diff --git "a/notebooks/gedi_figs7and8_benchmarking_statisticalTests.ipynb" "b/notebooks/gedi_figs7and8_benchmarking_statisticalTests.ipynb"
--- "a/notebooks/gedi_figs7and8_benchmarking_statisticalTests.ipynb"
+++ "b/notebooks/gedi_figs7and8_benchmarking_statisticalTests.ipynb"
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 1,
    "id": "1768477d",
    "metadata": {},
    "outputs": [],
@@ -10,8 +10,8 @@
     "import pandas as pd\n",
     "from scipy import spatial\n",
     "from sklearn.metrics.pairwise import cosine_similarity\n",
-    "TEST='pearsonr'#'kendalltau', 'pearsonr'\n",
-    "DATA_SOURCE = 'GenED' #'BaselineED', 'GenBaselineED', 'GenED'\n",
+    "TEST='kendalltau'#'kendalltau', 'pearsonr'\n",
+    "DATA_SOURCE = 'BaselineED' #'BaselineED', 'GenBaselineED', 'GenED'\n",
     "IMPUTE = False #If False Nan lines are dropped\n",
     "\n",
     "paper_feat_columns = [\"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",
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 2,
    "id": "d3b7f2d1",
    "metadata": {},
    "outputs": [
@@ -30,8 +30,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "GenED\n",
-      "pearsonr_GenED_nanDropped\n"
+      "BaselineED\n",
+      "kendalltau_BaselineED_nanDropped\n"
      ]
     }
    ],
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 3,
    "id": "6594d6b4",
    "metadata": {},
    "outputs": [],
@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 4,
    "id": "7428d805",
    "metadata": {},
    "outputs": [],
@@ -113,60 +113,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 5,
    "id": "14e72f71",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Path:  ../data/GenED_feat.csv\n",
-      "(467, 8)\n",
-      "['2_ense_enseef_genELtask_13_01_01', '2_ense_enseef_genELtask_1_00_00', '2_ense_enseef_genELtask_24_02_01', '2_ense_enseef_genELtask_25_02_02', '2_ense_enseef_genELtask_35_03_01', '2_ense_enseef_genELtask_36_03_02', '2_ense_enseef_genELtask_47_04_02', '2_ense_enseef_genELtask_48_04_03', '2_ense_enseef_genELtask_58_05_02', '2_ense_enseef_genELtask_59_05_03', '2_ense_enseef_genELtask_60_05_04', '2_ense_enseef_genELtask_69_06_02', '2_ense_enseef_genELtask_70_06_03', '2_ense_enseef_genELtask_71_06_04', '2_ense_enseef_genELtask_82_07_04', '2_ense_enseef_genELtask_83_07_05', '2_ense_enself_genELtask_1_00_00', '2_ense_enself_genELtask_24_02_01', '2_ense_enself_genELtask_25_02_02', '2_ense_enself_genELtask_2_00_01', '2_ense_enself_genELtask_35_03_01', '2_ense_enself_genELtask_36_03_02', '2_ense_enself_genELtask_46_04_01', '2_ense_enself_genELtask_47_04_02', '2_ense_enself_genELtask_58_05_02', '2_ense_enself_genELtask_67_06_00', '2_ense_enself_genELtask_68_06_01', '2_ense_enself_genELtask_70_06_03', '2_ense_enself_genELtask_78_07_00', '2_ense_enself_genELtask_81_07_03', '2_ense_enself_genELtask_82_07_04', '2_ense_enve_genELtask_13_01_01', '2_ense_enve_genELtask_14_01_02', '2_ense_enve_genELtask_16_01_04', '2_ense_enve_genELtask_17_01_05', '2_ense_enve_genELtask_18_01_06', '2_ense_enve_genELtask_1_00_00', '2_ense_enve_genELtask_27_02_04', '2_ense_enve_genELtask_29_02_06', '2_ense_enve_genELtask_2_00_01', '2_ense_enve_genELtask_30_02_07', '2_ense_enve_genELtask_31_02_08', '2_ense_enve_genELtask_37_03_03', '2_ense_enve_genELtask_38_03_04', '2_ense_enve_genELtask_3_00_02', '2_ense_enve_genELtask_40_03_06', '2_ense_enve_genELtask_41_03_07', '2_ense_enve_genELtask_42_03_08', '2_ense_enve_genELtask_43_03_09', '2_ense_enve_genELtask_48_04_03', '2_ense_enve_genELtask_50_04_05', '2_ense_enve_genELtask_51_04_06', '2_ense_enve_genELtask_52_04_07', '2_ense_enve_genELtask_53_04_08', '2_ense_enve_genELtask_61_05_05', '2_ense_enve_genELtask_62_05_06', '2_ense_enve_genELtask_63_05_07', '2_ense_enve_genELtask_64_05_08', '2_ense_enve_genELtask_65_05_09', '2_ense_enve_genELtask_73_06_06', '2_ense_enve_genELtask_74_06_07', '2_ense_enve_genELtask_75_06_08', '2_ense_enve_genELtask_76_06_09', '2_ense_enve_genELtask_85_07_07', '2_ense_enve_genELtask_86_07_08', '2_ense_rmcv_genELtask_15_01_03', '2_ense_rmcv_genELtask_16_01_04', '2_ense_rmcv_genELtask_17_01_05', '2_ense_rmcv_genELtask_18_01_06', '2_ense_rmcv_genELtask_25_02_02', '2_ense_rmcv_genELtask_26_02_03', '2_ense_rmcv_genELtask_35_03_01', '2_ense_rmcv_genELtask_36_03_02', '2_ense_rmcv_genELtask_37_03_03', '2_ense_rmcv_genELtask_46_04_01', '2_ense_rmcv_genELtask_47_04_02', '2_ense_rmcv_genELtask_48_04_03', '2_ense_rmcv_genELtask_57_05_01', '2_ense_rmcv_genELtask_58_05_02', '2_ense_rmcv_genELtask_59_05_03', '2_ense_rmcv_genELtask_67_06_00', '2_ense_rmcv_genELtask_6_00_05', '2_ense_rmcv_genELtask_78_07_00', '2_ense_rmcv_genELtask_7_00_06', '2_ense_rt10v_genELtask_12_01_00', '2_ense_rt10v_genELtask_21_01_09', '2_ense_rt10v_genELtask_22_01_10', '2_ense_rt10v_genELtask_23_02_00', '2_ense_rt10v_genELtask_25_02_02', '2_ense_rt10v_genELtask_31_02_08', '2_ense_rt10v_genELtask_32_02_09', '2_ense_rt10v_genELtask_33_02_10', '2_ense_rt10v_genELtask_36_03_02', '2_ense_rt10v_genELtask_40_03_06', '2_ense_rt10v_genELtask_41_03_07', '2_ense_rt10v_genELtask_42_03_08', '2_ense_rt10v_genELtask_43_03_09', '2_ense_rt10v_genELtask_45_04_00', '2_ense_rt10v_genELtask_47_04_02', '2_ense_rt10v_genELtask_49_04_04', '2_ense_rt10v_genELtask_50_04_05', '2_ense_rt10v_genELtask_51_04_06', '2_ense_rt10v_genELtask_52_04_07', '2_ense_rt10v_genELtask_53_04_08', '2_ense_rt10v_genELtask_55_04_10', '2_ense_rt10v_genELtask_57_05_01', '2_ense_rt10v_genELtask_58_05_02', '2_ense_rt10v_genELtask_60_05_04', '2_ense_rt10v_genELtask_61_05_05', '2_ense_rt10v_genELtask_62_05_06', '2_ense_rt10v_genELtask_63_05_07', '2_ense_rt10v_genELtask_64_05_08', '2_ense_rt10v_genELtask_68_06_01', '2_ense_rt10v_genELtask_69_06_02', '2_ense_rt10v_genELtask_6_00_05', '2_ense_rt10v_genELtask_70_06_03', '2_ense_rt10v_genELtask_71_06_04', '2_ense_rt10v_genELtask_72_06_05', '2_ense_rt10v_genELtask_74_06_07', '2_ense_rt10v_genELtask_79_07_01', '2_ense_rutpt_genELtask_12_01_00', '2_ense_rutpt_genELtask_13_01_01', '2_ense_rutpt_genELtask_1_00_00', '2_ense_rutpt_genELtask_24_02_01', '2_ense_rutpt_genELtask_25_02_02', '2_ense_rutpt_genELtask_26_02_03', '2_ense_rutpt_genELtask_33_02_10', '2_ense_rutpt_genELtask_35_03_01', '2_ense_rutpt_genELtask_36_03_02', '2_ense_rutpt_genELtask_39_03_05', '2_ense_rutpt_genELtask_43_03_09', '2_ense_rutpt_genELtask_46_04_01', '2_ense_rutpt_genELtask_47_04_02', '2_ense_rutpt_genELtask_48_04_03', '2_ense_rutpt_genELtask_49_04_04', '2_ense_rutpt_genELtask_51_04_06', '2_ense_rutpt_genELtask_52_04_07', '2_ense_rutpt_genELtask_53_04_08', '2_ense_rutpt_genELtask_54_04_09', '2_ense_rutpt_genELtask_55_04_10', '2_ense_rutpt_genELtask_58_05_02', '2_ense_rutpt_genELtask_59_05_03', '2_ense_rutpt_genELtask_60_05_04', '2_ense_rutpt_genELtask_61_05_05', '2_ense_rutpt_genELtask_62_05_06', '2_ense_rutpt_genELtask_63_05_07', '2_ense_rutpt_genELtask_64_05_08', '2_ense_rutpt_genELtask_65_05_09', '2_ense_rutpt_genELtask_66_05_10', '2_ense_rutpt_genELtask_71_06_04', '2_ense_rutpt_genELtask_72_06_05', '2_ense_rutpt_genELtask_73_06_06', '2_ense_rutpt_genELtask_74_06_07', '2_ense_rutpt_genELtask_75_06_08', '2_ense_rutpt_genELtask_76_06_09', '2_ense_rutpt_genELtask_77_06_10', '2_ense_rutpt_genELtask_87_07_09', '2_ense_rutpt_genELtask_88_07_10', '2_enseef_enself_genELtask_13_01_01', '2_enseef_enself_genELtask_1_00_00', '2_enseef_enself_genELtask_24_02_01', '2_enseef_enself_genELtask_2_00_01', '2_enseef_enself_genELtask_36_03_02', '2_enseef_enself_genELtask_37_03_03', '2_enseef_enself_genELtask_48_04_03', '2_enseef_enself_genELtask_49_04_04', '2_enseef_enself_genELtask_59_05_03', '2_enseef_enself_genELtask_60_05_04', 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'2_enseef_rutpt_genELtask_12_01_00', '2_enseef_rutpt_genELtask_13_01_01', '2_enseef_rutpt_genELtask_14_01_02', '2_enseef_rutpt_genELtask_15_01_03', '2_enseef_rutpt_genELtask_16_01_04', '2_enseef_rutpt_genELtask_1_00_00', '2_enseef_rutpt_genELtask_25_02_02', '2_enseef_rutpt_genELtask_26_02_03', '2_enseef_rutpt_genELtask_27_02_04', '2_enseef_rutpt_genELtask_2_00_01', '2_enseef_rutpt_genELtask_30_02_07', '2_enseef_rutpt_genELtask_33_02_10', '2_enseef_rutpt_genELtask_36_03_02', '2_enseef_rutpt_genELtask_37_03_03', '2_enseef_rutpt_genELtask_38_03_04', '2_enseef_rutpt_genELtask_40_03_06', '2_enseef_rutpt_genELtask_44_03_10', '2_enseef_rutpt_genELtask_53_04_08', '2_enseef_rutpt_genELtask_54_04_09', '2_enseef_rutpt_genELtask_55_04_10', '2_enseef_rutpt_genELtask_66_05_10', '2_enself_enve_genELtask_17_01_05', '2_enself_enve_genELtask_19_01_07', '2_enself_enve_genELtask_1_00_00', '2_enself_enve_genELtask_29_02_06', '2_enself_enve_genELtask_2_00_01', '2_enself_enve_genELtask_31_02_08', '2_enself_enve_genELtask_32_02_09', '2_enself_enve_genELtask_3_00_02', '2_enself_enve_genELtask_42_03_08', '2_enself_enve_genELtask_43_03_09', '2_enself_enve_genELtask_53_04_08', '2_enself_enve_genELtask_54_04_09', '2_enself_enve_genELtask_6_00_05', '2_enself_enve_genELtask_7_00_06', '2_enself_enve_genELtask_9_00_08', '2_enself_rmcv_genELtask_13_01_01', '2_enself_rmcv_genELtask_14_01_02', '2_enself_rmcv_genELtask_15_01_03', '2_enself_rmcv_genELtask_17_01_05', '2_enself_rmcv_genELtask_24_02_01', '2_enself_rmcv_genELtask_25_02_02', '2_enself_rmcv_genELtask_2_00_01', '2_enself_rmcv_genELtask_34_03_00', '2_enself_rmcv_genELtask_36_03_02', '2_enself_rmcv_genELtask_3_00_02', '2_enself_rmcv_genELtask_45_04_00', '2_enself_rmcv_genELtask_6_00_05', '2_enself_rmcv_genELtask_7_00_06', '2_enself_rt10v_genELtask_10_00_09', '2_enself_rt10v_genELtask_13_01_01', '2_enself_rt10v_genELtask_14_01_02', '2_enself_rt10v_genELtask_18_01_06', '2_enself_rt10v_genELtask_20_01_08', '2_enself_rt10v_genELtask_21_01_09', '2_enself_rt10v_genELtask_22_01_10', '2_enself_rt10v_genELtask_31_02_08', '2_enself_rt10v_genELtask_35_03_01', '2_enself_rt10v_genELtask_36_03_02', '2_enself_rt10v_genELtask_40_03_06', '2_enself_rt10v_genELtask_46_04_01', '2_enself_rt10v_genELtask_4_00_03', '2_enself_rt10v_genELtask_5_00_04', '2_enself_rt10v_genELtask_6_00_05', '2_enself_rt10v_genELtask_7_00_06', '2_enself_rt10v_genELtask_8_00_07', '2_enself_rutpt_genELtask_13_01_01', '2_enself_rutpt_genELtask_15_01_03', '2_enself_rutpt_genELtask_16_01_04', '2_enself_rutpt_genELtask_19_01_07', '2_enself_rutpt_genELtask_1_00_00', '2_enself_rutpt_genELtask_20_01_08', '2_enself_rutpt_genELtask_21_01_09', '2_enself_rutpt_genELtask_22_01_10', '2_enself_rutpt_genELtask_25_02_02', '2_enself_rutpt_genELtask_2_00_01', '2_enself_rutpt_genELtask_3_00_02', '2_enself_rutpt_genELtask_42_03_08', '2_enself_rutpt_genELtask_44_03_10', '2_enself_rutpt_genELtask_4_00_03', '2_enself_rutpt_genELtask_55_04_10', 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'2_rt10v_rutpt_genELtask_32_02_09', '2_rt10v_rutpt_genELtask_34_03_00', '2_rt10v_rutpt_genELtask_36_03_02', '2_rt10v_rutpt_genELtask_38_03_04', '2_rt10v_rutpt_genELtask_39_03_05', '2_rt10v_rutpt_genELtask_41_03_07', '2_rt10v_rutpt_genELtask_42_03_08', '2_rt10v_rutpt_genELtask_46_04_01', '2_rt10v_rutpt_genELtask_49_04_04', '2_rt10v_rutpt_genELtask_51_04_06', '2_rt10v_rutpt_genELtask_52_04_07', '2_rt10v_rutpt_genELtask_61_05_05', '2_rt10v_rutpt_genELtask_62_05_06', '2_rt10v_rutpt_genELtask_68_06_01', '2_rt10v_rutpt_genELtask_71_06_04', '2_rt10v_rutpt_genELtask_72_06_05', '2_rt10v_rutpt_genELtask_79_07_01', '2_rt10v_rutpt_genELtask_80_07_02', '2_rt10v_rutpt_genELtask_81_07_03', '2_rt10v_rutpt_genELtask_82_07_04', '2_rt10v_rutpt_genELtask_90_08_01', '2_rt10v_rutpt_genELtask_91_08_02', '2_rt10v_rutpt_genELtask_92_08_03']\n",
-      "Path:  ../data/GenED_bench.csv\n",
-      "(432, 19)\n",
-      "['2_ense_enseef_genELtask_13_01_01', '2_ense_enseef_genELtask_1_00_00', '2_ense_enseef_genELtask_24_02_01', '2_ense_enseef_genELtask_25_02_02', '2_ense_enseef_genELtask_35_03_01', '2_ense_enseef_genELtask_36_03_02', '2_ense_enseef_genELtask_47_04_02', '2_ense_enseef_genELtask_48_04_03', '2_ense_enseef_genELtask_58_05_02', '2_ense_enseef_genELtask_59_05_03', '2_ense_enseef_genELtask_60_05_04', '2_ense_enseef_genELtask_69_06_02', '2_ense_enseef_genELtask_70_06_03', '2_ense_enseef_genELtask_71_06_04', '2_ense_enseef_genELtask_82_07_04', '2_ense_enseef_genELtask_83_07_05', '2_ense_enself_genELtask_1_00_00', '2_ense_enself_genELtask_24_02_01', '2_ense_enself_genELtask_25_02_02', '2_ense_enself_genELtask_2_00_01', '2_ense_enself_genELtask_35_03_01', '2_ense_enself_genELtask_36_03_02', '2_ense_enself_genELtask_46_04_01', '2_ense_enself_genELtask_47_04_02', '2_ense_enself_genELtask_58_05_02', '2_ense_enself_genELtask_68_06_01', '2_ense_enself_genELtask_70_06_03', 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'2_enseef_rutpt_genELtask_53_04_08', '2_enseef_rutpt_genELtask_54_04_09', '2_enseef_rutpt_genELtask_66_05_10', '2_enself_enve_genELtask_17_01_05', '2_enself_enve_genELtask_19_01_07', '2_enself_enve_genELtask_1_00_00', '2_enself_enve_genELtask_29_02_06', '2_enself_enve_genELtask_2_00_01', '2_enself_enve_genELtask_31_02_08', '2_enself_enve_genELtask_32_02_09', '2_enself_enve_genELtask_3_00_02', '2_enself_enve_genELtask_42_03_08', '2_enself_enve_genELtask_43_03_09', '2_enself_enve_genELtask_53_04_08', '2_enself_enve_genELtask_54_04_09', '2_enself_enve_genELtask_6_00_05', '2_enself_enve_genELtask_7_00_06', '2_enself_enve_genELtask_9_00_08', '2_enself_rmcv_genELtask_13_01_01', '2_enself_rmcv_genELtask_14_01_02', '2_enself_rmcv_genELtask_15_01_03', '2_enself_rmcv_genELtask_17_01_05', '2_enself_rmcv_genELtask_24_02_01', '2_enself_rmcv_genELtask_25_02_02', '2_enself_rmcv_genELtask_2_00_01', '2_enself_rmcv_genELtask_34_03_00', '2_enself_rmcv_genELtask_36_03_02', '2_enself_rmcv_genELtask_3_00_02', '2_enself_rmcv_genELtask_45_04_00', '2_enself_rmcv_genELtask_6_00_05', '2_enself_rmcv_genELtask_7_00_06', '2_enself_rt10v_genELtask_10_00_09', '2_enself_rt10v_genELtask_13_01_01', '2_enself_rt10v_genELtask_14_01_02', '2_enself_rt10v_genELtask_18_01_06', '2_enself_rt10v_genELtask_20_01_08', '2_enself_rt10v_genELtask_21_01_09', '2_enself_rt10v_genELtask_22_01_10', '2_enself_rt10v_genELtask_31_02_08', '2_enself_rt10v_genELtask_35_03_01', '2_enself_rt10v_genELtask_36_03_02', '2_enself_rt10v_genELtask_40_03_06', '2_enself_rt10v_genELtask_46_04_01', '2_enself_rt10v_genELtask_4_00_03', '2_enself_rt10v_genELtask_5_00_04', '2_enself_rt10v_genELtask_6_00_05', '2_enself_rt10v_genELtask_7_00_06', '2_enself_rt10v_genELtask_8_00_07', '2_enself_rutpt_genELtask_13_01_01', '2_enself_rutpt_genELtask_15_01_03', '2_enself_rutpt_genELtask_16_01_04', '2_enself_rutpt_genELtask_19_01_07', '2_enself_rutpt_genELtask_1_00_00', '2_enself_rutpt_genELtask_20_01_08', '2_enself_rutpt_genELtask_21_01_09', '2_enself_rutpt_genELtask_22_01_10', '2_enself_rutpt_genELtask_2_00_01', '2_enself_rutpt_genELtask_3_00_02', '2_enself_rutpt_genELtask_42_03_08', '2_enself_rutpt_genELtask_44_03_10', '2_enself_rutpt_genELtask_4_00_03', '2_enself_rutpt_genELtask_55_04_10', '2_enself_rutpt_genELtask_5_00_04', '2_enself_rutpt_genELtask_6_00_05', '2_enve_rmcv_genELtask_100_09_00', '2_enve_rmcv_genELtask_104_09_04', '2_enve_rmcv_genELtask_35_03_01', '2_enve_rmcv_genELtask_40_03_06', '2_enve_rmcv_genELtask_47_04_02', '2_enve_rmcv_genELtask_48_04_03', '2_enve_rmcv_genELtask_49_04_04', '2_enve_rmcv_genELtask_57_05_01', '2_enve_rmcv_genELtask_58_05_02', '2_enve_rmcv_genELtask_68_06_01', '2_enve_rmcv_genELtask_69_06_02', '2_enve_rmcv_genELtask_6_00_05', '2_enve_rmcv_genELtask_70_06_03', '2_enve_rmcv_genELtask_78_07_00', '2_enve_rmcv_genELtask_7_00_06', '2_enve_rmcv_genELtask_80_07_02', '2_enve_rmcv_genELtask_81_07_03', '2_enve_rmcv_genELtask_89_08_00', '2_enve_rmcv_genELtask_90_08_01', '2_enve_rmcv_genELtask_92_08_03', '2_enve_rt10v_genELtask_102_09_02', '2_enve_rt10v_genELtask_108_09_08', '2_enve_rt10v_genELtask_109_09_09', '2_enve_rt10v_genELtask_17_01_05', '2_enve_rt10v_genELtask_23_02_00', '2_enve_rt10v_genELtask_26_02_03', '2_enve_rt10v_genELtask_45_04_00', '2_enve_rt10v_genELtask_46_04_01', '2_enve_rt10v_genELtask_47_04_02', '2_enve_rt10v_genELtask_48_04_03', '2_enve_rt10v_genELtask_56_05_00', '2_enve_rt10v_genELtask_57_05_01', '2_enve_rt10v_genELtask_60_05_04', '2_enve_rt10v_genELtask_64_05_08', '2_enve_rt10v_genELtask_6_00_05', '2_enve_rt10v_genELtask_73_06_06', '2_enve_rt10v_genELtask_74_06_07', '2_enve_rt10v_genELtask_75_06_08', '2_enve_rt10v_genELtask_76_06_09', '2_enve_rt10v_genELtask_77_06_10', '2_enve_rt10v_genELtask_79_07_01', '2_enve_rt10v_genELtask_80_07_02', '2_enve_rt10v_genELtask_82_07_04', '2_enve_rt10v_genELtask_83_07_05', '2_enve_rt10v_genELtask_84_07_06', '2_enve_rt10v_genELtask_85_07_07', '2_enve_rt10v_genELtask_86_07_08', '2_enve_rt10v_genELtask_87_07_09', '2_enve_rt10v_genELtask_88_07_10', '2_enve_rt10v_genELtask_90_08_01', '2_enve_rt10v_genELtask_91_08_02', '2_enve_rt10v_genELtask_95_08_06', '2_enve_rt10v_genELtask_96_08_07', '2_enve_rt10v_genELtask_97_08_08', '2_enve_rutpt_genELtask_102_09_02', '2_enve_rutpt_genELtask_104_09_04', '2_enve_rutpt_genELtask_1_00_00', '2_enve_rutpt_genELtask_38_03_04', '2_enve_rutpt_genELtask_3_00_02', '2_enve_rutpt_genELtask_40_03_06', '2_enve_rutpt_genELtask_44_03_10', '2_enve_rutpt_genELtask_46_04_01', '2_enve_rutpt_genELtask_48_04_03', '2_enve_rutpt_genELtask_53_04_08', '2_enve_rutpt_genELtask_55_04_10', '2_enve_rutpt_genELtask_57_05_01', '2_enve_rutpt_genELtask_60_05_04', '2_enve_rutpt_genELtask_61_05_05', '2_enve_rutpt_genELtask_63_05_07', '2_enve_rutpt_genELtask_64_05_08', '2_enve_rutpt_genELtask_65_05_09', '2_enve_rutpt_genELtask_66_05_10', '2_enve_rutpt_genELtask_68_06_01', '2_enve_rutpt_genELtask_70_06_03', '2_enve_rutpt_genELtask_74_06_07', '2_enve_rutpt_genELtask_77_06_10', '2_enve_rutpt_genELtask_79_07_01', '2_enve_rutpt_genELtask_81_07_03', '2_enve_rutpt_genELtask_82_07_04', '2_enve_rutpt_genELtask_83_07_05', '2_enve_rutpt_genELtask_90_08_01', '2_enve_rutpt_genELtask_91_08_02', '2_enve_rutpt_genELtask_92_08_03', '2_enve_rutpt_genELtask_93_08_04', '2_enve_rutpt_genELtask_98_08_09', '2_enve_rutpt_genELtask_99_08_10', '2_rmcv_rt10v_genELtask_12_01_00', '2_rmcv_rt10v_genELtask_15_01_03', '2_rmcv_rt10v_genELtask_17_01_05', '2_rmcv_rt10v_genELtask_19_01_07', '2_rmcv_rt10v_genELtask_20_01_08', '2_rmcv_rt10v_genELtask_27_02_04', '2_rmcv_rt10v_genELtask_29_02_06', '2_rmcv_rt10v_genELtask_2_00_01', '2_rmcv_rt10v_genELtask_34_03_00', '2_rmcv_rt10v_genELtask_37_03_03', '2_rmcv_rt10v_genELtask_38_03_04', '2_rmcv_rt10v_genELtask_39_03_05', '2_rmcv_rt10v_genELtask_40_03_06', '2_rmcv_rt10v_genELtask_43_03_09', '2_rmcv_rt10v_genELtask_48_04_03', '2_rmcv_rt10v_genELtask_54_04_09', '2_rmcv_rt10v_genELtask_55_04_10', '2_rmcv_rt10v_genELtask_67_06_00', '2_rmcv_rutpt_genELtask_11_00_10', '2_rmcv_rutpt_genELtask_13_01_01', '2_rmcv_rutpt_genELtask_14_01_02', '2_rmcv_rutpt_genELtask_20_01_08', '2_rmcv_rutpt_genELtask_22_01_10', '2_rmcv_rutpt_genELtask_25_02_02', '2_rmcv_rutpt_genELtask_26_02_03', '2_rmcv_rutpt_genELtask_27_02_04', '2_rmcv_rutpt_genELtask_35_03_01', '2_rmcv_rutpt_genELtask_38_03_04', '2_rmcv_rutpt_genELtask_39_03_05', '2_rmcv_rutpt_genELtask_40_03_06', '2_rmcv_rutpt_genELtask_45_04_00', '2_rmcv_rutpt_genELtask_56_05_00', '2_rmcv_rutpt_genELtask_57_05_01', '2_rt10v_rutpt_genELtask_101_09_01', '2_rt10v_rutpt_genELtask_102_09_02', '2_rt10v_rutpt_genELtask_1_00_00', '2_rt10v_rutpt_genELtask_22_01_10', '2_rt10v_rutpt_genELtask_27_02_04', '2_rt10v_rutpt_genELtask_30_02_07', '2_rt10v_rutpt_genELtask_34_03_00', '2_rt10v_rutpt_genELtask_36_03_02', '2_rt10v_rutpt_genELtask_38_03_04', '2_rt10v_rutpt_genELtask_39_03_05', '2_rt10v_rutpt_genELtask_41_03_07', '2_rt10v_rutpt_genELtask_42_03_08', '2_rt10v_rutpt_genELtask_46_04_01', '2_rt10v_rutpt_genELtask_49_04_04', '2_rt10v_rutpt_genELtask_51_04_06', '2_rt10v_rutpt_genELtask_52_04_07', '2_rt10v_rutpt_genELtask_61_05_05', '2_rt10v_rutpt_genELtask_62_05_06', '2_rt10v_rutpt_genELtask_68_06_01', '2_rt10v_rutpt_genELtask_71_06_04', '2_rt10v_rutpt_genELtask_79_07_01', '2_rt10v_rutpt_genELtask_80_07_02', '2_rt10v_rutpt_genELtask_81_07_03', '2_rt10v_rutpt_genELtask_82_07_04', '2_rt10v_rutpt_genELtask_90_08_01', '2_rt10v_rutpt_genELtask_91_08_02', '2_rt10v_rutpt_genELtask_92_08_03']\n",
-      "(432, 26)\n",
-      "Index(['log', 'ratio_unique_traces_per_trace', 'ratio_most_common_variant',\n",
-      "       'ratio_top_10_variants', 'epa_normalized_variant_entropy',\n",
-      "       'epa_normalized_sequence_entropy',\n",
-      "       'epa_normalized_sequence_entropy_linear_forgetting',\n",
-      "       'epa_normalized_sequence_entropy_exponential_forgetting', 'fitness_heu',\n",
-      "       'precision_heu', 'fscore_heu', 'size_heu', 'pnsize_heu', 'cfc_heu',\n",
-      "       'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'pnsize_ilp',\n",
-      "       'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf',\n",
-      "       'pnsize_imf', 'cfc_imf'],\n",
-      "      dtype='object')\n",
-      "Imputed dataset: (432, 26)\n",
-      "No nan's dataset: (281, 26)\n",
-      "FT_COL:  ['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",
-      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
-      "(281, 8) (281, 16)\n",
-      "GenED (281, 8) (281, 16)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['rutpt', 'rmcv', 'rt10v', 'enve', 'ense', 'enself', 'enseef']\n",
-      "Direct pearsonr GenED\n",
-      "GenED\n",
-      "../output/plots/pdm_pearsonr_GenED_nanDropped\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from scipy.stats import spearmanr\n",
     "from scipy.stats import kendalltau\n",
@@ -178,12 +128,13 @@
     "sys.path.append(os.path.dirname(\"../gedi/utils/io_helpers.py\"))\n",
     "from io_helpers import get_keys_abbreviation\n",
     "\n",
-    "def statistical_test(feature_source, bench_source, test, impute=False):\n",
+    "def statistical_test(feature_source, bench_source, test, impute=False, p_thresh=0.05, focus='stat'):\n",
     "    ft = load_data(feature_source, 'feat')\n",
+    "    #ft['log']=ft.apply(lambda x: x['log'].replace(\"Gen\",\"\"), axis=1)\n",
     "    #paper_feat_columns = [\"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",
     "    #ft= ft[paper_feat_columns]\n",
-    "    print(ft.shape)\n",
-    "    print(ft['log'].tolist())\n",
+    "    #print(ft.shape)\n",
+    "    #print(\"Feature: \", ft['log'].tolist())\n",
     "\n",
     "\n",
     "    ben = load_data(bench_source, 'bench')\n",
@@ -194,20 +145,20 @@
     "           'size_ilp','cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
     "\n",
     "    #ben = ben[paper_metrics_columns]\n",
-    "    print(ben.shape)\n",
-    "    print(ben['log'].tolist())\n",
+    "    #print(ben.shape)\n",
+    "    #print(\"Bench: \", ben['log'].tolist())\n",
     "    fd_pdm = pd.merge(ft, ben, on=['log'], 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",
+    "    #print(fd_pdm.shape)\n",
     "    fd_pdm['log'].unique()\n",
     "    \n",
-    "    print(fd_pdm.columns)\n",
+    "    #print(fd_pdm.columns)\n",
     "    benchmark_ft, benchmark_pd = clean_data(fd_pdm, impute, paper_feat_columns, paper_metrics_columns)\n",
     "    \n",
-    "    print(benchmark_ft.shape, benchmark_pd.shape)\n",
+    "    #print(benchmark_ft.shape, benchmark_pd.shape)\n",
     "\n",
     "    benchmarked_ft_plot = benchmark_ft.copy()\n",
     "    benchmarked_pdm_plot = benchmark_pd.copy()\n",
@@ -226,19 +177,65 @@
     "            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",
+    "                    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",
+    "                    df_tmp.loc[metric, feature] = eval(focus)*(1.0 if (p <= p_thresh) else 0.0)\n",
     "\n",
     "    feature_keys = get_keys_abbreviation(df_tmp.columns).split(\"_\")\n",
-    "    print(feature_keys)\n",
+    "    #print(feature_keys)\n",
     "    df_tmp.columns=feature_keys\n",
-    "    print(\"Direct\", TEST, DATA_SOURCE)\n",
+    "    print(\"Direct\", test, feature_source)\n",
     "    # df_tmp[pd.isnan()]\n",
-    "\n",
-    "    sns.heatmap(df_tmp.fillna(0), annot=True, cmap=\"viridis\", annot_kws={\"size\": 14})#, vmin=-0.9, vmax=0.9)\n",
+    "    return df_tmp\n",
+    "#df_tmp = statistical_test(DATA_SOURCE+\"_feat\", \"Gen\"+DATA_SOURCE+\"_bench\", TEST, IMPUTE)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "8f75faf4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Path:  ../data/BaselineED_feat.csv\n",
+      "Path:  ../data/BaselineED_bench.csv\n",
+      "Imputed dataset: (20, 26)\n",
+      "No nan's dataset: (14, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (14, 8) (14, 16)\n",
+      "Direct kendalltau BaselineED_feat\n",
+      "BaselineED\n",
+      "../output/plots/pdm_kendalltau_BaselineED_nanDropped\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def plot_stat_test(test_results, feature_source, bench_source, test, impute, mask=True, cbar=False):\n",
+    "    feature_source = feature_source.split(\"_\")[0]\n",
+    "    bench_source = bench_source.split(\"_\")[0]\n",
+    "    if feature_source==bench_source:\n",
+    "        data_source = feature_source\n",
+    "    else:\n",
+    "        data_source = f\"{feature_source}Feat_{bench_source}Bench\"\n",
+    "    sns.heatmap(test_results.fillna(0), annot=True, cmap=\"viridis\", annot_kws={\"size\": 14}, vmin=-1, vmax=1, cbar=cbar )\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",
+    "    if mask:\n",
+    "        sns.heatmap(test_results.fillna(0), mask=test_results.fillna(0)!=0, cmap=\"Greys\", annot=False, ax=ax, cbar=False)\n",
+    "\n",
     "    #ax.set_title(\"P-values of features leading to process discovery metrics\", fontsize=15)\n",
     "    cax = ax.figure.axes[-1]\n",
     "    cax.tick_params(labelsize=14)\n",
@@ -248,33 +245,119 @@
     "    plt.xticks(rotation=-30)\n",
     "\n",
     "    plt.tight_layout()\n",
-    "    output_path = f\"../output/plots/pdm_{get_output_file_name(TEST, DATA_SOURCE, IMPUTE)}\"\n",
+    "    output_path = f\"../output/plots/pdm_{get_output_file_name(test, data_source, impute)}\"\n",
     "    print(output_path)\n",
     "    plt.savefig(output_path, dpi=300)\n",
     "\n",
-    "statistical_test(DATA_SOURCE+\"_feat\", DATA_SOURCE+\"_bench\", TEST, IMPUTE)"
+    "masked_results = statistical_test(DATA_SOURCE+\"_feat\", DATA_SOURCE+\"_bench\", TEST, IMPUTE)\n",
+    "plot_stat_test(masked_results, DATA_SOURCE+\"_feat\", DATA_SOURCE+\"_bench\", TEST, IMPUTE)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "3d381199",
+   "execution_count": 7,
+   "id": "8065ff6f",
    "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "eb1a799c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "kendalltau BaselineED\n",
+      "Path:  ../data/BaselineED_feat.csv\n",
+      "Path:  ../data/BaselineED_bench.csv\n",
+      "Imputed dataset: (20, 26)\n",
+      "No nan's dataset: (14, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (14, 8) (14, 16)\n",
+      "Direct kendalltau BaselineED_feat\n",
+      "BaselineED\n",
+      "../output/plots/pdm_kendalltau_BaselineED_nanDropped\n",
+      "kendalltau GenBaselineED\n",
+      "Path:  ../data/GenBaselineED_feat.csv\n",
+      "Path:  ../data/GenBaselineED_bench.csv\n",
+      "Imputed dataset: (24, 26)\n",
+      "No nan's dataset: (19, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (19, 8) (19, 16)\n",
+      "Direct kendalltau GenBaselineED_feat\n",
+      "GenBaselineED\n",
+      "../output/plots/pdm_kendalltau_GenBaselineED_nanDropped\n",
+      "kendalltau GenED\n",
+      "Path:  ../data/GenED_feat.csv\n",
+      "Path:  ../data/GenED_bench.csv\n",
+      "Imputed dataset: (441, 26)\n",
+      "No nan's dataset: (285, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (285, 8) (285, 16)\n",
+      "Direct kendalltau GenED_feat\n",
+      "GenED\n",
+      "../output/plots/pdm_kendalltau_GenED_nanDropped\n",
+      "pearsonr BaselineED\n",
+      "Path:  ../data/BaselineED_feat.csv\n",
+      "Path:  ../data/BaselineED_bench.csv\n",
+      "Imputed dataset: (20, 26)\n",
+      "No nan's dataset: (14, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (14, 8) (14, 16)\n",
+      "Direct pearsonr BaselineED_feat\n",
+      "BaselineED\n",
+      "../output/plots/pdm_pearsonr_BaselineED_nanDropped\n",
+      "pearsonr GenBaselineED\n",
+      "Path:  ../data/GenBaselineED_feat.csv\n",
+      "Path:  ../data/GenBaselineED_bench.csv\n",
+      "Imputed dataset: (24, 26)\n",
+      "No nan's dataset: (19, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (19, 8) (19, 16)\n",
+      "Direct pearsonr GenBaselineED_feat\n",
+      "GenBaselineED\n",
+      "../output/plots/pdm_pearsonr_GenBaselineED_nanDropped\n",
+      "pearsonr GenED\n",
+      "Path:  ../data/GenED_feat.csv\n",
+      "Path:  ../data/GenED_bench.csv\n",
+      "Imputed dataset: (441, 26)\n",
+      "No nan's dataset: (285, 26)\n",
+      "FT_COL:  ['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",
+      "M_COL:  ['log', 'fitness_heu', 'precision_heu', 'fscore_heu', 'size_heu', 'cfc_heu', 'fitness_ilp', 'precision_ilp', 'fscore_ilp', 'size_ilp', 'cfc_ilp', 'fitness_imf', 'precision_imf', 'fscore_imf', 'size_imf', 'cfc_imf']\n",
+      "BaselineED (285, 8) (285, 16)\n",
+      "Direct pearsonr GenED_feat\n",
+      "GenED\n",
+      "../output/plots/pdm_pearsonr_GenED_nanDropped\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "TESTS=['kendalltau', 'pearsonr']\n",
+    "DATA_SOURCES = ['BaselineED', 'GenBaselineED', 'GenED']\n",
+    "\n",
+    "for test in TESTS:\n",
+    "    for data_source in DATA_SOURCES:\n",
+    "        cbar = True if data_source == 'GenED' else False\n",
+    "        print(test, data_source)\n",
+    "        masked_results = statistical_test(data_source+\"_feat\", data_source+\"_bench\", test, IMPUTE)\n",
+    "        plot_stat_test(masked_results, data_source+\"_feat\", data_source+\"_bench\", test, IMPUTE, cbar=cbar)\n",
+    "        plt.clf()"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "135aba30",
+   "id": "52c58c64",
    "metadata": {},
    "outputs": [],
    "source": []