Started by an SCM change12912407142b14155687d0d80b174796965d2793b1212407142b14155687d0d80b174796965d2793b12origin/master12407142b14155687d0d80b174796965d2793b1212407142b14155687d0d80b174796965d2793b12origin/master113b19b67713baf175f99baa0cb0bdde6e8c1fbc588b19b67713baf175f99baa0cb0bdde6e8c1fbc588origin/grid_fixesb19b67713baf175f99baa0cb0bdde6e8c1fbc588b19b67713baf175f99baa0cb0bdde6e8c1fbc588origin/grid_fixes108b928767c7238139d599dc55420d2a0956161726ab928767c7238139d599dc55420d2a0956161726aorigin/feeding_gr_to_hostb928767c7238139d599dc55420d2a0956161726ab928767c7238139d599dc55420d2a0956161726aorigin/feeding_gr_to_host187a931651e75fe59f3c0435a3b8d1ced442a89d9cca931651e75fe59f3c0435a3b8d1ced442a89d9ccrefs/remotes/origin/mastera931651e75fe59f3c0435a3b8d1ced442a89d9cca931651e75fe59f3c0435a3b8d1ced442a89d9ccrefs/remotes/origin/mastera931651e75fe59f3c0435a3b8d1ced442a89d9cca931651e75fe59f3c0435a3b8d1ced442a89d9ccrefs/remotes/origin/masterhttps://github.com/larson-group/clubb.git18758f0b74fc032b8302525ed85bf2c8c014d679b2b58f0b74fc032b8302525ed85bf2c8c014d679b2brefs/remotes/origin/master58f0b74fc032b8302525ed85bf2c8c014d679b2b58f0b74fc032b8302525ed85bf2c8c014d679b2brefs/remotes/origin/master58f0b74fc032b8302525ed85bf2c8c014d679b2b58f0b74fc032b8302525ed85bf2c8c014d679b2brefs/remotes/origin/masterhttps://github.com/larson-group/sys_adminfalse#1875345151912456clubb_fire_tuning_gfortran_test #187187false18710387SUCCESS1636450568626http://carson.math.uwm.edu/jenkins/job/clubb_fire_tuning_gfortran_test/187/utilities/sens_matrix/test_analyzeSensMatrix.pyutilities/sens_matrix/analyze_sensitivity_matrix.pyutilities/sens_matrix/sens_matrix_dashboard.pyae681935179f62ffb588fe2aab7c95780034f1531636387557000http://carson.math.uwm.edu/jenkins/user/vlarsonVince Larsonvlarson@uwm.eduAdd 3 new features to dashboard: 1) Add Huber (confusingly called "Ransac") regressor to find a fit that de-weights outliers. The goal is to identify tuning trade-offs. 2) Add ElasticNet regressor. The goal here is to obtain a good fit that doesn't perturb the parameters too much, and that leaves some parameter values unchanged if possible. 3) Add a routine to create PCA biplots. The goal here is to identify outliers (i.e., tuning trade-offs) analytically. For #910. 2021-11-08 10:05:57 -0600ae681935179f62ffb588fe2aab7c95780034f153Add 3 new features to dashboard:editutilities/sens_matrix/analyze_sensitivity_matrix.pyeditutilities/sens_matrix/sens_matrix_dashboard.pyeditutilities/sens_matrix/test_analyzeSensMatrix.pypostprocessing/tolerance_compare/tolerance_check.pya931651e75fe59f3c0435a3b8d1ced442a89d9cc1636405058000http://carson.math.uwm.edu/jenkins/user/pbroelspbroelspbroels@uwm.eduUpdating tolerance_check.py to Python3. 2021-11-08 14:57:38 -0600a931651e75fe59f3c0435a3b8d1ced442a89d9ccUpdating tolerance_check.py to Python3.editpostprocessing/tolerance_compare/tolerance_check.pygitiptable_scripts/iptables_patrol.bash58f0b74fc032b8302525ed85bf2c8c014d679b2b1636402789000http://carson.math.uwm.edu/jenkins/user/noreplynoreplynoreply@github.comChanging script to check once per day for attempts at access. #756 2021-11-08 14:19:49 -060058f0b74fc032b8302525ed85bf2c8c014d679b2bChanging script to check once per day for attempts at access. #756editiptable_scripts/iptables_patrol.bashgithttp://carson.math.uwm.edu/jenkins/user/vlarsonVince Larsonhttp://carson.math.uwm.edu/jenkins/user/noreplynoreplyhttp://carson.math.uwm.edu/jenkins/user/pbroelspbroelsfalse188http://carson.math.uwm.edu/jenkins/job/clubb_fire_tuning_gfortran_test/188/186http://carson.math.uwm.edu/jenkins/job/clubb_fire_tuning_gfortran_test/186/