_enve_rutpt_genELtask_92_08_03' '2_rt10v_rutpt_genELtask_72_06_05'\n", - " '2_ense_rt10v_genELtask_22_01_10' '2_enseef_rt10v_genELtask_12_01_00'\n", - " '2_ense_enve_genELtask_14_01_02' '2_enseef_enve_genELtask_30_02_07'\n", - " '2_enself_rt10v_genELtask_4_00_03' '2_ense_rt10v_genELtask_60_05_04'\n", - " '2_enve_rt10v_genELtask_6_00_05' '2_rt10v_rutpt_genELtask_1_00_00'\n", - " '2_ense_rmcv_genELtask_67_06_00' '2_enve_rmcv_genELtask_80_07_02'\n", - " '2_enself_rmcv_genELtask_2_00_01' '2_ense_rt10v_genELtask_72_06_05'\n", - " '2_enve_rt10v_genELtask_73_06_06' '2_rt10v_rutpt_genELtask_32_02_09'\n", - " '2_ense_rt10v_genELtask_62_05_06' '2_enseef_rt10v_genELtask_17_01_05'\n", - " '2_ense_rt10v_genELtask_70_06_03' '2_enself_rt10v_genELtask_18_01_06'\n", - " '2_ense_rutpt_genELtask_1_00_00' '2_rt10v_rutpt_genELtask_71_06_04'\n", - " '2_rmcv_rutpt_genELtask_13_01_01' '2_enve_rutpt_genELtask_61_05_05'\n", - " '2_rt10v_rutpt_genELtask_22_01_10' '2_enseef_enself_genELtask_1_00_00'\n", - " '2_ense_enve_genELtask_76_06_09' '2_enseef_enve_genELtask_52_04_07'\n", - " '2_rmcv_rt10v_genELtask_19_01_07' '2_enve_rt10v_genELtask_108_09_08'\n", - " '2_enself_rutpt_genELtask_44_03_10' '2_enself_rt10v_genELtask_40_03_06'\n", - " '2_ense_rt10v_genELtask_31_02_08' '2_rt10v_rutpt_genELtask_30_02_07'\n", - " '2_enself_enve_genELtask_7_00_06' '2_rmcv_rutpt_genELtask_20_01_08'\n", - " '2_enve_rt10v_genELtask_90_08_01' '2_enself_enve_genELtask_2_00_01'\n", - " '2_enve_rt10v_genELtask_57_05_01' '2_ense_rmcv_genELtask_48_04_03'\n", - " '2_enve_rutpt_genELtask_62_05_06' '2_ense_rt10v_genELtask_52_04_07'\n", - " '2_ense_rt10v_genELtask_69_06_02' '2_enseef_enve_genELtask_43_03_09'\n", - " '2_enself_rt10v_genELtask_36_03_02' '2_ense_rutpt_genELtask_13_01_01'\n", - " '2_rmcv_rt10v_genELtask_17_01_05' '2_ense_rmcv_genELtask_25_02_02'\n", - " '2_enseef_rmcv_genELtask_13_01_01' '2_rt10v_rutpt_genELtask_21_01_09'\n", - " '2_ense_rutpt_genELtask_46_04_01' '2_ense_enseef_genELtask_59_05_03'\n", - " '2_enve_rt10v_genELtask_74_06_07' '2_enseef_rutpt_genELtask_54_04_09'\n", - " '2_enve_rt10v_genELtask_76_06_09' '2_enve_rutpt_genELtask_68_06_01'\n", - " '2_ense_rutpt_genELtask_73_06_06' '2_rmcv_rt10v_genELtask_48_04_03'\n", - " '2_enseef_enself_genELtask_37_03_03' '2_ense_rutpt_genELtask_75_06_08'\n", - " '2_enve_rutpt_genELtask_83_07_05' '2_ense_rt10v_genELtask_64_05_08'\n", - " '2_ense_rmcv_genELtask_16_01_04' '2_enself_rutpt_genELtask_13_01_01'\n", - " '2_enself_rutpt_genELtask_3_00_02' '2_enself_rmcv_genELtask_15_01_03'\n", - " '2_ense_rutpt_genELtask_74_06_07' '2_enve_rutpt_genELtask_93_08_04'\n", - " '2_ense_rt10v_genELtask_42_03_08' '2_enseef_enve_genELtask_64_05_08'\n", - " '2_ense_enve_genELtask_63_05_07' '2_ense_rt10v_genELtask_47_04_02'\n", - " '2_enve_rutpt_genELtask_102_09_02' '2_enself_rt10v_genELtask_46_04_01'\n", - " '2_enseef_rutpt_genELtask_55_04_10' '2_enve_rmcv_genELtask_70_06_03'\n", - " '2_enself_rmcv_genELtask_7_00_06' '2_enself_enve_genELtask_54_04_09'\n", - " '2_enve_rutpt_genELtask_65_05_09' '2_enseef_rt10v_genELtask_27_02_04'\n", - " '2_enself_rt10v_genELtask_21_01_09' '2_ense_rutpt_genELtask_33_02_10'\n", - " '2_ense_rt10v_genELtask_68_06_01' '2_enself_rt10v_genELtask_14_01_02'\n", - " '2_enseef_rutpt_genELtask_12_01_00' '2_ense_rmcv_genELtask_6_00_05'\n", - " '2_ense_rutpt_genELtask_12_01_00' '2_enve_rmcv_genELtask_7_00_06'\n", - " '2_ense_rt10v_genELtask_63_05_07' '2_enseef_rutpt_genELtask_53_04_08'\n", - " '2_ense_rutpt_genELtask_65_05_09' '2_enself_rmcv_genELtask_6_00_05'\n", - " '2_ense_rutpt_genELtask_58_05_02' '2_ense_enve_genELtask_50_04_05'\n", - " '2_enve_rmcv_genELtask_89_08_00' '2_ense_enself_genELtask_67_06_00'\n", - " '2_ense_rt10v_genELtask_12_01_00' '2_ense_rt10v_genELtask_74_06_07'\n", - " '2_enself_enve_genELtask_43_03_09' '2_ense_rutpt_genELtask_62_05_06'\n", - " '2_ense_enseef_genELtask_47_04_02' '2_enself_enve_genELtask_53_04_08'\n", - " '2_enseef_rt10v_genELtask_35_03_01' '2_rt10v_rutpt_genELtask_41_03_07'\n", - " '2_ense_rt10v_genELtask_43_03_09' '2_enseef_rutpt_genELtask_1_00_00'\n", - " '2_ense_rmcv_genELtask_7_00_06' '2_rt10v_rutpt_genELtask_62_05_06'\n", - " '2_ense_enve_genELtask_61_05_05' '2_enself_rt10v_genELtask_35_03_01'\n", - " '2_rt10v_rutpt_genELtask_91_08_02' '2_enself_rmcv_genELtask_17_01_05'\n", - " '2_enve_rutpt_genELtask_46_04_01' '2_enseef_enve_genELtask_54_04_09'\n", - " '2_ense_rutpt_genELtask_54_04_09' '2_enseef_enve_genELtask_32_02_09'\n", - " '2_enve_rutpt_genELtask_44_03_10' '2_enself_rmcv_genELtask_14_01_02'\n", - " '2_rmcv_rt10v_genELtask_27_02_04' '2_rmcv_rutpt_genELtask_25_02_02'\n", - " '2_enself_enve_genELtask_9_00_08' '2_rmcv_rt10v_genELtask_37_03_03'\n", - " '2_rmcv_rt10v_genELtask_34_03_00' '2_rmcv_rutpt_genELtask_39_03_05'\n", - " '2_ense_enself_genELtask_24_02_01' '2_enseef_rutpt_genELtask_66_05_10'\n", - " '2_ense_rt10v_genELtask_33_02_10' '2_enve_rutpt_genELtask_70_06_03'\n", - " '2_ense_rmcv_genELtask_37_03_03' '2_ense_rutpt_genELtask_25_02_02'\n", - " '2_ense_rutpt_genELtask_26_02_03' '2_enseef_enve_genELtask_29_02_06'\n", - " '2_enseef_rt10v_genELtask_6_00_05' '2_ense_rt10v_genELtask_36_03_02'\n", - " '2_ense_rt10v_genELtask_23_02_00' '2_rmcv_rt10v_genELtask_12_01_00'\n", - " '2_enve_rt10v_genELtask_109_09_09' '2_enve_rt10v_genELtask_80_07_02'\n", - " '2_enve_rutpt_genELtask_48_04_03' '2_enve_rt10v_genELtask_64_05_08'\n", - " '2_rt10v_rutpt_genELtask_49_04_04' '2_enself_rmcv_genELtask_24_02_01'\n", - " '2_ense_enself_genELtask_47_04_02' '2_enseef_rutpt_genELtask_2_00_01'\n", - " '2_enseef_rt10v_genELtask_21_01_09' '2_enve_rutpt_genELtask_40_03_06'\n", - " '2_ense_rt10v_genELtask_57_05_01' '2_ense_enseef_genELtask_1_00_00'\n", - " '2_ense_rutpt_genELtask_35_03_01' '2_ense_rutpt_genELtask_53_04_08'\n", - " '2_enve_rmcv_genELtask_90_08_01' '2_rmcv_rt10v_genELtask_29_02_06'\n", - " '2_enseef_enve_genELtask_31_02_08' '2_ense_enve_genELtask_42_03_08'\n", - " '2_ense_enve_genELtask_73_06_06' '2_ense_enve_genELtask_43_03_09'\n", - " '2_rt10v_rutpt_genELtask_42_03_08' '2_rmcv_rutpt_genELtask_40_03_06'\n", - " '2_ense_rutpt_genELtask_60_05_04' '2_rmcv_rt10v_genELtask_54_04_09'\n", - " '2_ense_enve_genELtask_52_04_07' '2_rmcv_rt10v_genELtask_39_03_05'\n", - " '2_rt10v_rutpt_genELtask_81_07_03' '2_enve_rmcv_genELtask_100_09_00'\n", - " '2_rmcv_rutpt_genELtask_45_04_00' '2_ense_rutpt_genELtask_64_05_08'\n", - " '2_ense_enve_genELtask_38_03_04' '2_rmcv_rt10v_genELtask_55_04_10'\n", - " '2_enve_rutpt_genELtask_55_04_10' '2_enve_rt10v_genELtask_86_07_08'\n", - " '2_ense_enseef_genELtask_36_03_02' '2_ense_enve_genELtask_29_02_06'\n", - " '2_ense_enve_genELtask_86_07_08' '2_ense_rutpt_genELtask_88_07_10'\n", - " '2_ense_enseef_genELtask_83_07_05' '2_ense_enseef_genELtask_25_02_02'\n", - " '2_rmcv_rt10v_genELtask_38_03_04' '2_ense_rutpt_genELtask_59_05_03'\n", - " '2_enve_rutpt_genELtask_81_07_03' '2_enve_rutpt_genELtask_60_05_04'\n", - " '2_enve_rt10v_genELtask_60_05_04' '2_rmcv_rutpt_genELtask_11_00_10'\n", - " '2_rmcv_rutpt_genELtask_26_02_03' '2_enseef_rmcv_genELtask_25_02_02'\n", - " '2_enself_rt10v_genELtask_7_00_06' '2_rmcv_rt10v_genELtask_2_00_01'\n", - " '2_enseef_rmcv_genELtask_37_03_03' '2_ense_rt10v_genELtask_6_00_05'\n", - " '2_enve_rutpt_genELtask_71_06_04' '2_rmcv_rutpt_genELtask_14_01_02'\n", - " '2_ense_enself_genELtask_78_07_00' '2_enve_rmcv_genELtask_40_03_06'\n", - " '2_rmcv_rt10v_genELtask_20_01_08' '2_ense_rmcv_genELtask_46_04_01'\n", - " '2_ense_rmcv_genELtask_18_01_06' '2_enseef_rutpt_genELtask_33_02_10'\n", - " '2_ense_enseef_genELtask_70_06_03' '2_enve_rmcv_genELtask_37_03_03'\n", - " '2_enseef_enself_genELtask_48_04_03' '2_rt10v_rutpt_genELtask_102_09_02'\n", - " '2_ense_rutpt_genELtask_77_06_10' '2_enself_rutpt_genELtask_4_00_03'\n", - " '2_ense_rutpt_genELtask_39_03_05' '2_enseef_enve_genELtask_21_01_09'\n", - " '2_rt10v_rutpt_genELtask_38_03_04' '2_ense_enve_genELtask_30_02_07'\n", - " '2_enve_rutpt_genELtask_99_08_10' '2_ense_enve_genELtask_40_03_06'\n", - " '2_enself_enve_genELtask_6_00_05' '2_enself_rutpt_genELtask_2_00_01'\n", - " '2_enself_enve_genELtask_1_00_00' '2_enve_rmcv_genELtask_104_09_04'\n", - " '2_enve_rutpt_genELtask_86_07_08' '2_rt10v_rutpt_genELtask_101_09_01'\n", - " '2_enve_rt10v_genELtask_91_08_02' '2_ense_enself_genELtask_81_07_03'\n", - " '2_ense_rutpt_genELtask_51_04_06' '2_enve_rt10v_genELtask_75_06_08'\n", - " '2_enself_rmcv_genELtask_34_03_00' '2_enseef_rt10v_genELtask_23_02_00'\n", - " '2_enseef_enve_genELtask_17_01_05' '2_ense_rutpt_genELtask_43_03_09'\n", - " '2_ense_enseef_genELtask_48_04_03' '2_enve_rt10v_genELtask_46_04_01'\n", - " '2_enve_rmcv_genELtask_92_08_03' '2_ense_enve_genELtask_1_00_00'\n", - " '2_ense_rutpt_genELtask_66_05_10' '2_enseef_enve_genELtask_16_01_04'\n", - " '2_enve_rmcv_genELtask_58_05_02' '2_rt10v_rutpt_genELtask_90_08_01'\n", - " '2_enself_enve_genELtask_29_02_06' '2_enve_rmcv_genELtask_79_07_01'\n", - " '2_ense_rutpt_genELtask_52_04_07' '2_rt10v_rutpt_genELtask_79_07_01'\n", - " '2_ense_rutpt_genELtask_87_07_09' '2_ense_rutpt_genELtask_55_04_10'\n", - " '2_enve_rutpt_genELtask_38_03_04' '2_enself_enve_genELtask_31_02_08'\n", - " '2_enself_rutpt_genELtask_55_04_10' '2_rmcv_rutpt_genELtask_35_03_01'\n", - " '2_enseef_rt10v_genELtask_46_04_01' '2_enve_rutpt_genELtask_57_05_01'\n", - " '2_rmcv_rutpt_genELtask_57_05_01' '2_enve_rt10v_genELtask_71_06_04'\n", - " '2_ense_enself_genELtask_68_06_01' '2_ense_rt10v_genELtask_58_05_02'\n", - " '2_enve_rt10v_genELtask_95_08_06' '2_enseef_rt10v_genELtask_47_04_02'\n", - " '2_ense_rt10v_genELtask_79_07_01' '2_ense_rt10v_genELtask_50_04_05'\n", - " '2_ense_rutpt_genELtask_71_06_04' '2_ense_enself_genELtask_36_03_02'\n", - " '2_enseef_enself_genELtask_59_05_03' '2_enseef_enve_genELtask_2_00_01'\n", - " '2_ense_rmcv_genELtask_57_05_01' '2_enself_rutpt_genELtask_21_01_09'\n", - " '2_enself_rutpt_genELtask_1_00_00' '2_enseef_rutpt_genELtask_44_03_10'\n", - " '2_enseef_enself_genELtask_36_03_02' '2_enve_rt10v_genELtask_97_08_08'\n", - " '2_ense_rmcv_genELtask_78_07_00' '2_ense_enseef_genELtask_69_06_02'\n", - " '2_rt10v_rutpt_genELtask_68_06_01' '2_ense_enve_genELtask_62_05_06'\n", - " '2_ense_enseef_genELtask_13_01_01' '2_ense_enseef_genELtask_35_03_01'\n", - " '2_enself_enve_genELtask_3_00_02' '2_ense_rmcv_genELtask_58_05_02'\n", - " '2_enve_rmcv_genELtask_78_07_00' '2_ense_enve_genELtask_13_01_01'\n", - " '2_enve_rt10v_genELtask_82_07_04' '2_ense_enve_genELtask_48_04_03'\n", - " '2_enself_rmcv_genELtask_3_00_02' '2_rt10v_rutpt_genELtask_52_04_07'\n", - " '2_rt10v_rutpt_genELtask_61_05_05' '2_enseef_enself_genELtask_49_04_04'\n", - " '2_enseef_enve_genELtask_1_00_00' '2_enve_rt10v_genELtask_87_07_09'\n", - " '2_enself_rt10v_genELtask_5_00_04' '2_enself_rutpt_genELtask_15_01_03'\n", - " '2_ense_rt10v_genELtask_61_05_05' '2_ense_rutpt_genELtask_47_04_02'\n", - " '2_enve_rt10v_genELtask_84_07_06' '2_enve_rutpt_genELtask_91_08_02'\n", - " '2_enve_rt10v_genELtask_85_07_07' '2_enseef_enself_genELtask_24_02_01'\n", - " '2_enve_rutpt_genELtask_66_05_10' '2_enve_rt10v_genELtask_56_05_00'\n", - " '2_enseef_rutpt_genELtask_13_01_01' '2_enseef_rt10v_genELtask_29_02_06'\n", - " '2_enve_rt10v_genELtask_26_02_03' '2_ense_rutpt_genELtask_24_02_01'\n", - " '2_enve_rutpt_genELtask_1_00_00' '2_enve_rutpt_genELtask_82_07_04'\n", - " '2_enve_rt10v_genELtask_102_09_02' '2_enself_rutpt_genELtask_42_03_08'\n", - " '2_ense_rmcv_genELtask_15_01_03' '2_ense_enve_genELtask_18_01_06'\n", - " '2_enve_rmcv_genELtask_81_07_03' '2_enve_rt10v_genELtask_83_07_05'\n", - " '2_ense_enve_genELtask_53_04_08' '2_enseef_rmcv_genELtask_45_04_00'\n", - " '2_enseef_rutpt_genELtask_27_02_04' '2_enve_rt10v_genELtask_48_04_03'\n", - " '2_enve_rutpt_genELtask_76_06_09' '2_ense_rutpt_genELtask_63_05_07'\n", - " '2_ense_rmcv_genELtask_17_01_05' '2_rt10v_rutpt_genELtask_34_03_00'\n", - " '2_ense_enve_genELtask_16_01_04' '2_ense_enve_genELtask_51_04_06'\n", - " '2_enve_rutpt_genELtask_104_09_04' '2_enseef_rmcv_genELtask_14_01_02'\n", - " '2_enseef_rutpt_genELtask_36_03_02' '2_enself_rmcv_genELtask_45_04_00'\n", - " '2_rmcv_rt10v_genELtask_15_01_03' '2_ense_rmcv_genELtask_35_03_01'\n", - " '2_enseef_enve_genELtask_27_02_04' '2_ense_enve_genELtask_3_00_02'\n", - " '2_ense_rmcv_genELtask_47_04_02' '2_enseef_rutpt_genELtask_15_01_03'\n", - " '2_ense_enself_genELtask_25_02_02' '2_enseef_rt10v_genELtask_43_03_09'\n", - " '2_enseef_enve_genELtask_18_01_06' '2_enve_rutpt_genELtask_90_08_01'\n", - " '2_ense_rt10v_genELtask_41_03_07' '2_ense_enve_genELtask_85_07_07'\n", - " '2_enve_rutpt_genELtask_63_05_07' '2_enself_rutpt_genELtask_6_00_05'\n", - " '2_enseef_rutpt_genELtask_30_02_07' '2_enseef_rmcv_genELtask_36_03_02'\n", - " '2_rmcv_rutpt_genELtask_15_01_03' '2_ense_enself_genELtask_1_00_00'\n", - " '2_rt10v_rutpt_genELtask_36_03_02' '2_enself_rutpt_genELtask_16_01_04'\n", - " '2_enself_rt10v_genELtask_13_01_01' '2_ense_rmcv_genELtask_36_03_02'\n", - " '2_enself_rmcv_genELtask_13_01_01' '2_rt10v_rutpt_genELtask_46_04_01'\n", - " '2_enseef_enve_genELtask_53_04_08' '2_ense_enve_genELtask_64_05_08'\n", - " '2_enself_rt10v_genELtask_6_00_05' '2_ense_rutpt_genELtask_76_06_09'\n", - " '2_enve_rt10v_genELtask_88_07_10' '2_ense_rutpt_genELtask_61_05_05'\n", - " '2_enve_rmcv_genELtask_91_08_02' '2_enseef_rutpt_genELtask_37_03_03'\n", - " '2_ense_rmcv_genELtask_26_02_03' '2_enself_enve_genELtask_32_02_09'\n", - " '2_rmcv_rutpt_genELtask_22_01_10' '2_enseef_enve_genELtask_15_01_03'\n", - " '2_enve_rutpt_genELtask_98_08_09' '2_ense_enself_genELtask_35_03_01'\n", - " '2_ense_rt10v_genELtask_25_02_02' '2_rt10v_rutpt_genELtask_80_07_02'\n", - " '2_rt10v_rutpt_genELtask_92_08_03' '2_enve_rt10v_genELtask_23_02_00'\n", - " '2_enself_rt10v_genELtask_8_00_07' '2_enseef_enve_genELtask_19_01_07'\n", - " '2_ense_rt10v_genELtask_51_04_06' '2_enseef_rt10v_genELtask_11_00_10'\n", - " '2_rmcv_rt10v_genELtask_67_06_00' '2_ense_rutpt_genELtask_36_03_02'\n", - " '2_enve_rt10v_genELtask_79_07_01' '2_enve_rt10v_genELtask_72_06_05'\n", - " '2_enself_rmcv_genELtask_25_02_02']\n" - ] - } - ], - "source": [ - "## LOAD FEATURE FILES\n", - "#bpi_ft = pd.read_csv(\"../data/34_bpic_features.csv\").sort_values('log')\n", - "bpi_ft = pd.read_csv(\"../data/BaselineED_feat.csv\").sort_values('log')\n", - "\n", - "#gen_ft =pd.read_csv(\"../output/generated/instance_selection_feat.csv\")\n", - "gen_ft = pd.read_csv(\"../data/GenED_feat.csv\")\n", - "if EXP_BASELINE:\n", - " gen_ft = pd.read_csv(\"../data/GenBaselineED_feat.csv\")\n", - " gen_ft['log']=gen_ft.apply(lambda x: \"Gen\"+x['log'], axis=1)\n", - "\n", - "#print(gen_ft['log'].unique())\n", - "\n", - "paper_cols = [\"log\",\"ratio_unique_traces_per_trace\", \"ratio_most_common_variant\", 'ratio_top_10_variants', 'epa_normalized_variant_entropy', 'epa_normalized_sequence_entropy', 'epa_normalized_sequence_entropy_linear_forgetting', 'epa_normalized_sequence_entropy_exponential_forgetting'] \n", - "bpi_ft= bpi_ft[paper_cols]\n", - "print(gen_ft.shape, bpi_ft.shape)\n", - "#print(gen_ft.columns == df.columns)\n", - "bpi_ft['source']='Real'\n", - "gen_ft['source']='Generated'\n", - "\n", - "\n", - "#if EXP_BASELINE:\n", - "# gen_ft['log']=gen_ft.apply(lambda x: \"Gen\"+x['log'], axis=1)\n", - "both_df = pd.concat([bpi_ft, gen_ft])\n", - "#both_df['log']=both_df.apply(lambda x: x['log'].replace(\".xes\",\"\"), axis=1)\n", - "#both_df['log']=both_df.apply(lambda x: x['log'].replace(\"_processed\",\"\"), axis=1)\n", - "print(both_df.shape)\n", - "print(both_df['log'].unique())\n", - "feature_logs = both_df['log'].unique()\n", - "#print(feature_logs)" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "id": "d3d0e83b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(432, 19) (17, 19)\n", - "(449, 17)\n", - "['BPIC13cp' 'BPIC13inc' 'BPIC13op' 'BPIC14dc_p' 'BPIC14di_p' 'BPIC16c_p'\n", - " 'BPIC16wm_p' 'BPIC17ol' 'BPIC20a' 'BPIC20b' 'BPIC20c' 'BPIC20d' 'BPIC20e'\n", - " 'HD' 'RTFMP' 'RWABOCSL' 'SEPSIS' '2_ense_rmcv_genELtask_67_06_00'\n", - " '2_enself_rmcv_genELtask_13_01_01' '2_rt10v_rutpt_genELtask_1_00_00'\n", - " '2_ense_enve_genELtask_2_00_01' '2_rmcv_rutpt_genELtask_35_03_01'\n", - " '2_enseef_rutpt_genELtask_30_02_07' '2_enve_rutpt_genELtask_98_08_09'\n", - " '2_ense_enve_genELtask_27_02_04' '2_rmcv_rutpt_genELtask_40_03_06'\n", - " '2_enve_rmcv_genELtask_57_05_01' '2_ense_rutpt_genELtask_13_01_01'\n", - " '2_enself_rutpt_genELtask_6_00_05' '2_enself_enve_genELtask_1_00_00'\n", - " '2_ense_enve_genELtask_75_06_08' '2_ense_rutpt_genELtask_63_05_07'\n", - " '2_ense_enseef_genELtask_13_01_01' '2_enve_rt10v_genELtask_87_07_09'\n", - " '2_enseef_rmcv_genELtask_26_02_03' '2_enseef_rmcv_genELtask_7_00_06'\n", - " '2_enseef_rutpt_genELtask_66_05_10' '2_ense_enve_genELtask_38_03_04'\n", - " '2_ense_enself_genELtask_46_04_01' '2_ense_rmcv_genELtask_57_05_01'\n", - " '2_enseef_rt10v_genELtask_57_05_01' '2_enve_rt10v_genELtask_95_08_06'\n", - " '2_ense_rmcv_genELtask_16_01_04' '2_ense_enve_genELtask_16_01_04'\n", - " '2_enseef_enve_genELtask_16_01_04' '2_enve_rt10v_genELtask_26_02_03'\n", - " '2_ense_enve_genELtask_86_07_08' '2_ense_rt10v_genELtask_36_03_02'\n", - " '2_ense_rutpt_genELtask_74_06_07' '2_ense_enve_genELtask_63_05_07'\n", - " '2_enseef_rutpt_genELtask_36_03_02' '2_enve_rutpt_genELtask_104_09_04'\n", - " '2_enseef_rmcv_genELtask_25_02_02' '2_enself_rt10v_genELtask_46_04_01'\n", - " '2_enve_rutpt_genELtask_92_08_03' '2_rt10v_rutpt_genELtask_39_03_05'\n", - " '2_enve_rutpt_genELtask_90_08_01' '2_enseef_rt10v_genELtask_30_02_07'\n", - " '2_ense_rt10v_genELtask_6_00_05' '2_enve_rt10v_genELtask_83_07_05'\n", - " '2_ense_rutpt_genELtask_60_05_04' '2_rmcv_rutpt_genELtask_27_02_04'\n", - " '2_ense_enself_genELtask_68_06_01' '2_ense_rutpt_genELtask_64_05_08'\n", - " '2_ense_rt10v_genELtask_52_04_07' '2_enself_rt10v_genELtask_4_00_03'\n", - " '2_enve_rutpt_genELtask_40_03_06' '2_enve_rmcv_genELtask_6_00_05'\n", - " '2_enself_rt10v_genELtask_5_00_04' '2_rt10v_rutpt_genELtask_46_04_01'\n", - " '2_enself_rutpt_genELtask_16_01_04' '2_ense_rutpt_genELtask_51_04_06'\n", - " '2_ense_rmcv_genELtask_15_01_03' '2_ense_enve_genELtask_50_04_05'\n", - " '2_rt10v_rutpt_genELtask_36_03_02' '2_enseef_enve_genELtask_43_03_09'\n", - " '2_enseef_rt10v_genELtask_35_03_01' '2_rmcv_rt10v_genELtask_29_02_06'\n", - " '2_enseef_enself_genELtask_59_05_03' '2_rt10v_rutpt_genELtask_34_03_00'\n", - " '2_enve_rmcv_genELtask_70_06_03' '2_enve_rmcv_genELtask_81_07_03'\n", - " '2_enseef_rutpt_genELtask_33_02_10' '2_enseef_rutpt_genELtask_44_03_10'\n", - " '2_rmcv_rutpt_genELtask_20_01_08' '2_ense_rutpt_genELtask_73_06_06'\n", - " '2_ense_rutpt_genELtask_43_03_09' '2_ense_rt10v_genELtask_60_05_04'\n", - " '2_ense_rt10v_genELtask_58_05_02' '2_ense_rutpt_genELtask_24_02_01'\n", - " '2_enself_enve_genELtask_9_00_08' '2_enve_rmcv_genELtask_58_05_02'\n", - " '2_enseef_rmcv_genELtask_24_02_01' '2_ense_rmcv_genELtask_36_03_02'\n", - " '2_rt10v_rutpt_genELtask_79_07_01' '2_ense_enseef_genELtask_48_04_03'\n", - " '2_enve_rutpt_genELtask_68_06_01' '2_enself_rutpt_genELtask_19_01_07'\n", - " '2_enself_rutpt_genELtask_15_01_03' '2_ense_rt10v_genELtask_49_04_04'\n", - " '2_ense_rutpt_genELtask_36_03_02' '2_ense_enself_genELtask_2_00_01'\n", - " '2_ense_rt10v_genELtask_53_04_08' '2_enve_rutpt_genELtask_79_07_01'\n", - " '2_ense_enve_genELtask_51_04_06' '2_rmcv_rt10v_genELtask_37_03_03'\n", - " '2_ense_enve_genELtask_31_02_08' '2_enve_rt10v_genELtask_85_07_07'\n", - " '2_ense_rutpt_genELtask_48_04_03' '2_enseef_rmcv_genELtask_37_03_03'\n", - " '2_enself_rt10v_genELtask_18_01_06' '2_ense_enve_genELtask_13_01_01'\n", - " '2_enseef_enve_genELtask_32_02_09' '2_enve_rutpt_genELtask_38_03_04'\n", - " '2_ense_rutpt_genELtask_55_04_10' '2_enve_rmcv_genELtask_48_04_03'\n", - " '2_ense_enve_genELtask_85_07_07' '2_rmcv_rt10v_genELtask_38_03_04'\n", - " '2_rt10v_rutpt_genELtask_92_08_03' '2_ense_enve_genELtask_14_01_02'\n", - " '2_ense_rt10v_genELtask_21_01_09' '2_enseef_rt10v_genELtask_20_01_08'\n", - " '2_enve_rutpt_genELtask_57_05_01' '2_enve_rt10v_genELtask_90_08_01'\n", - " '2_enve_rt10v_genELtask_88_07_10' '2_rt10v_rutpt_genELtask_91_08_02'\n", - " '2_ense_enself_genELtask_81_07_03' '2_enve_rutpt_genELtask_65_05_09'\n", - " '2_enve_rt10v_genELtask_56_05_00' '2_ense_rmcv_genELtask_47_04_02'\n", - " '2_rmcv_rt10v_genELtask_12_01_00' '2_enve_rt10v_genELtask_109_09_09'\n", - " '2_enself_rmcv_genELtask_6_00_05' '2_enself_rt10v_genELtask_13_01_01'\n", - " '2_enseef_rmcv_genELtask_14_01_02' '2_enself_enve_genELtask_32_02_09'\n", - " '2_ense_enve_genELtask_52_04_07' '2_enseef_rt10v_genELtask_46_04_01'\n", - " '2_ense_enve_genELtask_3_00_02' '2_enseef_enve_genELtask_64_05_08'\n", - " '2_enve_rutpt_genELtask_74_06_07' '2_rt10v_rutpt_genELtask_52_04_07'\n", - " '2_rt10v_rutpt_genELtask_71_06_04' '2_enve_rt10v_genELtask_74_06_07'\n", - " '2_enve_rt10v_genELtask_47_04_02' '2_ense_enseef_genELtask_59_05_03'\n", - " '2_ense_enseef_genELtask_1_00_00' '2_rmcv_rt10v_genELtask_39_03_05'\n", - " '2_enself_enve_genELtask_3_00_02' '2_enseef_rmcv_genELtask_56_05_00'\n", - " '2_enve_rt10v_genELtask_48_04_03' '2_ense_enve_genELtask_1_00_00'\n", - " '2_ense_enve_genELtask_74_06_07' '2_ense_rutpt_genELtask_88_07_10'\n", - " '2_enself_rmcv_genELtask_15_01_03' '2_rmcv_rt10v_genELtask_54_04_09'\n", - " '2_ense_enseef_genELtask_47_04_02' '2_rt10v_rutpt_genELtask_62_05_06'\n", - " '2_rt10v_rutpt_genELtask_90_08_01' '2_enve_rt10v_genELtask_60_05_04'\n", - " '2_rt10v_rutpt_genELtask_27_02_04' '2_rmcv_rt10v_genELtask_27_02_04'\n", - " '2_ense_rmcv_genELtask_37_03_03' '2_enseef_enve_genELtask_31_02_08'\n", - " '2_rt10v_rutpt_genELtask_61_05_05' '2_ense_rt10v_genELtask_25_02_02'\n", - " '2_enseef_enve_genELtask_30_02_07' '2_enself_rt10v_genELtask_10_00_09'\n", - " '2_rmcv_rutpt_genELtask_38_03_04' '2_enself_enve_genELtask_6_00_05'\n", - " '2_enve_rutpt_genELtask_46_04_01' '2_ense_rutpt_genELtask_49_04_04'\n", - " '2_ense_rutpt_genELtask_53_04_08' '2_enseef_enself_genELtask_36_03_02'\n", - " '2_ense_rt10v_genELtask_51_04_06' '2_ense_enve_genELtask_64_05_08'\n", - " '2_ense_enseef_genELtask_35_03_01' '2_enve_rutpt_genELtask_77_06_10'\n", - " '2_enseef_rmcv_genELtask_13_01_01' '2_ense_enseef_genELtask_58_05_02'\n", - " '2_enve_rt10v_genELtask_96_08_07' '2_enseef_rutpt_genELtask_27_02_04'\n", - " '2_ense_rt10v_genELtask_43_03_09' '2_enve_rt10v_genELtask_75_06_08'\n", - " '2_rt10v_rutpt_genELtask_51_04_06' '2_enve_rmcv_genELtask_47_04_02'\n", - " '2_enve_rutpt_genELtask_70_06_03' '2_enseef_enself_genELtask_13_01_01'\n", - " '2_enself_rt10v_genELtask_6_00_05' '2_enve_rmcv_genELtask_89_08_00'\n", - " '2_ense_rt10v_genELtask_50_04_05' '2_enve_rt10v_genELtask_86_07_08'\n", - " '2_ense_rt10v_genELtask_33_02_10' '2_enself_rt10v_genELtask_21_01_09'\n", - " '2_rt10v_rutpt_genELtask_102_09_02' '2_enseef_rutpt_genELtask_53_04_08'\n", - " '2_rt10v_rutpt_genELtask_80_07_02' '2_enself_rmcv_genELtask_3_00_02'\n", - " '2_enseef_rt10v_genELtask_21_01_09' '2_ense_rt10v_genELtask_31_02_08'\n", - " '2_rmcv_rutpt_genELtask_22_01_10' '2_ense_enself_genELtask_36_03_02'\n", - " '2_ense_enseef_genELtask_70_06_03' '2_ense_rutpt_genELtask_59_05_03'\n", - " '2_enve_rutpt_genELtask_83_07_05' '2_enve_rutpt_genELtask_93_08_04'\n", - " '2_ense_enseef_genELtask_36_03_02' '2_enve_rutpt_genELtask_81_07_03'\n", - " '2_ense_rutpt_genELtask_46_04_01' '2_enself_enve_genELtask_43_03_09'\n", - " '2_enve_rutpt_genELtask_91_08_02' '2_ense_enve_genELtask_30_02_07'\n", - " '2_enself_enve_genELtask_31_02_08' '2_ense_enseef_genELtask_82_07_04'\n", - " '2_ense_enseef_genELtask_71_06_04' '2_rmcv_rt10v_genELtask_17_01_05'\n", - " '2_ense_rt10v_genELtask_63_05_07' '2_enve_rutpt_genELtask_48_04_03'\n", - " '2_rmcv_rutpt_genELtask_39_03_05' '2_ense_rmcv_genELtask_6_00_05'\n", - " '2_enself_enve_genELtask_42_03_08' '2_enve_rutpt_genELtask_55_04_10'\n", - " '2_enself_enve_genELtask_7_00_06' '2_enself_enve_genELtask_54_04_09'\n", - " '2_enseef_enve_genELtask_53_04_08' '2_ense_rutpt_genELtask_58_05_02'\n", - " '2_enseef_rmcv_genELtask_6_00_05' '2_enve_rmcv_genELtask_69_06_02'\n", - " '2_enseef_enve_genELtask_19_01_07' '2_enve_rt10v_genELtask_73_06_06'\n", - " '2_rt10v_rutpt_genELtask_38_03_04' '2_enseef_rutpt_genELtask_15_01_03'\n", - " '2_enve_rutpt_genELtask_53_04_08' '2_enve_rt10v_genELtask_102_09_02'\n", - " '2_ense_rt10v_genELtask_45_04_00' '2_enseef_rt10v_genELtask_18_01_06'\n", - " '2_enself_rt10v_genELtask_35_03_01' '2_ense_enseef_genELtask_60_05_04'\n", - " '2_rmcv_rt10v_genELtask_40_03_06' '2_enseef_rutpt_genELtask_26_02_03'\n", - " '2_enseef_enself_genELtask_37_03_03' '2_enseef_enve_genELtask_63_05_07'\n", - " '2_enve_rt10v_genELtask_82_07_04' '2_enve_rt10v_genELtask_79_07_01'\n", - " '2_enseef_rt10v_genELtask_29_02_06' '2_ense_rutpt_genELtask_61_05_05'\n", - " '2_ense_rt10v_genELtask_71_06_04' '2_enseef_enve_genELtask_17_01_05'\n", - " '2_enve_rmcv_genELtask_80_07_02' '2_enve_rutpt_genELtask_3_00_02'\n", - " '2_enve_rmcv_genELtask_68_06_01' '2_enve_rmcv_genELtask_90_08_01'\n", - " '2_ense_rmcv_genELtask_26_02_03' '2_enself_rutpt_genELtask_1_00_00'\n", - " '2_enself_enve_genELtask_19_01_07' '2_rt10v_rutpt_genELtask_41_03_07'\n", - " '2_enself_rutpt_genELtask_13_01_01' '2_enve_rt10v_genELtask_23_02_00'\n", - " '2_enseef_rmcv_genELtask_45_04_00' '2_rmcv_rutpt_genELtask_13_01_01'\n", - " '2_ense_enself_genELtask_35_03_01' '2_ense_rmcv_genELtask_78_07_00'\n", - " '2_ense_rt10v_genELtask_64_05_08' '2_ense_enve_genELtask_43_03_09'\n", - " '2_enself_rutpt_genELtask_4_00_03' '2_enseef_enself_genELtask_24_02_01'\n", - " '2_enve_rmcv_genELtask_78_07_00' '2_ense_rutpt_genELtask_35_03_01'\n", - " '2_enself_rmcv_genELtask_24_02_01' '2_ense_rmcv_genELtask_35_03_01'\n", - " '2_ense_rutpt_genELtask_25_02_02' '2_enseef_rt10v_genELtask_23_02_00'\n", - " '2_ense_rutpt_genELtask_54_04_09' '2_enseef_enve_genELtask_29_02_06'\n", - " '2_enseef_enself_genELtask_1_00_00' '2_enseef_rt10v_genELtask_22_01_10'\n", - " '2_enself_rmcv_genELtask_36_03_02' '2_enseef_rutpt_genELtask_25_02_02'\n", - " '2_enve_rutpt_genELtask_82_07_04' '2_ense_rutpt_genELtask_12_01_00'\n", - " '2_enseef_rt10v_genELtask_6_00_05' '2_ense_enve_genELtask_48_04_03'\n", - " '2_ense_rmcv_genELtask_48_04_03' '2_enve_rmcv_genELtask_100_09_00'\n", - " '2_rmcv_rt10v_genELtask_15_01_03' '2_enve_rt10v_genELtask_45_04_00'\n", - " '2_enself_rt10v_genELtask_20_01_08' '2_enve_rutpt_genELtask_44_03_10'\n", - " '2_enseef_rutpt_genELtask_13_01_01' '2_enseef_rt10v_genELtask_12_01_00'\n", - " '2_ense_enself_genELtask_1_00_00' '2_enseef_enve_genELtask_18_01_06'\n", - " '2_rmcv_rutpt_genELtask_25_02_02' '2_ense_enseef_genELtask_24_02_01'\n", - " '2_enseef_enve_genELtask_54_04_09' '2_ense_rt10v_genELtask_55_04_10'\n", - " '2_ense_rmcv_genELtask_59_05_03' '2_rmcv_rutpt_genELtask_57_05_01'\n", - " '2_enseef_rt10v_genELtask_11_00_10' '2_enself_rt10v_genELtask_31_02_08'\n", - " '2_enve_rmcv_genELtask_35_03_01' '2_enve_rt10v_genELtask_77_06_10'\n", - " '2_ense_enve_genELtask_40_03_06' '2_enseef_enve_genELtask_2_00_01'\n", - " '2_enseef_rmcv_genELtask_36_03_02' '2_ense_rutpt_genELtask_33_02_10'\n", - " '2_rmcv_rt10v_genELtask_48_04_03' '2_enself_enve_genELtask_53_04_08'\n", - " '2_enseef_enve_genELtask_42_03_08' '2_ense_rt10v_genELtask_47_04_02'\n", - " '2_ense_enve_genELtask_42_03_08' '2_ense_rutpt_genELtask_77_06_10'\n", - " '2_enve_rutpt_genELtask_99_08_10' '2_enve_rt10v_genELtask_76_06_09'\n", - " '2_rmcv_rt10v_genELtask_67_06_00' '2_rt10v_rutpt_genELtask_81_07_03'\n", - " '2_enseef_enself_genELtask_60_05_04' '2_rmcv_rt10v_genELtask_20_01_08'\n", - " '2_rmcv_rt10v_genELtask_34_03_00' '2_rt10v_rutpt_genELtask_49_04_04'\n", - " '2_rt10v_rutpt_genELtask_22_01_10' '2_rt10v_rutpt_genELtask_101_09_01'\n", - " '2_enve_rmcv_genELtask_49_04_04' '2_ense_rt10v_genELtask_41_03_07'\n", - " '2_ense_rt10v_genELtask_22_01_10' '2_enseef_rt10v_genELtask_27_02_04'\n", - " '2_enve_rt10v_genELtask_17_01_05' '2_enself_rutpt_genELtask_2_00_01'\n", - " '2_enself_rutpt_genELtask_20_01_08' '2_ense_enve_genELtask_37_03_03'\n", - " '2_enself_rutpt_genELtask_44_03_10' '2_ense_rt10v_genELtask_68_06_01'\n", - " '2_enve_rt10v_genELtask_64_05_08' '2_enself_enve_genELtask_29_02_06'\n", - " '2_enseef_enself_genELtask_2_00_01' '2_ense_enve_genELtask_18_01_06'\n", - " '2_ense_rmcv_genELtask_46_04_01' '2_enseef_rt10v_genELtask_47_04_02'\n", - " '2_enseef_enve_genELtask_52_04_07' '2_enself_rutpt_genELtask_55_04_10'\n", - " '2_enseef_enve_genELtask_3_00_02' '2_ense_rt10v_genELtask_40_03_06'\n", - " '2_ense_rmcv_genELtask_17_01_05' '2_enself_rmcv_genELtask_17_01_05'\n", - " '2_rmcv_rutpt_genELtask_11_00_10' '2_enseef_rt10v_genELtask_19_01_07'\n", - " '2_rt10v_rutpt_genELtask_68_06_01' '2_enve_rmcv_genELtask_104_09_04'\n", - " '2_enself_rutpt_genELtask_21_01_09' '2_enseef_rutpt_genELtask_12_01_00'\n", - " '2_enve_rmcv_genELtask_7_00_06' '2_ense_rutpt_genELtask_62_05_06'\n", - " '2_rmcv_rt10v_genELtask_19_01_07' '2_rmcv_rt10v_genELtask_43_03_09'\n", - " '2_ense_rt10v_genELtask_70_06_03' '2_ense_rt10v_genELtask_23_02_00'\n", - " '2_ense_enve_genELtask_41_03_07' '2_ense_rt10v_genELtask_32_02_09'\n", - " '2_rmcv_rt10v_genELtask_55_04_10' '2_enseef_rutpt_genELtask_37_03_03'\n", - " '2_ense_rt10v_genELtask_62_05_06' '2_ense_enself_genELtask_47_04_02'\n", - " '2_enself_rmcv_genELtask_7_00_06' '2_enseef_rmcv_genELtask_15_01_03'\n", - " '2_enself_rmcv_genELtask_45_04_00' '2_enself_rt10v_genELtask_22_01_10'\n", - " '2_enve_rt10v_genELtask_6_00_05' '2_ense_rutpt_genELtask_26_02_03'\n", - " '2_enseef_enve_genELtask_1_00_00' '2_enseef_enve_genELtask_15_01_03'\n", - " '2_enself_enve_genELtask_2_00_01' '2_enself_rutpt_genELtask_3_00_02'\n", - " '2_rt10v_rutpt_genELtask_42_03_08' '2_enve_rmcv_genELtask_92_08_03'\n", - " '2_ense_enve_genELtask_62_05_06' '2_ense_rutpt_genELtask_39_03_05'\n", - " '2_enseef_enve_genELtask_27_02_04' '2_ense_enseef_genELtask_83_07_05'\n", - " '2_ense_enve_genELtask_76_06_09' '2_ense_rt10v_genELtask_79_07_01'\n", - " '2_enve_rt10v_genELtask_57_05_01' '2_ense_enve_genELtask_53_04_08'\n", - " '2_enseef_rutpt_genELtask_38_03_04' '2_ense_rutpt_genELtask_1_00_00'\n", - " '2_enve_rt10v_genELtask_84_07_06' '2_enself_rmcv_genELtask_25_02_02'\n", - " '2_enve_rt10v_genELtask_46_04_01' '2_enve_rt10v_genELtask_108_09_08'\n", - " '2_enself_rt10v_genELtask_36_03_02' '2_ense_enseef_genELtask_25_02_02'\n", - " '2_enself_rutpt_genELtask_22_01_10' '2_ense_rutpt_genELtask_52_04_07'\n", - " '2_enself_rutpt_genELtask_42_03_08' '2_ense_enself_genELtask_24_02_01'\n", - " '2_ense_rmcv_genELtask_58_05_02' '2_ense_rutpt_genELtask_66_05_10'\n", - " '2_rmcv_rutpt_genELtask_45_04_00' '2_enseef_rt10v_genELtask_17_01_05'\n", - " '2_enseef_rutpt_genELtask_54_04_09' '2_enve_rutpt_genELtask_63_05_07'\n", - " '2_ense_rt10v_genELtask_61_05_05' '2_enve_rutpt_genELtask_102_09_02'\n", - " '2_enseef_rt10v_genELtask_41_03_07' '2_ense_enseef_genELtask_69_06_02'\n", - " '2_enve_rmcv_genELtask_40_03_06' '2_enself_rt10v_genELtask_14_01_02'\n", - " '2_rmcv_rutpt_genELtask_26_02_03' '2_enve_rutpt_genELtask_64_05_08'\n", - " '2_ense_rt10v_genELtask_42_03_08' '2_enseef_rutpt_genELtask_2_00_01'\n", - " '2_enve_rt10v_genELtask_97_08_08' '2_enseef_rutpt_genELtask_14_01_02'\n", - " '2_enself_rmcv_genELtask_14_01_02' '2_enve_rt10v_genELtask_91_08_02'\n", - " '2_ense_enve_genELtask_29_02_06' '2_ense_enself_genELtask_58_05_02'\n", - " '2_enve_rutpt_genELtask_66_05_10' '2_enself_rmcv_genELtask_2_00_01'\n", - " '2_rmcv_rutpt_genELtask_56_05_00' '2_rt10v_rutpt_genELtask_30_02_07'\n", - " '2_ense_rmcv_genELtask_7_00_06' '2_enself_enve_genELtask_17_01_05'\n", - " '2_enve_rutpt_genELtask_1_00_00' '2_enself_rt10v_genELtask_40_03_06'\n", - " '2_ense_enself_genELtask_25_02_02' '2_ense_rt10v_genELtask_57_05_01'\n", - " '2_rmcv_rutpt_genELtask_14_01_02' '2_enseef_rutpt_genELtask_1_00_00'\n", - " '2_enseef_enve_genELtask_21_01_09' '2_enseef_enself_genELtask_48_04_03'\n", - " '2_ense_rt10v_genELtask_74_06_07' '2_rt10v_rutpt_genELtask_82_07_04'\n", - " '2_ense_rutpt_genELtask_71_06_04' '2_ense_enve_genELtask_61_05_05'\n", - " '2_enself_rt10v_genELtask_7_00_06' '2_enve_rutpt_genELtask_60_05_04'\n", - " '2_ense_rmcv_genELtask_18_01_06' '2_enself_rmcv_genELtask_34_03_00'\n", - " '2_enve_rutpt_genELtask_61_05_05' '2_enve_rt10v_genELtask_80_07_02'\n", - " '2_enseef_rutpt_genELtask_40_03_06' '2_ense_enself_genELtask_70_06_03'\n", - " '2_enseef_rt10v_genELtask_43_03_09' '2_enself_rutpt_genELtask_5_00_04'\n", - " '2_ense_rt10v_genELtask_12_01_00' '2_enseef_enself_genELtask_49_04_04'\n", - " '2_ense_rutpt_genELtask_75_06_08' '2_rmcv_rt10v_genELtask_2_00_01'\n", - " '2_enself_rt10v_genELtask_8_00_07']\n" - ] - } - ], - "source": [ - "## LOAD DISCOVERY METRICS FILES\n", - "#bpi_pd = pd.read_csv(\"../output/benchmark/bpics_PDbenchmark.csv\").sort_values('log')\n", - "bpi_pd = pd.read_csv(\"../data/BaselineED_bench.csv\").sort_values('log')\n", - "\n", - "#gen_pd = pd.read_csv(\"../output/benchmark/instance_selection_3_2_bench.csv\")\n", - "gen_pd = pd.read_csv(\"../data/GenED_bench.csv\")\n", - "if EXP_BASELINE:\n", - " gen_pd = pd.read_csv(\"../data/GenBaselineED_bench.csv\")\n", - " gen_pd['log']=gen_pd.apply(lambda x: \"Gen\"+x['log'].replace(\"genEL\",\"\").rsplit(\"_\",7)[0], axis=1)\n", - "\n", - "#gen_pd = gen_pd.sample(30)\n", - "\n", - "paper_metrics = ['log', 'fitness_heu', 'precision_heu',\n", - " 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp',\n", - " 'size_ilp','cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf', 'source']\n", - "\n", - "print(gen_pd.shape, bpi_pd.shape)\n", - "bpi_pd['source']='Real'\n", - "gen_pd['source']='Generated'\n", - "#gen_pd['log']=gen_pd.apply(lambda x: \"Gen\"+x['log'].replace(\"genEL\",\"\").rsplit(\"_\",7)[0], axis=1)\n", - "#if EXP_BASELINE:\n", - "# gen_pd['log']=gen_pd.apply(lambda x: \"Gen\"+x['log'], axis=1)\n", - "both_pd = pd.concat([bpi_pd, gen_pd])\n", - "both_pd= both_pd[paper_metrics]\n", - "#both_pd['log']=both_pd.apply(lambda x: x['log'].replace(\".xes\",\"\"), axis=1)\n", - "#both_pd['log']=both_pd.apply(lambda x: x['log'].replace(\"_processed\",\"\"), axis=1)\n", - "print(both_pd.shape)\n", - "print(both_pd['log'].unique())" - ] - }, - { - "cell_type": "code", - "execution_count": 106, - "id": "ca100d3e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(449, 24)\n" - ] - }, - { - "data": { - "text/plain": [ - "array(['BPIC13cp', 'BPIC13inc', 'BPIC13op', 'BPIC14dc_p', 'BPIC14di_p',\n", - " 'BPIC16c_p', 'BPIC16wm_p', 'BPIC17ol', 'BPIC20a', 'BPIC20b',\n", - " 'BPIC20c', 'BPIC20d', 'BPIC20e', 'HD', 'RTFMP', 'RWABOCSL',\n", - " 'SEPSIS', '2_rmcv_rt10v_genELtask_40_03_06',\n", - " '2_rt10v_rutpt_genELtask_39_03_05',\n", - " '2_ense_rt10v_genELtask_32_02_09',\n", - " '2_enseef_rt10v_genELtask_41_03_07',\n", - " '2_enseef_rt10v_genELtask_18_01_06',\n", - " '2_ense_rt10v_genELtask_40_03_06',\n", - " '2_enve_rt10v_genELtask_45_04_00',\n", - " '2_ense_rt10v_genELtask_21_01_09',\n", - " '2_enself_rt10v_genELtask_10_00_09',\n", - " '2_enseef_rt10v_genELtask_20_01_08',\n", - " '2_enself_enve_genELtask_42_03_08',\n", - " '2_enself_rmcv_genELtask_36_03_02',\n", - " '2_ense_enseef_genELtask_60_05_04',\n", - " '2_enseef_rmcv_genELtask_6_00_05',\n", - " '2_enself_rutpt_genELtask_5_00_04',\n", - " '2_enve_rutpt_genELtask_53_04_08',\n", - " '2_enself_rt10v_genELtask_22_01_10',\n", - " '2_enseef_enve_genELtask_63_05_07',\n", - " '2_enseef_rutpt_genELtask_26_02_03',\n", - " '2_enself_rutpt_genELtask_20_01_08',\n", - " '2_enseef_rt10v_genELtask_30_02_07',\n", - " '2_enseef_enself_genELtask_60_05_04',\n", - " '2_enve_rmcv_genELtask_48_04_03',\n", - " '2_enve_rutpt_genELtask_74_06_07',\n", - " '2_ense_rt10v_genELtask_45_04_00',\n", - " '2_rmcv_rutpt_genELtask_56_05_00',\n", - " '2_enself_rt10v_genELtask_20_01_08',\n", - " '2_ense_enself_genELtask_70_06_03',\n", - " '2_ense_enseef_genELtask_24_02_01',\n", - " '2_enself_enve_genELtask_17_01_05',\n", - " '2_enve_rmcv_genELtask_69_06_02',\n", - " '2_ense_enseef_genELtask_82_07_04',\n", - " '2_ense_rt10v_genELtask_53_04_08',\n", - " '2_enseef_rutpt_genELtask_25_02_02',\n", - " '2_enseef_rt10v_genELtask_57_05_01',\n", - " '2_rt10v_rutpt_genELtask_82_07_04',\n", - " '2_rt10v_rutpt_genELtask_27_02_04',\n", - " '2_enve_rt10v_genELtask_47_04_02',\n", - " '2_enself_rutpt_genELtask_22_01_10',\n", - " '2_ense_enve_genELtask_2_00_01',\n", - " '2_enseef_rutpt_genELtask_14_01_02',\n", - " '2_enve_rutpt_genELtask_64_05_08',\n", - " '2_enve_rt10v_genELtask_77_06_10',\n", - " '2_enve_rmcv_genELtask_49_04_04',\n", - " '2_enseef_enve_genELtask_3_00_02',\n", - " '2_enseef_enself_genELtask_13_01_01',\n", - " '2_enve_rmcv_genELtask_6_00_05', '2_enve_rt10v_genELtask_96_08_07',\n", - " '2_ense_enseef_genELtask_58_05_02',\n", - " '2_enself_rutpt_genELtask_19_01_07',\n", - " '2_enseef_enself_genELtask_2_00_01',\n", - " '2_enself_rt10v_genELtask_31_02_08',\n", - " '2_ense_enve_genELtask_75_06_08', '2_enve_rmcv_genELtask_47_04_02',\n", - " '2_enseef_rmcv_genELtask_56_05_00',\n", - " '2_enve_rutpt_genELtask_79_07_01',\n", - " '2_ense_enself_genELtask_2_00_01',\n", - " '2_ense_enself_genELtask_46_04_01',\n", - " '2_ense_rmcv_genELtask_59_05_03',\n", - " '2_enseef_rutpt_genELtask_38_03_04',\n", - " '2_ense_enseef_genELtask_71_06_04',\n", - " '2_enve_rt10v_genELtask_17_01_05',\n", - " '2_enve_rmcv_genELtask_68_06_01',\n", - " '2_enseef_rmcv_genELtask_15_01_03',\n", - " '2_enseef_rutpt_genELtask_40_03_06',\n", - " '2_ense_rt10v_genELtask_71_06_04',\n", - " '2_rt10v_rutpt_genELtask_51_04_06',\n", - " '2_enseef_rmcv_genELtask_7_00_06',\n", - " '2_ense_enve_genELtask_27_02_04',\n", - " '2_enseef_rmcv_genELtask_26_02_03',\n", - " '2_enseef_enve_genELtask_42_03_08',\n", - " '2_enseef_rt10v_genELtask_22_01_10',\n", - " '2_enve_rutpt_genELtask_3_00_02',\n", - " '2_ense_rutpt_genELtask_48_04_03',\n", - " '2_enseef_rmcv_genELtask_24_02_01',\n", - " '2_rmcv_rt10v_genELtask_43_03_09',\n", - " '2_enve_rmcv_genELtask_57_05_01', '2_ense_enve_genELtask_41_03_07',\n", - " '2_ense_enve_genELtask_31_02_08',\n", - " '2_enseef_rt10v_genELtask_19_01_07',\n", - " '2_rmcv_rutpt_genELtask_27_02_04',\n", - " '2_rmcv_rutpt_genELtask_38_03_04',\n", - " '2_ense_enself_genELtask_58_05_02',\n", - " '2_ense_enve_genELtask_74_06_07',\n", - " '2_enself_enve_genELtask_19_01_07',\n", - " '2_ense_rutpt_genELtask_49_04_04',\n", - " '2_ense_rt10v_genELtask_55_04_10',\n", - " '2_enve_rmcv_genELtask_35_03_01',\n", - " '2_enve_rutpt_genELtask_77_06_10',\n", - " '2_ense_rt10v_genELtask_49_04_04',\n", - " '2_ense_enve_genELtask_37_03_03',\n", - " '2_enve_rutpt_genELtask_92_08_03',\n", - " '2_ense_rt10v_genELtask_22_01_10',\n", - " '2_enseef_rt10v_genELtask_12_01_00',\n", - " '2_ense_enve_genELtask_14_01_02',\n", - " '2_enseef_enve_genELtask_30_02_07',\n", - " '2_enself_rt10v_genELtask_4_00_03',\n", - " '2_ense_rt10v_genELtask_60_05_04',\n", - " '2_enve_rt10v_genELtask_6_00_05',\n", - " '2_rt10v_rutpt_genELtask_1_00_00',\n", - " '2_ense_rmcv_genELtask_67_06_00', '2_enve_rmcv_genELtask_80_07_02',\n", - " '2_enself_rmcv_genELtask_2_00_01',\n", - " '2_enve_rt10v_genELtask_73_06_06',\n", - " '2_ense_rt10v_genELtask_62_05_06',\n", - " '2_enseef_rt10v_genELtask_17_01_05',\n", - " '2_ense_rt10v_genELtask_70_06_03',\n", - " '2_enself_rt10v_genELtask_18_01_06',\n", - " '2_ense_rutpt_genELtask_1_00_00',\n", - " '2_rt10v_rutpt_genELtask_71_06_04',\n", - " '2_rmcv_rutpt_genELtask_13_01_01',\n", - " '2_enve_rutpt_genELtask_61_05_05',\n", - " '2_rt10v_rutpt_genELtask_22_01_10',\n", - " '2_enseef_enself_genELtask_1_00_00',\n", - " '2_ense_enve_genELtask_76_06_09',\n", - " '2_enseef_enve_genELtask_52_04_07',\n", - " '2_rmcv_rt10v_genELtask_19_01_07',\n", - " '2_enve_rt10v_genELtask_108_09_08',\n", - " '2_enself_rutpt_genELtask_44_03_10',\n", - " '2_enself_rt10v_genELtask_40_03_06',\n", - " '2_ense_rt10v_genELtask_31_02_08',\n", - " '2_rt10v_rutpt_genELtask_30_02_07',\n", - " '2_enself_enve_genELtask_7_00_06',\n", - " '2_rmcv_rutpt_genELtask_20_01_08',\n", - " '2_enve_rt10v_genELtask_90_08_01',\n", - " '2_enself_enve_genELtask_2_00_01',\n", - " '2_enve_rt10v_genELtask_57_05_01',\n", - " '2_ense_rmcv_genELtask_48_04_03',\n", - " '2_ense_rt10v_genELtask_52_04_07',\n", - " '2_enseef_enve_genELtask_43_03_09',\n", - " '2_enself_rt10v_genELtask_36_03_02',\n", - " '2_ense_rutpt_genELtask_13_01_01',\n", - " '2_rmcv_rt10v_genELtask_17_01_05',\n", - " '2_enseef_rmcv_genELtask_13_01_01',\n", - " '2_ense_rutpt_genELtask_46_04_01',\n", - " '2_ense_enseef_genELtask_59_05_03',\n", - " '2_enve_rt10v_genELtask_74_06_07',\n", - " '2_enseef_rutpt_genELtask_54_04_09',\n", - " '2_enve_rt10v_genELtask_76_06_09',\n", - " '2_enve_rutpt_genELtask_68_06_01',\n", - " '2_ense_rutpt_genELtask_73_06_06',\n", - " '2_rmcv_rt10v_genELtask_48_04_03',\n", - " '2_enseef_enself_genELtask_37_03_03',\n", - " '2_ense_rutpt_genELtask_75_06_08',\n", - " '2_enve_rutpt_genELtask_83_07_05',\n", - " '2_ense_rt10v_genELtask_64_05_08',\n", - " '2_ense_rmcv_genELtask_16_01_04',\n", - " '2_enself_rutpt_genELtask_13_01_01',\n", - " '2_enself_rutpt_genELtask_3_00_02',\n", - " '2_enself_rmcv_genELtask_15_01_03',\n", - " '2_ense_rutpt_genELtask_74_06_07',\n", - " '2_enve_rutpt_genELtask_93_08_04',\n", - " '2_ense_rt10v_genELtask_42_03_08',\n", - " '2_enseef_enve_genELtask_64_05_08',\n", - " '2_ense_enve_genELtask_63_05_07',\n", - " '2_ense_rt10v_genELtask_47_04_02',\n", - " '2_enve_rutpt_genELtask_102_09_02',\n", - " '2_enself_rt10v_genELtask_46_04_01',\n", - " '2_enve_rmcv_genELtask_70_06_03',\n", - " '2_enself_rmcv_genELtask_7_00_06',\n", - " '2_enself_enve_genELtask_54_04_09',\n", - " '2_enve_rutpt_genELtask_65_05_09',\n", - " '2_enseef_rt10v_genELtask_27_02_04',\n", - " '2_enself_rt10v_genELtask_21_01_09',\n", - " '2_ense_rutpt_genELtask_33_02_10',\n", - " '2_ense_rt10v_genELtask_68_06_01',\n", - " '2_enself_rt10v_genELtask_14_01_02',\n", - " '2_enseef_rutpt_genELtask_12_01_00',\n", - " '2_ense_rmcv_genELtask_6_00_05', '2_ense_rutpt_genELtask_12_01_00',\n", - " '2_enve_rmcv_genELtask_7_00_06', '2_ense_rt10v_genELtask_63_05_07',\n", - " '2_enseef_rutpt_genELtask_53_04_08',\n", - " '2_enself_rmcv_genELtask_6_00_05',\n", - " '2_ense_rutpt_genELtask_58_05_02',\n", - " '2_ense_enve_genELtask_50_04_05', '2_enve_rmcv_genELtask_89_08_00',\n", - " '2_ense_rt10v_genELtask_12_01_00',\n", - " '2_ense_rt10v_genELtask_74_06_07',\n", - " '2_enself_enve_genELtask_43_03_09',\n", - " '2_ense_rutpt_genELtask_62_05_06',\n", - " '2_ense_enseef_genELtask_47_04_02',\n", - " '2_enself_enve_genELtask_53_04_08',\n", - " '2_enseef_rt10v_genELtask_35_03_01',\n", - " '2_rt10v_rutpt_genELtask_41_03_07',\n", - " '2_ense_rt10v_genELtask_43_03_09',\n", - " '2_enseef_rutpt_genELtask_1_00_00',\n", - " '2_ense_rmcv_genELtask_7_00_06',\n", - " '2_rt10v_rutpt_genELtask_62_05_06',\n", - " '2_ense_enve_genELtask_61_05_05',\n", - " '2_enself_rt10v_genELtask_35_03_01',\n", - " '2_rt10v_rutpt_genELtask_91_08_02',\n", - " '2_enself_rmcv_genELtask_17_01_05',\n", - " '2_enve_rutpt_genELtask_46_04_01',\n", - " '2_enseef_enve_genELtask_54_04_09',\n", - " '2_ense_rutpt_genELtask_54_04_09',\n", - " '2_enseef_enve_genELtask_32_02_09',\n", - " '2_enve_rutpt_genELtask_44_03_10',\n", - " '2_enself_rmcv_genELtask_14_01_02',\n", - " '2_rmcv_rt10v_genELtask_27_02_04',\n", - " '2_rmcv_rutpt_genELtask_25_02_02',\n", - " '2_enself_enve_genELtask_9_00_08',\n", - " '2_rmcv_rt10v_genELtask_37_03_03',\n", - " '2_rmcv_rt10v_genELtask_34_03_00',\n", - " '2_rmcv_rutpt_genELtask_39_03_05',\n", - " '2_ense_enself_genELtask_24_02_01',\n", - " '2_enseef_rutpt_genELtask_66_05_10',\n", - " '2_ense_rt10v_genELtask_33_02_10',\n", - " '2_enve_rutpt_genELtask_70_06_03',\n", - " '2_ense_rmcv_genELtask_37_03_03',\n", - " '2_ense_rutpt_genELtask_25_02_02',\n", - " '2_ense_rutpt_genELtask_26_02_03',\n", - " '2_enseef_enve_genELtask_29_02_06',\n", - " '2_enseef_rt10v_genELtask_6_00_05',\n", - " '2_ense_rt10v_genELtask_36_03_02',\n", - " '2_ense_rt10v_genELtask_23_02_00',\n", - " '2_rmcv_rt10v_genELtask_12_01_00',\n", - " '2_enve_rt10v_genELtask_109_09_09',\n", - " '2_enve_rt10v_genELtask_80_07_02',\n", - " '2_enve_rutpt_genELtask_48_04_03',\n", - " '2_enve_rt10v_genELtask_64_05_08',\n", - " '2_rt10v_rutpt_genELtask_49_04_04',\n", - " '2_enself_rmcv_genELtask_24_02_01',\n", - " '2_ense_enself_genELtask_47_04_02',\n", - " '2_enseef_rutpt_genELtask_2_00_01',\n", - " '2_enseef_rt10v_genELtask_21_01_09',\n", - " '2_enve_rutpt_genELtask_40_03_06',\n", - " '2_ense_rt10v_genELtask_57_05_01',\n", - " '2_ense_enseef_genELtask_1_00_00',\n", - " '2_ense_rutpt_genELtask_35_03_01',\n", - " '2_ense_rutpt_genELtask_53_04_08',\n", - " '2_enve_rmcv_genELtask_90_08_01',\n", - " '2_rmcv_rt10v_genELtask_29_02_06',\n", - " '2_enseef_enve_genELtask_31_02_08',\n", - " '2_ense_enve_genELtask_42_03_08', '2_ense_enve_genELtask_43_03_09',\n", - " '2_rt10v_rutpt_genELtask_42_03_08',\n", - " '2_rmcv_rutpt_genELtask_40_03_06',\n", - " '2_ense_rutpt_genELtask_60_05_04',\n", - " '2_rmcv_rt10v_genELtask_54_04_09',\n", - " '2_ense_enve_genELtask_52_04_07',\n", - " '2_rmcv_rt10v_genELtask_39_03_05',\n", - " '2_rt10v_rutpt_genELtask_81_07_03',\n", - " '2_enve_rmcv_genELtask_100_09_00',\n", - " '2_rmcv_rutpt_genELtask_45_04_00',\n", - " '2_ense_rutpt_genELtask_64_05_08',\n", - " '2_ense_enve_genELtask_38_03_04',\n", - " '2_rmcv_rt10v_genELtask_55_04_10',\n", - " '2_enve_rutpt_genELtask_55_04_10',\n", - " '2_enve_rt10v_genELtask_86_07_08',\n", - " '2_ense_enseef_genELtask_36_03_02',\n", - " '2_ense_enve_genELtask_29_02_06', '2_ense_enve_genELtask_86_07_08',\n", - " '2_ense_rutpt_genELtask_88_07_10',\n", - " '2_ense_enseef_genELtask_83_07_05',\n", - " '2_ense_enseef_genELtask_25_02_02',\n", - " '2_rmcv_rt10v_genELtask_38_03_04',\n", - " '2_ense_rutpt_genELtask_59_05_03',\n", - " '2_enve_rutpt_genELtask_81_07_03',\n", - " '2_enve_rutpt_genELtask_60_05_04',\n", - " '2_enve_rt10v_genELtask_60_05_04',\n", - " '2_rmcv_rutpt_genELtask_11_00_10',\n", - " '2_rmcv_rutpt_genELtask_26_02_03',\n", - " '2_enseef_rmcv_genELtask_25_02_02',\n", - " '2_enself_rt10v_genELtask_7_00_06',\n", - " '2_rmcv_rt10v_genELtask_2_00_01',\n", - " '2_enseef_rmcv_genELtask_37_03_03',\n", - " '2_ense_rt10v_genELtask_6_00_05',\n", - " '2_rmcv_rutpt_genELtask_14_01_02',\n", - " '2_enve_rmcv_genELtask_40_03_06',\n", - " '2_rmcv_rt10v_genELtask_20_01_08',\n", - " '2_ense_rmcv_genELtask_46_04_01', '2_ense_rmcv_genELtask_18_01_06',\n", - " '2_enseef_rutpt_genELtask_33_02_10',\n", - " '2_ense_enseef_genELtask_70_06_03',\n", - " '2_enseef_enself_genELtask_48_04_03',\n", - " '2_rt10v_rutpt_genELtask_102_09_02',\n", - " '2_ense_rutpt_genELtask_77_06_10',\n", - " '2_enself_rutpt_genELtask_4_00_03',\n", - " '2_ense_rutpt_genELtask_39_03_05',\n", - " '2_enseef_enve_genELtask_21_01_09',\n", - " '2_rt10v_rutpt_genELtask_38_03_04',\n", - " '2_ense_enve_genELtask_30_02_07',\n", - " '2_enve_rutpt_genELtask_99_08_10',\n", - " '2_ense_enve_genELtask_40_03_06',\n", - " '2_enself_enve_genELtask_6_00_05',\n", - " '2_enself_rutpt_genELtask_2_00_01',\n", - " '2_enself_enve_genELtask_1_00_00',\n", - " '2_enve_rmcv_genELtask_104_09_04',\n", - " '2_rt10v_rutpt_genELtask_101_09_01',\n", - " '2_enve_rt10v_genELtask_91_08_02',\n", - " '2_ense_enself_genELtask_81_07_03',\n", - " '2_ense_rutpt_genELtask_51_04_06',\n", - " '2_enve_rt10v_genELtask_75_06_08',\n", - " '2_enself_rmcv_genELtask_34_03_00',\n", - " '2_enseef_rt10v_genELtask_23_02_00',\n", - " '2_enseef_enve_genELtask_17_01_05',\n", - " '2_ense_rutpt_genELtask_43_03_09',\n", - " '2_ense_enseef_genELtask_48_04_03',\n", - " '2_enve_rt10v_genELtask_46_04_01',\n", - " '2_enve_rmcv_genELtask_92_08_03', '2_ense_enve_genELtask_1_00_00',\n", - " '2_ense_rutpt_genELtask_66_05_10',\n", - " '2_enseef_enve_genELtask_16_01_04',\n", - " '2_enve_rmcv_genELtask_58_05_02',\n", - " '2_rt10v_rutpt_genELtask_90_08_01',\n", - " '2_enself_enve_genELtask_29_02_06',\n", - " '2_ense_rutpt_genELtask_52_04_07',\n", - " '2_rt10v_rutpt_genELtask_79_07_01',\n", - " '2_ense_rutpt_genELtask_55_04_10',\n", - " '2_enve_rutpt_genELtask_38_03_04',\n", - " '2_enself_enve_genELtask_31_02_08',\n", - " '2_enself_rutpt_genELtask_55_04_10',\n", - " '2_rmcv_rutpt_genELtask_35_03_01',\n", - " '2_enseef_rt10v_genELtask_46_04_01',\n", - " '2_enve_rutpt_genELtask_57_05_01',\n", - " '2_rmcv_rutpt_genELtask_57_05_01',\n", - " '2_ense_enself_genELtask_68_06_01',\n", - " '2_ense_rt10v_genELtask_58_05_02',\n", - " '2_enve_rt10v_genELtask_95_08_06',\n", - " '2_enseef_rt10v_genELtask_47_04_02',\n", - " '2_ense_rt10v_genELtask_79_07_01',\n", - " '2_ense_rt10v_genELtask_50_04_05',\n", - " '2_ense_rutpt_genELtask_71_06_04',\n", - " '2_ense_enself_genELtask_36_03_02',\n", - " '2_enseef_enself_genELtask_59_05_03',\n", - " '2_enseef_enve_genELtask_2_00_01',\n", - " '2_ense_rmcv_genELtask_57_05_01',\n", - " '2_enself_rutpt_genELtask_21_01_09',\n", - " '2_enself_rutpt_genELtask_1_00_00',\n", - " '2_enseef_rutpt_genELtask_44_03_10',\n", - " '2_enseef_enself_genELtask_36_03_02',\n", - " '2_enve_rt10v_genELtask_97_08_08',\n", - " '2_ense_rmcv_genELtask_78_07_00',\n", - " '2_ense_enseef_genELtask_69_06_02',\n", - " '2_rt10v_rutpt_genELtask_68_06_01',\n", - " '2_ense_enve_genELtask_62_05_06',\n", - " '2_ense_enseef_genELtask_13_01_01',\n", - " '2_ense_enseef_genELtask_35_03_01',\n", - " '2_enself_enve_genELtask_3_00_02',\n", - " '2_ense_rmcv_genELtask_58_05_02', '2_enve_rmcv_genELtask_78_07_00',\n", - " '2_ense_enve_genELtask_13_01_01',\n", - " '2_enve_rt10v_genELtask_82_07_04',\n", - " '2_ense_enve_genELtask_48_04_03',\n", - " '2_enself_rmcv_genELtask_3_00_02',\n", - " '2_rt10v_rutpt_genELtask_52_04_07',\n", - " '2_rt10v_rutpt_genELtask_61_05_05',\n", - " '2_enseef_enself_genELtask_49_04_04',\n", - " '2_enseef_enve_genELtask_1_00_00',\n", - " '2_enve_rt10v_genELtask_87_07_09',\n", - " '2_enself_rt10v_genELtask_5_00_04',\n", - " '2_enself_rutpt_genELtask_15_01_03',\n", - " '2_ense_rt10v_genELtask_61_05_05',\n", - " '2_enve_rt10v_genELtask_84_07_06',\n", - " '2_enve_rutpt_genELtask_91_08_02',\n", - " '2_enve_rt10v_genELtask_85_07_07',\n", - " '2_enseef_enself_genELtask_24_02_01',\n", - " '2_enve_rutpt_genELtask_66_05_10',\n", - " '2_enve_rt10v_genELtask_56_05_00',\n", - " '2_enseef_rutpt_genELtask_13_01_01',\n", - " '2_enseef_rt10v_genELtask_29_02_06',\n", - " '2_enve_rt10v_genELtask_26_02_03',\n", - " '2_ense_rutpt_genELtask_24_02_01',\n", - " '2_enve_rutpt_genELtask_1_00_00',\n", - " '2_enve_rutpt_genELtask_82_07_04',\n", - " '2_enve_rt10v_genELtask_102_09_02',\n", - " '2_enself_rutpt_genELtask_42_03_08',\n", - " '2_ense_rmcv_genELtask_15_01_03', '2_ense_enve_genELtask_18_01_06',\n", - " '2_enve_rmcv_genELtask_81_07_03',\n", - " '2_enve_rt10v_genELtask_83_07_05',\n", - " '2_ense_enve_genELtask_53_04_08',\n", - " '2_enseef_rmcv_genELtask_45_04_00',\n", - " '2_enseef_rutpt_genELtask_27_02_04',\n", - " '2_enve_rt10v_genELtask_48_04_03',\n", - " '2_ense_rutpt_genELtask_63_05_07',\n", - " '2_ense_rmcv_genELtask_17_01_05',\n", - " '2_rt10v_rutpt_genELtask_34_03_00',\n", - " '2_ense_enve_genELtask_16_01_04', '2_ense_enve_genELtask_51_04_06',\n", - " '2_enve_rutpt_genELtask_104_09_04',\n", - " '2_enseef_rmcv_genELtask_14_01_02',\n", - " '2_enseef_rutpt_genELtask_36_03_02',\n", - " '2_enself_rmcv_genELtask_45_04_00',\n", - " '2_rmcv_rt10v_genELtask_15_01_03',\n", - " '2_ense_rmcv_genELtask_35_03_01',\n", - " '2_enseef_enve_genELtask_27_02_04',\n", - " '2_ense_enve_genELtask_3_00_02', '2_ense_rmcv_genELtask_47_04_02',\n", - " '2_enseef_rutpt_genELtask_15_01_03',\n", - " '2_ense_enself_genELtask_25_02_02',\n", - " '2_enseef_rt10v_genELtask_43_03_09',\n", - " '2_enseef_enve_genELtask_18_01_06',\n", - " '2_enve_rutpt_genELtask_90_08_01',\n", - " '2_ense_rt10v_genELtask_41_03_07',\n", - " '2_ense_enve_genELtask_85_07_07',\n", - " '2_enve_rutpt_genELtask_63_05_07',\n", - " '2_enself_rutpt_genELtask_6_00_05',\n", - " '2_enseef_rutpt_genELtask_30_02_07',\n", - " '2_enseef_rmcv_genELtask_36_03_02',\n", - " '2_ense_enself_genELtask_1_00_00',\n", - " '2_rt10v_rutpt_genELtask_36_03_02',\n", - " '2_enself_rutpt_genELtask_16_01_04',\n", - " '2_enself_rt10v_genELtask_13_01_01',\n", - " '2_ense_rmcv_genELtask_36_03_02',\n", - " '2_enself_rmcv_genELtask_13_01_01',\n", - " '2_rt10v_rutpt_genELtask_46_04_01',\n", - " '2_enseef_enve_genELtask_53_04_08',\n", - " '2_ense_enve_genELtask_64_05_08',\n", - " '2_enself_rt10v_genELtask_6_00_05',\n", - " '2_enve_rt10v_genELtask_88_07_10',\n", - " '2_ense_rutpt_genELtask_61_05_05',\n", - " '2_enseef_rutpt_genELtask_37_03_03',\n", - " '2_ense_rmcv_genELtask_26_02_03',\n", - " '2_enself_enve_genELtask_32_02_09',\n", - " '2_rmcv_rutpt_genELtask_22_01_10',\n", - " '2_enseef_enve_genELtask_15_01_03',\n", - " '2_enve_rutpt_genELtask_98_08_09',\n", - " '2_ense_enself_genELtask_35_03_01',\n", - " '2_ense_rt10v_genELtask_25_02_02',\n", - " '2_rt10v_rutpt_genELtask_80_07_02',\n", - " '2_rt10v_rutpt_genELtask_92_08_03',\n", - " '2_enve_rt10v_genELtask_23_02_00',\n", - " '2_enself_rt10v_genELtask_8_00_07',\n", - " '2_enseef_enve_genELtask_19_01_07',\n", - " '2_ense_rt10v_genELtask_51_04_06',\n", - " '2_enseef_rt10v_genELtask_11_00_10',\n", - " '2_rmcv_rt10v_genELtask_67_06_00',\n", - " '2_ense_rutpt_genELtask_36_03_02',\n", - " '2_enve_rt10v_genELtask_79_07_01',\n", - " '2_enself_rmcv_genELtask_25_02_02'], dtype=object)" - ] - }, - "execution_count": 106, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "## MERGE FEATURES AND METRICS\n", - "fd_pdm = pd.merge(both_df, both_pd, on=['log', 'source'], how='inner').reset_index(drop=True)#.reindex(both_df.index)\n", - "\n", - "## DROP DUPLICATES\n", - "fd_pdm = fd_pdm.reset_index(drop=True)\n", - "fd_pdm = fd_pdm.T.drop_duplicates().T\n", - "print(fd_pdm.shape)\n", - "fd_pdm['log'].unique()" - ] - }, - { - "cell_type": "code", - "execution_count": 107, - "id": "0d5d55a1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Imputed dataset: (449, 24)\n", - "17\n", - "No nan's dataset: (295, 24)\n", - "14\n" - ] - } - ], - "source": [ - "### INSTANCE SELECTION: NULLS OR IMPUTATION?\n", - "import numpy as np\n", - "from sklearn.impute import SimpleImputer\n", - "\n", - "num_cols = fd_pdm.convert_dtypes().select_dtypes(exclude=['string']).columns\n", - "str_cols = fd_pdm.convert_dtypes().select_dtypes(include=['string']).columns\n", - "\n", - "imputer = SimpleImputer(missing_values=np.nan, strategy='mean')\n", - "imputer.fit(fd_pdm.drop(str_cols, axis=1))\n", - "imp_df = imputer.transform(fd_pdm.drop(str_cols, axis=1))\n", - "imp_df = pd.DataFrame(imp_df, columns=num_cols)\n", - "imp_df['source'] = fd_pdm['source']\n", - "imp_df['log'] = fd_pdm['log']\n", - "print(\"Imputed dataset:\" ,imp_df.shape)\n", - "print(len(imp_df[imp_df['source']==DATA_SOURCE]['log']))\n", - "\n", - "ft_pdm_no_nans = fd_pdm.copy()\n", - "ft_pdm_no_nans = ft_pdm_no_nans.dropna()\n", - "ft_pdm_no_nans['source'] = fd_pdm['source']\n", - "ft_pdm_no_nans['log'] = fd_pdm['log']\n", - "print(\"No nan's dataset:\" ,ft_pdm_no_nans.shape)\n", - "print(len(ft_pdm_no_nans[ft_pdm_no_nans['source']==DATA_SOURCE]['log']))" - ] - }, - { - "cell_type": "code", - "execution_count": 108, - "id": "eb40e909", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "if IMPUTE:\n", - " benchmarked_ft = imp_df[both_df.columns]\n", - " benchmarked_pd = imp_df[both_pd.columns]\n", - "else:\n", - " benchmarked_ft = ft_pdm_no_nans[both_df.columns]\n", - " benchmarked_pd = ft_pdm_no_nans[both_pd.columns]\n", - "\n", - "real_log_names = benchmarked_ft[benchmarked_ft['source']=='Real']['log'].unique()\n", - "gen_log_names = benchmarked_ft[benchmarked_ft['source']=='Generated']['log'].unique()" - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "id": "83549f71", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Feature similarity: (13, 282)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "\n", - "ft_similarity = cosine_similarity(benchmarked_ft.drop(str_cols, axis=1))\n", - "ft_similarity = pd.DataFrame(ft_similarity, columns=benchmarked_ft['log'], index=benchmarked_ft['log'])#.sort_values(by='BPI_Challenge_2013_closed_problems')\n", - "ft_similarity = ft_similarity.loc[ft_similarity.columns[len(real_log_names)-1:],ft_similarity.columns[:len(real_log_names)-1]].copy()\n", - "ft_similarity = ft_similarity.sort_values(by=ft_similarity.columns[0], ascending=False).transpose()\n", - "\n", - "#with_pcs.loc[:,~with_pcs.columns.duplicated()].copy()\n", - "print(\"Feature similarity:\", ft_similarity.shape)\n", - "#plt.imshow(ft_similarity, cmap='viridis', interpolation='nearest')\n", - "sns.heatmap(ft_similarity.astype(np.float16), cmap=\"viridis\")\n", - "ax = plt.gca()\n", - "ax.set_title(\"Feature similarity between BPICs and GenED\")\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "id": "296941ec", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Metrics similarity: (13, 282)\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pdm_similarity = cosine_similarity(benchmarked_pd.drop(str_cols, axis=1))\n", - "pdm_similarity = pd.DataFrame(pdm_similarity, columns=benchmarked_pd['log'], index=benchmarked_pd['log'])#.sort_values(by='BPI_Challenge_2013_closed_problems')\n", - "pdm_similarity = pdm_similarity.loc[pdm_similarity.columns[len(real_log_names)-1:],pdm_similarity.columns[:len(real_log_names)-1]].copy()\n", - "pdm_similarity = pdm_similarity.transpose()[ft_similarity.columns]#.sort_values(by=ft_similarity.columns[0], ascending=False)\n", - "\n", - "print(\"Metrics similarity:\", pdm_similarity.shape)\n", - "#plt.imshow(pdm_similarity, cmap='viridis', interpolation='nearest')\n", - "sns.heatmap(pdm_similarity.astype(np.float16), cmap=\"viridis\", vmin=0.6)\n", - "ax = plt.gca()\n", - "ax.set_title(\"Performance metrics similarity between BPICs and GenED\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "15811602", - "metadata": {}, - "source": [ - "## Statistical test: Is there a statistical significant relation between feature similarity and performance metrics?" - ] - }, - { - "cell_type": "code", - "execution_count": 111, - "id": "b949efcd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "kendalltau: stat=0.061, p=0.000\n", - "Probably dependent\n" - ] - } - ], - "source": [ - "## STATISTICAL TEST ON COSINE SIMILARITIES\n", - "from scipy.stats import pearsonr\n", - "from scipy.stats import kendalltau\n", - "\n", - "data1 = ft_similarity.to_numpy().flatten()\n", - "data2 = pdm_similarity.to_numpy().flatten()\n", - "\n", - "stat, p = eval(f\"{TEST}(data1, data2)\")\n", - "print(f\"{TEST}:\",'stat=%.3f, p=%.3f' % (stat, p))\n", - "if p > 0.05:\n", - " print('Probably independent')\n", - "else:\n", - " print('Probably dependent')" - ] - }, - { - "cell_type": "code", - "execution_count": 112, - "id": "d702b321", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(295, 9) (295, 17)\n", - "Real (14, 9) (14, 17)\n", - "['rutpt', 'rmcv', 'rt10v', 'enve', 'ense', 'enself', 'enseef']\n", - "Direct kendalltau Real\n", - "Real\n", - "../output/plots/pdm_kendalltau_BaselineED_nanDropped\n" - ] - }, - { - "data": { - "image/png": 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CC1MuippISueEdFbrevUKFixYuf7Rh6Jnr5XTiN10Yw+OPMatn3pToXQMnapmngFFxHOSdiJLWvdfkh7Ib5c0GDiclRlSayIpnRPSWa37zLbLuPH6NVm6dBHz3xFrrhV0775y+/+9Ln5+2VoAzJ8vrryiByePckCqdZ4LrowkbUKWS+ImSf8ATsxt2wIYBxwYEQtT8YqkdBHxl9Ql1z8iSs0JVEhK92BELJHUnywPxoqkdMBaZEnp/tSR39GsGnr1gq8evJjvnrE2Enx75Me8MKcLTzy2BocNW8zFV6wckPCtY3o6+NSJRhiGXTMBCBgAjJW0nCyfxMnAT9O24WRdY7/J8sbxekQc5KR0Zm1z4FeWcOBXlqxStvU2iz+x3/hfLvhEmdWmWuxSK5XzAZWXv0yrKE9G2lA61IQ55tETS77f/HK362qq2VRLLSAzM2sjPwOqQU5KZ2arg1ocVl2qhgtATkpnZquDRngG1HAByKyR+VmLFTRCC6j+Q6iZ2WpoOSp5aQtJQ9KUZ3Mknd3E9pMkzUhTo/0pP2G0pO+n42ZLOrC1a7kFZGZWhyrRApLUleydy/2BecA0SZMi4pncbr+KiKvS/gcDFwFDUiA6Atge2AT4vaT+EbGsueu5BWRmVocqNBfcIGBORMyNiMXARGBofoeIeD+3ug4rXz8ZCkyMiEUR8SIwJ52vWXUVgCRtLOlRSU8UZrNu43E/lHRWJetmZtaZKhSA+gCv5tbnpbJVSBop6QXgJ8DoUo7Nq6sARDYdzoyI+HxE/LHalTEzq5al0aXkJT95clpGtOfaETEuIrYGvkc2EXS71PQzIEnHAmeRNfFeAXYE1kqZTb8A7AP8GOgKvB0RX27hdNtJmgJsDlwSEZela3yTLIJ3J5sN+5SIWCZpQUT0TPscBnwtIoaX/7c0Mytde54BFU2e3JTXgM1y65umsuZMBK5s57G12wKStD1ZZP1SROwIHAecC9ya8gL1BK4FDk3bD2/llJ8FDiTrkzxPUjdJ2wLDgD3SOZcBR1fg1zEzK6sKdcFNA/pJ2lJSd7JBBZPyO0jKp6v5KvB8+jwJOEJSj5RTrR/w15YuVsstoC8Bt0XE2wARMT9NRFqwO/BwethFRMxv5Xy/jYhFwCJJbwL/TNaltzPZSA/IZr1+s5RKpibsCICrr76aESPa1aI1MytJJUbBRcRSSaPIsgR0BcZHxCxJY4DpETEJGJXS4ywB3iVrHJD2+zXwDLAUGNnSCDio7QBUbvk55gv5gATcEBHfb2L//ER/TeYCAucDMrPqqNSLqBFxD3BPUdm5uc+ntXDs+bSemXqFmu2CAx4EDpe0IYCkDYq2TwX2LqTPbmJ7WzwAHCbpnwrnSLmHAP4uaVtJXYCvt+s3MDOrkAiVvNSamm0Bpebc+cBDkpaR5eOZktv+Vur+ujMFiTfJXp4q5RrPSDoH+F06xxJgJFkyurOBu8nyA00ne+ZkZlYTGmE2bOcDKi9/mWbWVh2KIHv+/rsl32/+NPgnNRW1arYFZGZmzavFLrVSNVQAknQ8UPyA7BGnaDCzRtMIs2E3VABKSeeceM7MGp5bQGZmVhVuAZmZWVU0wvgxByAzszrUCMOwHYDMzOqQnwGZmVlVNMIzoE6dikfSaEnPSnq3kGtc0iH5nOKdTdKYNLEekqakVA9mZjUtovSl1nR2C+gUYHBEzMuVHUI25c0zTR5RYflJ9szM6kUjdMF1WgtI0lXAVsC9ks6QdIWkLwIHA2MlPSlp69QKuVDSXyU9V0i9LamrpLGSpkl6WtK3U3lvSQ+n42dK2ivtOyGtz5B0Rgv1mpASzhWXL5B0saRZkh6QtHFlvhkzs9I1wmSknRaAIuIk4HVgP7IcEkTEn8mSGH0nIgZGxAtp9zUiYhBwOnBeKjsBeC8idgV2Bf4tzYR9FDA5JZTbEXgSGAj0iYgdImIA7Xs5dR2y/BfbAw/l6mFmVnUVSkjXqWo1HcOd6edjQN/0+QDgWElPkqXO3pAs49404HhJPwQGRMQHwFxgK0mXSxoCvN+OOiwHbk2fbwL2bGqnfI71a65pKdOtmVn5+BlQ5RSSxxUSx0E2c+ypETG5eGdJe5Olhp0g6aKIuFHSjmQpuE8CvgF8q4N1avKfzwnpzKwaarFLrVS10AL6AOjVhv0mAydL6gYgqb+kdVICub9HxLXAdcBOkjYCukTEHcA5wE7tqFcXoPBs6CjgT+04h5lZRTTCM6BaaAFNBK6VNJqVN/ymXEfWHfe4JJElijsE2Bf4jqQlwALgWKAPcH1KMgfQVMrt1nwIDEoJ694EhrXjHGZmFdEI3S1OSNcMSQsiotQsqP4yzaytOtQk6X/Hj0q+3zx36P+rqWZQLbSAzMysVA3w524tPAPqFJLGpXeF8svxze3fjtaPmVmnqdQzIElDJM2WNKcwY03R9jMlPZPex3wgPYcvbFuWu79Oau1aq00LyFlRzayRVOLpiaSuwDhgf2AeME3SpIjIz1TzBLBLRHwk6WTgJ6x8Rr4wvZPZJqtNC8jMrJFUqAU0CJgTEXMjYjHZILGhq143/hARH6XVqcCm7f0dHIDMzOpRqOQl/+J8WkYUnbUP8GpufV4qa84JwL259TXTeadKOqS1X2G16YIzM2sk7emCK3pxvkMkfRPYBdgnV7xFRLwmaSvgQUkzclOsfYJbQGZm9SjasbTuNWCz3PqmqWwVKYXNfwAHR0Rh5hoi4rX0cy4wBfh8SxdzADIzq0MVegY0DegnaUtJ3YEjyCaMXkHS54GryYLPm7ny9SX1SJ83AvaglTQ7NReAJO0i6bIWtm8i6fYyX/MeSeulzwvKeW4zs4qoQAsoIpYCo8imPnsW+HVEzEqJOw9Ou40FegK3FQ233haYLukp4A/ABUWj5z6h4jMhSOoaEcsqepEyaucMCAUN8GqYmXWSDs1K0PeXF5R8v3npmLNraiaEDrWAJPWV9DdJN6dU27dLWlvSSymp3OPA4ZIOkPQXSY9Luk1Sz3T8rpL+LOmplICul6R9Jd2dtu+Te6npibS9r6SZafuakq5PSeeekLRfKh8u6U5J90l6XtJPWvk9XkpNxnzZvsoS3f02vZR1VW5uOTOz6qrMM6BOVY4b6meAn0fEtmR5d05J5e9ExE7A78lmpB6c1qcDZ6b+xVuB0yJiR2AwsLDo3GcBI9OLTXs1sX0kECnp3JHADZLWTNsGkr0cNQAYJmkzSjcIOBXYDtga+NfiHZwPyMyqQ+1Yaks5hmG/GhGPpM83AaPT50Iyt93JbuCPZJNY0x34C1ngeiMipgFExPsAaZ+CR4CLJN0M3BkR84q27wlcno7/m6SXgf5p2wMR8V465zPAFqw6vr0t/ppGcyDplnS9VZ4/OR+QmVVFA9xtyhGAir+GwvqH6aeA+yPiyPxOkga0euKICyT9FjiILIAdCHzcxnotyn3OJ7YrRXO/m5lZdS2vvRZNqcrRBbe5pC+kz00lbpsK7CFpGwBlSeT6A7OB3pJ2TeW9JK0SJCRtHREzIuJCsuGBny069x+Bo9O+/YHN03nLZVAajtiFrDvPSenMrCY0QkrucgSg2cBISc8C6wNX5jdGxFvAcOAWSU+Tdb99Ns0zNAy4PA3bux9Yk1WdLmlmOm4Jq075APBzoIukGWRdfsPzL0WVwTTgCrLhiC8Cd5Xx3GZm7dcAgxA6NAxbUl/g7ojYoWw1qhGS9gXOioivlXBYDf4Tm1mN6lAf2hbXjS35fvPyid+pqX47zwVnZlaH1AB/7nYoAEXES0DdtH4kPQr0KCo+JiJmFO8bEVPI5jIyM6s9q3sAqjcRsVu162BmVhZtzHBay1arAGRm1jDcAjIzs6pwADIzs6pwADIzs6pogGdAVZvdWdLoNIP2zdWqQ6rHmJTdD0lTJO1SzfqYmbWFovSl1lSzBXQK2QzZ88p5UklrpKRKbRIR55bz+mZmnaIGA0qpqtICknQVsBVwr6TzinP+pH2+l/L8PCXpglQ2UNJUSU9LukvS+ql8iqRLJE0HTpO0s6SHJD0mabKk3i3UZYKkw5ooXyDpYkmzJD0gaeOKfBlmZqupqgSgiDgJeB3YD9iFopw/kr4CDAV2S7mCCgnlbgS+FxGfA2YA5+VO2z0idgEuI0vRcFhE7AyMB85vRzXXAaZHxPbAQ0XXMjOrqkbogquFDJ+FnD+jgfVS99lg4PqI+AggIuZL+lTa/lA67gZg79x5CvmHPkM2O8P9kp4kS4a3aTvqtTx3zpvIcgF9ghPSmVlVhEpfakzVR8E1k/OnPfL5h2ZFxBda2rkdmvz7wQnpzKwqGuBuU/UWUDM5f+4Hjpe0dtpng5Td9F1Je6VDjyHrGis2G9i4kKNIUjdJ27ejal2AwrOhpvIcmZlVTwOkY6h6AKKJnD8RcR8wCZieutHOSvseB4xN+w4ExhSfLOUZOgy4MOUZehL4Yjvq9SFZQrqZwJeaupaZWbVU6hmQpCGSZkuaI+nsJrafKemZNBjsAUlb5LYdJ+n5tBzX+u9Qi2nyaoCkBRHRs8TD/GWaWVt16KHM1j+7qOT7zQv/fmaL15TUFXgO2B+YR9YrdWREPJPbZz/g0Yj4SNLJwL4RMUzSBsB0soFlATwG7BwR7zZ3vVpoAZmZWakq0wU3CJgTEXNTb9JEshHJKy8b8YfCADFgKisHeR0I3B8R81PQuR8Y0tLFVpsAJGlc7n2jwnJ8c/u3o/VjZtZp2tMFlx+1m5YRRaftA7yaW5+XyppzAnBvO4+t/ii4zhIRI6tdBzOzsmnHsOqiUbsdIumbZN1t+7T3HKtNC8jMrKFUpgvuNWCz3PqmqWwVaf7M/wAOjohFpRyb5wBkZlaHKjQKbhrQT9KWkroDR5CNSF55XenzwNVkwefN3KbJwAGS1k/TpB2Qypq12nTBmZk1lAqMuY2IpZJGkQWOrsD4iJglaQzZ1GSTgLFAT+A2SQCvRMTBacaaH5EFMYAxETG/pes5AJmZ1aFKze0WEfcA9xSVnZv7PLiFY8eTzb/ZJg5AZmb1qAHeOqzLZ0CSrpO0XZnO5YR0ZlZ/GmAqnrpsAUXEiWU8lxPSmVndqcX0CqWq+RaQpHUk/TYlppspaVihpSLp4NxLpbMlvZiOcUI6M7MaV/MBiGwqh9cjYseI2AG4r7AhIiZFxMCUzO4p4KeSuuGEdGbW6BqgC64eAtAMYH9JF0raK6VlWIWk7wILI2IcTkhnZquBRsiIWvPPgCLiOUk7kSWs+y9JD+S3pwEEh7MyO6oT0plZ42uAu03Nt4AkbQJ8FBE3kb0AtVNu2xbAOODwiFiYip2QzswaXwN0wdV8CwgYQJaEbjlZwrqTgZ+mbcOBDYHfpDdyX4+Ig9KggsskfYrsd7wEmFXidQsJ6c4B3gSGdfD3MDMrm1rsUiuVE9I1wwnpzKzCOpSQbtv/d3HJ95tnf3RGh65ZbvXQAjIzsyKN0AJabQKQpHHAHkXFl0bE9U3t74R0ZlbTlle7Ah232gQgJ6Qzs0biFpCZmVWHA5CZmVWFA5CZmVWDu+DMzKw6HIDMzKwaGqEFVPNT8bSVpI0lPSrpCUl7lXDcwZLOTp9/KOmsytXSzKxMPBVPTfkyMKPUZHURMQmYVJkqmZlVSA0GlFLVbQCSdCxwFtk/wyvAjsBaKaX2F4B9gB8DXYG3I+LLzZxnOLBLRIwqKp9ClmNoH7Lv6VsR8deK/DJmZiWqqTl12qkuu+DS7NbnAF+KiB2B44BzgVtTcrqewLXAoWn74e281NrpfKeQJbZrqi7OB2Rmna9CXXCShqQM03MKjyeKtu8t6XFJS4uzSUtalstS3WrPUr22gL4E3BYRbwNExPw0G3bB7sDDEfFiYXs7r3NLOv5hSetKWi8i/pHfwfmAzKwaKjEIQVJXshQ3+wPzgGmSJkXEM7ndXiHLRNDU8/KF6Y/2NqnXANRZiv+JHWDMrDZU5m40CJgTEXMBJE0EhgIrAlBEvJS2dXg2urrsggMeBA6XtCGApA2Ktk8F9pa0ZTPb22pYOn5P4L2m0oGbmVVFO7rg8o8M0jKi6Kx9gFdz6/NSWVutmc47VdIhre1cly2giJgl6XzgIUnLgCeAKbntb6Uv9k5JXcgSyu3fjkt9LOkJoBvwrY7X3MysPNrTBVf0yKAStoiI1yRtBTwoaUZEvNDcznUZgAAi4gbghqLiCbnt9wL3tuE8EwrHRcQPizbfFBGnt7+WZmYVUpkuuNeAzXLrm6ayNomI19LPuWkk8eeBZgNQvXbBmZmt1hSlL20wDegnaUtJ3YEjaON7kpLWl9Qjfd6ILP/aMy0dU7ctoFJJOh44raj4kebyBEXEvhWvlJlZe1WgBRQRSyWNAiaTvUM5Pj3yGANMj4hJknYF7gLWB/5F0n9GxPbAtsDVaXBCF+CCotFzn6AID+wqI3+ZZtZWHXqXdKeTLy75fvP4lWfU1Purq00LyMysoTTAn7sOQGZm9cgByMzMqqER0jE4AJmZ1aMGCEAVHYYtabSkZyW9m8u5c4ik7Sp53VbqNEbS4BKPGStplqSxlaqXmVkpFFHyUmsq3QI6BRgcEfNyZYcAd9PK+PBKiYhz23HYCGCDiFhW7vqYmbVL7cWTklWsBSTpKmAr4F5JZ0i6QtIXgYOBsWm67q0lTZF0oaS/SnqukM1UUtfU8pgm6WlJ307lvSU9nI6fKWmvtO+EtD5D0hkt1GtCYQpxSS9J+u90rumSdpI0WdILkk5K+0wiS+/wmKRhlfq+zMxKUaEXUTtVxVpAEXGSpCHAfsDXUtmf0w397oi4HSClUVgjIgZJOgg4DxgMnEA2Aeiu6e3aRyT9DvhXYHJEnJ+mDl8bGAj0iYgd0jnXK6Gqr0TEQEkXk03JswewJjATuCoiDpa0oJQpxs3MKq4GA0qpamUqnjvTz8eAvunzAcCxkp4EHgU2BPqRTRVxvKQfAgMi4gNgLrCVpMtT0Hu/hGsXppmYATwaER9ExFvAorYEMiekM7NqcAuofBaln8tYWScBp0bE5OKdJe0NfBWYIOmiiLhR0o7AgcBJwDdo++zVhWsvz30urLf6/TghnZlVRQPcbaoRgD4AerVhv8nAyZIejIglkvqTzcq6ETAvIq5NXXM7SboHWBwRd0iaDdxUsdqbmdWAWmzRlKoaAWgicK2k0cBhLex3HVl33OPKHhS9RTaCbl/gO5KWAAuAY8kSJl2fcv8AfL8iNTczqxUNEIA8GWl5+cs0s7bq0MSgu3/zopLvN1NvOtOTkZqZWQc1QOOhYQOQpHFkQ6rzLo2I66tRHzOzcvIzoBrWXKI5M7OG4ABkZmbVoOXVrkHHOQCZmdUjt4DMzKwa/AzIzMyqQsvrPwLVylxwZmZWimjH0gaShkiaLWlOIY9b0fa9JT0uaWkhs0Bu23GSnk/Lca1dq+oBSNIuki5rYfsmkm4v8zXvKWXGbEk9JP0+pW1wSgYzq7pKTEaaMgyMA74CbAcc2UQC0VeA4cCvio7dgCybwW7AIOA8Seu3dL2yd8FJ6lpK4raImA5Mb2H767Q8ZU/JIuKgEg/5fDpuYDnrYWbWbpV5EXUQMCci5gJImggMJZdANCJeStuKx+EdCNwfEfPT9vuBIcAtzV2spBaQpL6S/ibp5pRq+3ZJa6fEbhdKehw4XNIBkv6Smmm3SeqZjt9V0p8lPZUS0PWStK+ku9P2fVIr40lJT6TtfSXNTNvXlHR9Sjr3hKT9UvlwSXdKui81/X7Syu/xkqSNcr/PBGXJ8G6WNFjSI+k8gyT9E9nkprumem1dyndmZlYJ7WkB5dPHpGVE0Wn7AK/m1uelsrYo+dj2tIA+A5wQEY9IGk+WdhvgnYjYSdJGZPl9BkfEh5K+B5wp6QLgVmBYREyTtC6wsOjcZwEj07l7Ah8XbR8JREQMkPRZ4HdplmzIktJ9niylwmxJl0fEq7RuG+BwsvQN04CjgD3JMrf+ICIOkXQicFZEfK1N35CZWaW1owFUlD6m6trzDOjViHgkfb6J7GYNWXAB2J2s7/CRlEzuOGALssD1RkRMA4iI9yNiadG5HwEuSjNlr9fE9j3TNYmIvwEvA4UA9EBEvBcRH5M1F7do4+/zYkTMiIjlwKx0niBLUNe3tYOdkM7MqqFCCeleAzbLrW+ayipybHtaQMW/RmH9w/RTZP2AR+Z3kjSg1RNHXCDpt8BBZAHsQD7ZCmpOPplcPrFdKcflk9I5IZ2Z1a7KDMOeBvSTtCVZ8DiCrFeoLSYDP84NPDiAVlLjtKcFtLmkL6TPRwF/Kto+FdhD0jYAktZJ3WSzgd6Sdk3lvSStcoOXtHVqjVxI9kV8tujcfwSOTvv2BzZP5zUzW71UYBh26nUaRRZMngV+HRGzJI2RdDCseJY/j+zRxdWSZqVj5wM/Irt3TwPGFAYkNKc9LaDZwMj0/OcZ4Erg1Nwv8Jak4cAtyjKWApwTEc+lIcyXS1qL7PnP4KJzn54GFhS6w+4Feue2/xy4UtIMYCkwPCIWSTWV4sLMrOIqNRNCRNwD3FNUdm7u8zSy7rWmjh0PjG/rtUpKSCepL3B3ROzQ5oNWL+6CM7O26tBfzvsOubDk+82U+75XU3+teyoeM7M6tNrNBZdeQKqb1o+kR4EeRcXHRMSMatTHzKxsVrcAVG8iYrdq18HMrBLklNxmZlYVTkhnZmbV4BaQmZlVR/3HHwcgM7O61AAtoE7LByRpdJpB++bOumYz9RgjqfgF2NaOGStplqSxlaqXmVkpKjQXXKfqzBbQKWQzZM8r50klrdHEpKXNyr/RW4IRwAal5DkyM6sot4DaRtJVwFbAvZLOK875k/b5Xsrz81RK3YCkgZKmSnpa0l2FSe4kTZF0iaTpwGmSdpb0kKTHJE2W1LuFukxQSiOb8gL9d6rLdEk7peNfkHRS2mcS0BN4TM6GamY1QstLX2pNp7SAIuIkSUOA/YDrKcr5I+krZFn3douIj5SldgW4ETg1Ih6SNIYs3evpaVv3iNhFUjfgIWBomoduGHA+WX6ftnglIgZKuhiYAOwBrAnMBK6KiIMlLXA2VDOrKW4BtUtTOX8GA9dHxEeQzaoq6VNp+0PpuBuAvXPnKeQf+gzZ7Az3p/xD59DMRHnNmJR+zgAejYgPIuItYJGk9Vo72PmAzKwqKjAbdmfr9FFwzeT8aY98/qFZEfGFlnZuQT7/T3FuIOcDMrOa1AjvAXV6C6iZnD/3A8dLWjvts0FEvAe8K2mvdOgxZF1txWYDGxdyFEnqJmn7iv8iZmbVFFH6UmOq8R7QJ3L+pJw+A4HpkhaT5aL4AVk676tSYJoLHF98sohYnAYVXJa67dYALknnNjNrTDU4qKBUJeUDslb5yzSztupQbp4Dd/3Pku83k6ed53xAZmbWQQ3QeGjYACRpHNmQ6rxLI+L6atTHzKysHIBqV0SMrHYdzMwqpgGeATVsADIza2SNMAzbAcisjrz1ep9qV6FJG2/yWrWrsPqpUABKs9ZcCnQFrouIC4q29yCbpWZn4B1gWES8JKkv8CzZqzEAUyPipJau5QBkZlaPKhCAJHUFxgH7A/OAaZImRcQzud1OAN6NiG0kHQFcCBTmyXyhlGnLqjEVj5mZdVRlXkQdBMyJiLkRsRiYSDZPZ95QsqnRAG4HviypXcO7HYDMzOrR8tKX/NyVaRlRdNY+wKu59XmprMl90lye7wEbpm1bpiwHD+VmsWlWXQQgSddJ2q5M53JCOlst3HPfGpw0ai1OHrUWs59r+n/1X1zfnWFHr71i/drx3Tn0iLU57d/X7KxqWjspouQlIq6JiF1ySzlnUH4D2DwiPg+cCfxK0rotHVAXz4Ai4sQynssJ6azhvf8B3H5nN64et5C33hY/+vGaXHn5wlX2mT9fvDJv1Z6Trw9dwkFDlvCTn/XozOpae1RmEMJrwGa59U1TWVP7zJO0BvAp4J3IptVZlFUtHpP0AtAfmN7cxWquBSRpHUm/TYnpZkoalhLQ7SLp4Fwyu9mSXkzHOCGdWc6zz3blcwOW0a0bbNI7+OgjWLx41X0m/LIbxxy1ZJWyjTYMutTcXcGatGx56UvrpgH9JG0pqTtwBCtT1hRMIpunE+Aw4MGICEkbp0EMSNoK6Ec2h2ezarEFNAR4PSK+CpAmGD0ZICImkb4MSb8GHkoJ6S7HCenMVnjvfdGr18r1Xj3h/Q/ERhtmfzW/Ok8sXCi22boB3mZcXVWgBRQRSyWNAiaTDcMeHxGzUkLQ6eke/Avgl5LmAPPJghRk+drGSFpC9tTppIiY39L1ajEAzQB+JulC4O6I+GPxAAtJ3wUWRsQ4STuwMiEdZF/aGyVcL5+QrmdEfAB8IGmRpPUi4h8tHZwe4o0AuPrqqxkxoviZnlnnW3fdYMGClesLPoR1e628YY2f0J0Tj1/cxJFWNyr0HlBE3EOWkSBfdm7u88fA4U0cdwdwRynXqrkAFBHPSdqJLGHdf0l6IL89DSA4nJXZUZ2QzqzIdtsu49pfdGfpUnj7HbHWWtC9+8rtr7/RhZ9dmj3neWe+uOSy7pw+2gGpriyv/9tNzQUgSZsA8yPiJkn/AE7MbduC7CWpAyOi8ER1RUK6iPhL6pLrHxHOB2SrrXV7ZQMKRp2+FgJOO3URz8/pwrTpXTnqiCVcPW7lgIRhR6+9IvjccVc3fv/gGrz8ShdO+/c1+e6Zi+jTp/5vdA0p6r/7tOYCEDAAGCtpObCE7PnPT9O24WTjzX+Tuttej4iDnJDO7JO+dtBSvnbQ0lXK+m3zyZvWrTd/tOLzoV9fwqFfX/KJfawGNcBccE5IV17+Mq2iPBdcQ+lQcrivbH56yfebe1+5xAnpzMysgxqg8dCwAcgJ6cysoTkA1S4npDOzhuYAZGadyc9abIXlHgVnZmbV4BaQmZlVhQOQmZlVhWdCMDOzaogGmAmhbideT1N/P5qy77WaeS933MGSzi7xWodLelbSH0qvqZlZBSyP0pcaU88toC8DM0pNVpdP6VCCE4B/i4g/lXicmVll+BlQ55F0LHAW2XQ3rwA7AmtJ2gX4ArAP8GOydAxvR8SXmznPcGCXiBglaQKwEPg88E9kOYSOTed7NCKGSzoX2BP4haRJEfGdyv2WZmZt1ADDsOuiC07S9sA5wJciYkeybHznAremRHE9gWuBQ9P2T+SqaMH6ZAHnDLKW0cXA9sAASQMjYgxZStmjmwo+kkakbKrTr7mmnOnVzcxaEFH6UmPqpQX0JeC2iHgbICLmFyWp2x14OCJeLGwv4dz/m9LJzgD+HhEzACTNAvoCT7Z0sPMBmVk1RAO0gOolAFVShxLSmZlVRQ22aEpVF11wwIPA4ZI2BJC0QdH2qcDekrZsZruZWWPxKLjOERGzJJ0PPCRpGfAEMCW3/S1JI4A7JXUB3gT2r0plzcw6QwO8B+SEdOXlL9PM2qpDyeEO6H5Uyfeb3y3+VU0lpKuXLjgzM8uL5aUvbSBpiKTZkuY09dK+pB6Sbk3bH5XUN7ft+6l8tqQDW7tWXXTBtYek44HTioofcZ4gM2sEUYFnOpK6AuPIHmHMA6al9x+fye12AvBuRGwj6QjgQmCYpO2AI8heY9kE+L2k/hGxrLnrNWwASplPnf3UzBpTZZ4BDQLmRMRcAEkTgaFAPgANBX6YPt8OXKHsvZihwMSIWAS8KGlOOt9fmrtYwwagKilb/6qkEekdo5pTq3VzvUrjepWulup2//LbSr7fpMFaI3JF1xT9Pn2AV3Pr84Ddik6zYp+IWCrpPWDDVD616Ng+LdXHz4Bq14jWd6maWq2b61Ua16t0tVy3VkXENRGxS26pajB1ADIzs4LXgM1y65umsib3kbQG8CngnTYeuwoHIDMzK5gG9JO0paTuZIMKirMHTCKbjxPgMODByN7nmQQckUbJbQn0A/7a0sX8DKh21UQ/czNqtW6uV2lcr9LVct06LD3TGQVMJsssMD5NBDAGmJ7S2fwC+GUaZDCfLEgVJgz4NdmAhaXAyJZGwIFfRDUzsypxF5yZmVWFA5CZmVWFA1ANknRIequ4tf32lfTFzqhTtUn6QdH6eElvSppZVL6BpPslPZ9+rt+5NbXOIKlv/t9e0i2SnpZ0RjXr1RRJoyU9K+nmatel1jgAVYkyzX3/hwCtBiBgX6CsAaiVelVFesv6nKLiCcCQJnY/G3ggIvoBD6R1a2CSPg3sGhGfi4iLq12fJpwC7B8RR1e7IjUnIrx00kKWYXU2cCMwK/v6V2w7jOym+kWykSUvkmVj3Zos9cSlaX0m2fQWfYH/Ixtn/ySwV5nq9WG69gTgOeBmYDDwCPA8MCgd05NsqqMZwNPAocBJwNjceYcDV5ShTi+QzTT+JHBz0T4zi46bDfROn3un9S7AS8B6uf2eB/65A9/ZN8mGmD4JXE02YmgBcD7wFNkb4f9M9o7Ey0CXdNw6ZG+Rd0v/tvcBjwF/BD5bpv/O2lS3tO/h6b+pp8iyCpP2H0s2JPdp4Nu1Vpf8v30qX0gb/j+o5HcDfCdX/p+p7CpgMdn/J2dU8v5Sj0vVK7A6Lel/muXA7ml9QW7bYcCE9HkCcFhu2xTg2vR579z/eD8EzipnvdLnpcAAshv3Y8B4smmGhgK/ScdcCFySO8f6wMZk80gVyu4F9iz3d1W0T3EA+kfuswrrZAH8+PR5N+D3Hfi+tgX+F+iW1n8OHEsWJP8llf0EOCd9/h9gv/R5GHBd+vwA0C9XpwfL8G9Zat1mAH3S5/XSzxG57T2A6cCWtVQXVg1An/jvoAr1OYBsiLbI/r+5G9g77fcSsFFH/20bcfF7QJ3v5YiY2vpun3ALQEQ8LGldSeuVt1pZvdLU6i9GxAwASbPIurRC0gyy/9khaxUdUTg4It5N+8+VtDtZC+OzZC2nDtWpvQenOhfeM7gVOJes1XZEWm+vLwM7k80UDLAWWRLExWQ3HsgCdyEp4q1kgecP6do/l9STrLV7WzoHZDe0jiq1bo8AE9L7G3emsgOAz0k6LK1/iuylwhdrqC7PlViXStfngLQ8kcp7pvKH21HP1YYDUOf7MPc5/xLWmq0cV/zCVrlf4MrXa1Hu8/Lc+nJa/29mIvAN4G/AXZH+BCxDndrq75J6R8QbknqT3WAgm5F3G0kbkz1j+68O1EvADRHx/VUKpbNyv+8yVn5Xk4Afp1TxO5OlmF+HrHU2sAP16HDdIuIkSbsBXwUek7RzOsepETG5VuuSz0FTI/U5EPjviLi6HfVabdXUw+bV0N8lbZse+n89V/4B0Kto32EAkvYE3ouI95rZr7PcD6zIrZQbbXYXWVfdkWTBqFyWSOrWhv3y04QcR9b9RbrB3AVcBDwbEe90oC4PAIdJ+idYMfJui+Z2jogFZM8GLgXujohlEfE+2ZT1h6dzSNKOHahTu+omaeuIeDQizgXeIpvLazJwcuH7ltRf0jp1XpdK12cy8K3UskVSn8J1rHluAVXX2WRN/7fI+pJ7pvKJwLWSRpM9GwL4WNITZA+vv5XK/he4XdJQsr/K/thpNc9aEOPSUNhlwH8Cd0bEu5KeBbaLiBbngSrRNcDTkh6PiKMl3UI2CnAjSfOA8yLiF8AFwK8lnUD28P8buXPcShYIhnekIhHxjKRzgN+lPx6WkAvGzbgVuC3VueBo4Mp0rm5k/+5PdXLdxkrqR/aX/QPp+k+TdbU+nkYgvkXWaqzbulS6PhHxO0nbAn9J3XsLyAY8vNnUiS3jqXjqgKQpZIMNple7LmZm5eIuODMzqwq3gMzMrCrcAjIzs6pwADIzs6pwADIzs6pwADIzs6pwADIzs6r4/5NdWat31FM4AAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "### DIRECT STATISTICAL TEST\n", - "from scipy.stats import spearmanr\n", - "from scipy.stats import kendalltau\n", - "from scipy.stats import pearsonr\n", - "from numpy import isnan\n", - "\n", - "import sys\n", - "import os\n", - "sys.path.append(os.path.dirname(\"../gedi/utils/io_helpers.py\"))\n", - "from io_helpers import get_keys_abbreviation\n", - "\n", - "print(benchmarked_ft.shape, benchmarked_pd.shape)\n", - "\n", - "benchmarked_ft_plot = benchmarked_ft.copy()[benchmarked_ft['source']==DATA_SOURCE]\n", - "benchmarked_pdm_plot = benchmarked_pd.copy()[benchmarked_pd['source']==DATA_SOURCE]\n", - "\n", - "#benchmarked_ft = benchmarked_ft.head(10)\n", - "#benchmarked_pdm = benchmarked_pdm.head(10)\n", - "print(DATA_SOURCE, benchmarked_ft_plot.shape, benchmarked_pdm_plot.shape)\n", - "\n", - "tmp = list(benchmarked_ft_plot.columns[1:-1])\n", - "df_tmp = pd.DataFrame(index=benchmarked_pdm_plot.columns[1:-1], columns=tmp)\n", - "#print(\"Benchmark_pdm:\", benchmarked_pdm.columns[1:-1])\n", - "#print (\"Benchmark_ft:\", tmp)\n", - "\n", - "for feature in benchmarked_ft_plot.columns:\n", - " if feature != 'log' and feature != 'source':\n", - " for metric in benchmarked_pdm_plot.columns:\n", - " if metric != 'log' and metric != 'source':\n", - " #print(feature, benchmarked_pdm.columns[1])\n", - " stat, p = eval(f\"{TEST}(benchmarked_ft_plot[feature], benchmarked_pdm_plot[metric])\") \n", - " #print(feature, metric, p, p <= 0.05)\n", - " df_tmp.loc[metric, feature] = stat*(1.0 if (p <= 0.05) else 0.0)\n", - "\n", - "feature_keys = get_keys_abbreviation(df_tmp.columns).split(\"_\")\n", - "print(feature_keys)\n", - "df_tmp.columns=feature_keys\n", - "print(\"Direct\", TEST, DATA_SOURCE)\n", - "# df_tmp[pd.isnan()]\n", - "\n", - "sns.heatmap(df_tmp.fillna(0), annot=True, cmap=\"viridis\", annot_kws={\"size\": 9})\n", - "ax = plt.gca()\n", - "sns.heatmap(df_tmp.fillna(0), mask=df_tmp.fillna(0)!=0, cmap=\"Greys\", annot=False, cbar=False, ax=ax)\n", - "#ax.set_title(\"P-values of features leading to process discovery metrics\", fontsize=15)\n", - "plt.tight_layout()\n", - "output_path = f\"../output/plots/pdm_{get_output_file_name(TEST, DATA_SOURCE, EXP_BASELINE, IMPUTE)}\"\n", - "print(output_path)\n", - "plt.savefig(output_path, dpi=300)" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "id": "b367b003", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(295, 9) (295, 17)\n", - "Real (14, 9) (14, 17)\n", - "['rutpt', 'rmcv', 'rt10v', 'enve', 'ense', 'enself', 'enseef']\n", - "Similarity kendalltau Real\n", - "Real\n", - "../output/plots/pdmSim_kendalltau_BaselineED_nanDropped\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "### SIMILARITY STATISTICAL TEST\n", - "from scipy.stats import spearmanr\n", - "from scipy.stats import kendalltau\n", - "from numpy import isnan\n", - "\n", - "print(benchmarked_ft.shape, benchmarked_pd.shape)\n", - "\n", - "benchmarked_ft_plot = benchmarked_ft.copy()[benchmarked_ft['source']==DATA_SOURCE]\n", - "benchmarked_pdm_plot = benchmarked_pd.copy()[benchmarked_pd['source']==DATA_SOURCE]\n", - "\n", - "print(DATA_SOURCE, benchmarked_ft_plot.shape, benchmarked_pdm_plot.shape)\n", - "\n", - "tmp = list(benchmarked_ft_plot.columns[1:-1])\n", - "df_tmp = pd.DataFrame(index=benchmarked_pdm_plot.columns[1:-1], columns=tmp)\n", - "#print(\"Benchmark_pdm:\", benchmarked_pdm.columns[1:-1])\n", - "#print (\"Benchmark_ft:\", tmp)\n", - "\n", - "\n", - "for feature in benchmarked_ft_plot.columns:\n", - " if feature != 'log' and feature != 'source':\n", - " for metric in benchmarked_pd.columns:\n", - " if metric != 'log' and metric != 'source':\n", - " #print(feature, benchmarked_pdm.columns[1])\n", - " X = benchmarked_ft_plot[feature].to_numpy()\n", - " ft_sim = (1-np.abs(np.subtract.outer(X,X)/max(X))).flatten()\n", - " #ft_sim = np.nan_to_num(ft_sim)\n", - " \n", - " Y = benchmarked_pdm_plot[metric].to_numpy()\n", - " Y = [y if y!=0 else 1.e-100 for y in Y]\n", - " pdm_sim = (1-np.abs(np.subtract.outer(Y,Y))/Y).flatten()\n", - " #pdm_sim = np.nan_to_num(pdm_sim)\n", - " #print(ft_sim, pdm_sim)\n", - " #print(f\"{TEST}(ft_sim, pdm_sim)\")\n", - " stat, p = eval(f\"{TEST}(ft_sim, pdm_sim)\")\n", - " #print(feature, metric, p, p <= 0.05)\n", - " df_tmp.loc[metric, feature] = stat*(1.0 if (p <= 0.05) else 0)\n", - "\n", - "# df_tmp[pd.isnan()]\n", - "\n", - "feature_keys = get_keys_abbreviation(df_tmp.columns).split(\"_\")\n", - "print(feature_keys)\n", - "df_tmp.columns=feature_keys\n", - "sns.heatmap(df_tmp.fillna(0), annot=True, cmap=\"viridis\", annot_kws={\"size\": 9})\n", - "ax = plt.gca()\n", - "sns.heatmap(df_tmp.fillna(0), mask=df_tmp.fillna(0)!=0, cmap=\"Greys\", annot=True, annot_kws={\"color\":\"white\", \"size\": 9}, cbar=False, ax=ax)\n", - "print(\"Similarity\", TEST, DATA_SOURCE)\n", - "\n", - "#ax.set_title(\"P-values of feature similarity leading to process discovery metrics similarity\", fontsize=15)\n", - "output_path = f\"../output/plots/pdmSim_{get_output_file_name(TEST, DATA_SOURCE, EXP_BASELINE, IMPUTE)}\"\n", - "print(output_path)\n", - "plt.tight_layout()\n", - "plt.savefig(output_path, dpi=300)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "474485e6", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.19" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}