From 13ebf4cb884bed0f84a73b4e42b4ba3c0ff7e730 Mon Sep 17 00:00:00 2001 From: Thierry Moudiki Date: Wed, 22 May 2024 23:04:18 +0200 Subject: [PATCH] update notebook --- ...40501_tuning_BCN_classifier_lazy_Pt2.ipynb | 2766 +++++++++-------- 1 file changed, 1450 insertions(+), 1316 deletions(-) diff --git a/GPopt/demo/thierrymoudiki_20240501_tuning_BCN_classifier_lazy_Pt2.ipynb b/GPopt/demo/thierrymoudiki_20240501_tuning_BCN_classifier_lazy_Pt2.ipynb index d73e505..974ea65 100644 --- a/GPopt/demo/thierrymoudiki_20240501_tuning_BCN_classifier_lazy_Pt2.ipynb +++ b/GPopt/demo/thierrymoudiki_20240501_tuning_BCN_classifier_lazy_Pt2.ipynb @@ -100,8 +100,8 @@ "Requirement already satisfied: certifi>=2017.4.17 in /Users/t/Documents/Python_Packages/GPopt/venv/lib/python3.11/site-packages (from requests->nnetsauce->GPopt==0.6.0) (2024.2.2)\n", "Building wheels for collected packages: GPopt\n", " Building wheel for GPopt (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for GPopt: filename=GPopt-0.6.0-py2.py3-none-any.whl size=71976 sha256=74f1bbe531ccf4d8b17555c2c70345e485e8527d1be945f71e9a1ef33ccf6bd1\n", - " Stored in directory: /private/var/folders/cp/q8d6040n3m38d22z3hkk1zc40000gn/T/pip-ephem-wheel-cache-wix53z_b/wheels/18/c5/f2/2bcb5749155d04d8e285ee88d9c1f7d49467719147ee803dc9\n", + "\u001b[?25h Created wheel for GPopt: filename=GPopt-0.6.0-py2.py3-none-any.whl size=71975 sha256=d9d3f4994f13f2f1c3cf8691218a26972e531fffb02f201c850ed084d1a3d6cb\n", + " Stored in directory: /private/var/folders/cp/q8d6040n3m38d22z3hkk1zc40000gn/T/pip-ephem-wheel-cache-5t5s_fb7/wheels/18/c5/f2/2bcb5749155d04d8e285ee88d9c1f7d49467719147ee803dc9\n", "Successfully built GPopt\n", "Installing collected packages: GPopt\n", " Attempting uninstall: GPopt\n", @@ -273,15 +273,13 @@ "score for next parameter: -1.0 \n", "\n", "{'parameters': DescribeResult(best_params=array([29.25997925, -0.90249939, -1.29089355, -7.03671265, -5.42616882,\n", - " 0.99440308, 1.83303833]), best_score=-1.0, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=100, type_pi='kde')), 'opt_object': }\n", + " 0.99440308, 1.83303833]), best_score=-1.0, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=150, type_pi='kde')), 'opt_object': }\n", " |======================================================================| 100%\n", "\n", - " Elapsed: 4.3761022090911865\n", - "\n", "\n", " Test set accuracy: 0.9722222222222222\n", "\n", - " Elapsed: 0.05333089828491211\n", + " Elapsed: 53.765836000442505\n", "\n", " adjusting surrogate model # 1 (CustomRegressor(BaggingRegressor))... \n", "\n", @@ -321,379 +319,381 @@ "iteration 4 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [26.40634155 -1.2719696 -0.07263184 -5.5085144 -4.87232361 0.92040405\n", - " 2.40103149]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 5 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [29.22445679 -1.45490417 5.19592285 -5.84030151 -4.93426208 0.95502319\n", - " 3.43301392]\n", - "score for next parameter: -0.7976431085254615 \n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [57.35528564 -1.26710815 4.42504883 -9.32818604 -4.14292603 0.94852295\n", + " 3.53253174]\n", + "score for next parameter: -0.790798073615411 \n", "\n", "iteration 6 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", - "score for next parameter: -0.9763060428849902 \n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [97.69696045 -1.49109497 -3.9465332 -1.4520874 -4.4230896 0.94278564\n", + " 3.762146 ]\n", + "score for next parameter: -0.9521992890723542 \n", "\n", "iteration 7 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [96.48031616 -1.55861511 -6.01501465 -6.17428589 -5.59109802 0.94838257\n", - " 2.33731079]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [41.13632202 -0.60072937 -0.41442871 -2.006073 -5.04805603 0.9781189\n", + " 3.31069946]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 8 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [30.94433594 -0.30166016 -5.33203125 -7.26660156 -4.15048828 0.92597656\n", - " 2.90722656]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [86.23144474 -1.26062895 2.30159918 -9.94778117 -4.96713712 0.85116269\n", + " 3.56545594]\n", + "score for next parameter: -0.8234725829153074 \n", "\n", "iteration 9 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 9.36444092 -0.37620239 -6.51489258 -4.277771 -0.46766968 0.93741455\n", - " 1.42572021]\n", - "score for next parameter: -0.8297102897102896 \n", + "next parameter: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 10 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [52.90313721 -1.36505737 -0.59448242 -4.30963135 -5.95786743 0.88309326\n", - " 1.51397705]\n", - "score for next parameter: -0.9667822333611807 \n", + "next parameter: [70.37426758 -2.31970215 -5.27832031 -3.51586914 -5.75368652 0.87915039\n", + " 1.28051758]\n", + "score for next parameter: -0.9577635327635328 \n", "\n", "iteration 11 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [60.08459473 -1.60596924 -4.02099609 -8.61462402 -5.09180908 0.99758301\n", - " 1.61486816]\n", - "score for next parameter: -0.9680687830687831 \n", + "next parameter: [67.81072998 -1.7302063 -9.89379883 -5.60491943 -5.76268921 0.85987549\n", + " 2.6473999 ]\n", + "score for next parameter: -0.7907980736154111 \n", "\n", "iteration 12 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [31.16635132 -1.84382019 -4.59899902 -3.63864136 -3.38147888 0.9387146\n", - " 1.50674438]\n", - "score for next parameter: -0.9515621633268692 \n", + "next parameter: [45.95553589 -1.90071716 -5.87585449 -5.85238647 -4.75348816 0.96935425\n", + " 2.384552 ]\n", + "score for next parameter: -0.9601513587891297 \n", "\n", "iteration 13 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [20.3112793 -1.30275879 -4.78027344 -6.7722168 -2.63371582 0.98256836\n", - " 2.36303711]\n", - "score for next parameter: -0.9515861549298081 \n", + "next parameter: [72.64770508 -0.2454834 -3.87207031 -5.83618164 -4.60134277 0.94633789\n", + " 2.33520508]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 14 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [31.93304443 -0.45830688 -3.15063477 -7.7164917 -5.29743042 0.90582275\n", - " 2.77996826]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [60.55230713 -1.45580444 -0.65795898 -4.47442627 -4.82713013 0.94573975\n", + " 2.77740479]\n", + "score for next parameter: -0.9593748259537733 \n", "\n", "iteration 15 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 6.62921143 -1.30455933 -1.2097168 -8.831604 -5.20020142 0.99412842\n", - " 3.10040283]\n", - "score for next parameter: -0.9517495536226187 \n", + "next parameter: [ 6.13781738 -1.56851807 -2.76123047 -5.59558105 -5.32515869 0.97697754\n", + " 3.52355957]\n", + "score for next parameter: -0.832962920120815 \n", "\n", "iteration 16 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [14.50631714 -1.55501404 5.13977051 -8.27816772 -5.51403503 0.993573\n", - " 2.18533325]\n", - "score for next parameter: -0.8146565760807245 \n", + "next parameter: [26.59363994 -5.45847167 7.66782133 -6.80583503 -1.92765282 0.85876589\n", + " 2.62865945]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 17 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [99.3576355 -1.20210876 -7.61901855 -3.9078064 -5.8179657 0.88424683\n", - " 2.03225708]\n", - "score for next parameter: -0.8427559912854029 \n", + "next parameter: [70.54891968 -0.91474304 -4.79919434 -7.70578003 -4.99908142 0.89188843\n", + " 2.85220337]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 18 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", - " 3.53500752]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [27.74139404 -1.67835083 -0.38208008 -5.70159912 -4.02841187 0.90499268\n", + " 3.66986084]\n", + "score for next parameter: -0.9680687830687831 \n", "\n", "iteration 19 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [18.33978271 -0.17310181 -2.08618164 -4.72381592 -5.55958862 0.9776001\n", - " 1.57440186]\n", + "next parameter: [22.16732788 -0.55895691 -2.35290527 -2.32907104 -4.59720154 0.89515991\n", + " 1.6210022 ]\n", "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 20 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [62.92047119 -0.41293335 -9.03686523 -9.40509033 -5.20164185 0.97171631\n", - " 2.3760376 ]\n", - "score for next parameter: -0.9134531590413942 \n", + "next parameter: [32.92175293 -1.79178467 -7.54150391 -2.70178223 -3.77957764 0.9564209\n", + " 1.14099121]\n", + "score for next parameter: -0.5870147630147631 \n", "\n", "iteration 21 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [40.92318726 -4.64977722 -9.11071777 -6.63571167 -5.20794373 0.96820679\n", - " 1.66201782]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", + " 1.00860596]\n", + "score for next parameter: -0.9589390961062788 \n", "\n", "iteration 22 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", - " 3.03146362]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [77.21234131 -0.79248657 -1.70532227 -5.55438232 -5.86207886 0.88199463\n", + " 2.48114014]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 23 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [88.35751343 -1.72138367 -0.34606934 -8.86593628 -4.97603455 0.96141968\n", - " 3.54360962]\n", + "next parameter: [50.9760437 -0.82327576 -5.23132324 -8.09359741 -5.62350769 0.88087769\n", + " 3.84646606]\n", "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 24 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [78.24841309 -0.86126709 -7.04345703 -2.67980957 -5.88548584 0.94440918\n", - " 2.91784668]\n", - "score for next parameter: -0.968187134502924 \n", + "next parameter: [48.97459547 -0.48934498 4.02367628 -2.68769112 -1.12635245 0.89247043\n", + " 3.60488843]\n", + "score for next parameter: -0.7683943810286521 \n", "\n", "iteration 25 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [52.15716553 -0.5706604 -0.11352539 -5.64666748 -5.1850769 0.82662354\n", - " 1.60662842]\n", - "score for next parameter: -0.9577635327635328 \n", + "next parameter: [59.68200684 -1.66790771 -7.74658203 -3.76965332 -5.90853271 0.80300293\n", + " 3.67956543]\n", + "score for next parameter: -0.8203324550692972 \n", "\n", "iteration 26 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 8.97756801 -3.35099037 5.00761608 -8.45276339 -5.84574241 0.88054979\n", - " 1.30676987]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [22.67352295 -2.27468872 -2.2277832 -1.8036499 -5.85199585 0.90997314\n", + " 1.1137085 ]\n", + "score for next parameter: -0.5805982905982906 \n", "\n", "iteration 27 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [59.72640991 -0.33713074 -2.96813965 -3.32662964 -2.89461365 0.84291382\n", - " 1.43496704]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [26.77636719 -0.14033203 -8.22265625 -6.59863281 -4.63447266 0.96738281\n", + " 1.67675781]\n", + "score for next parameter: -0.9349137549756745 \n", "\n", "iteration 28 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 5.89804077 -0.854245 -8.46130371 -8.22872925 -1.61407166 0.88202515\n", - " 2.71304321]\n", - "score for next parameter: -0.6480388668031689 \n", + "next parameter: [56.13568115 -1.20444946 -4.60571289 -4.11737061 -4.45910034 0.89967041\n", + " 2.50311279]\n", + "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 29 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [33.95782471 -1.13458862 1.12426758 -2.55181885 -5.72739868 0.80653076\n", - " 1.77178955]\n", - "score for next parameter: -0.9253825803825805 \n", + "next parameter: [35.82867432 -1.69203491 -3.99780273 -3.69219971 -1.52566528 0.89007568\n", + " 1.28033447]\n", + "score for next parameter: -0.7635062007235921 \n", "\n", "iteration 30 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [91.53973389 -0.39060669 -4.27856445 -6.68157959 -1.35209351 0.89219971\n", - " 2.39398193]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [81.32702637 -0.32254639 -6.62353516 -3.71252441 -3.84295654 0.91950684\n", + " 2.14001465]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 31 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [71.36386837 -4.10036573 6.97359411 -9.02428174 -2.52055746 0.93959145\n", " 1.15576259]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 32 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [34.44329834 -1.24478149 -0.95336914 -6.35858154 -5.40978394 0.95767822\n", - " 1.29901123]\n", - "score for next parameter: -0.9680687830687831 \n", + "next parameter: [20.7789917 -0.59226685 -9.9621582 -3.31536865 -5.64457397 0.87637939\n", + " 2.69573975]\n", + "score for next parameter: -0.7987501433321866 \n", "\n", "iteration 33 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [52.75512695 -0.71794434 -9.77050781 -3.74438477 -4.70505371 0.95610352\n", - " 2.5871582 ]\n", - "score for next parameter: -0.8173744819565254 \n", + "next parameter: [63.32794828 -0.30289793 0.99469241 -2.74332929 -2.84288681 0.8113242\n", + " 2.69867417]\n", + "score for next parameter: -0.9118212197159565 \n", "\n", "iteration 34 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [68.85611999 -1.0064982 -6.12318616 -4.2177702 -3.82647124 0.8896449\n", - " 3.99534442]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [89.18341064 -0.62179565 0.36254883 -4.12506104 -5.89448853 0.99539795\n", + " 3.20440674]\n", + "score for next parameter: -0.9445393713040773 \n", "\n", "iteration 35 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [95.37911987 -0.5683197 -7.03308105 -5.99960327 -3.64003601 0.84244995\n", - " 3.76077271]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [25.25482178 -0.68589478 -8.78540039 -5.40057373 -4.60890503 0.93834229\n", + " 1.52459717]\n", + "score for next parameter: -0.903322194374826 \n", "\n", "iteration 36 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [69.82824076 -3.88455314 -6.66694252 -3.2741885 -2.79463632 0.85075364\n", - " 1.9297718 ]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [90.32012939 -0.96749878 -5.02807617 -4.65240479 -4.39644165 0.8618042\n", + " 3.02862549]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 37 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [88.0132581 -3.76422671 6.57971842 -5.82198753 -4.33375148 0.8005958\n", " 2.77675216]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 38 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [88.21246338 -1.29447632 -2.92358398 -3.80645752 -3.928302 0.9605835\n", - " 1.14849854]\n", + "next parameter: [72.28952026 -0.64466248 -7.39929199 -3.6902771 -5.5025116 0.94943237\n", + " 1.46463013]\n", "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 39 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [34.35449219 -0.97001953 -6.66015625 -2.52050781 -3.43603516 0.91425781\n", - " 2.09863281]\n", - "score for next parameter: -0.8505446623093682 \n", + "next parameter: [24.26712784 -4.50386356 -7.66841876 -5.34755625 -5.56134511 0.98353203\n", + " 3.56795442]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 40 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [71.68859863 -2.05250244 -2.52685547 -7.3885498 -4.79508057 0.93713379\n", - " 3.04309082]\n", - "score for next parameter: -0.9685173718610252 \n", + "next parameter: [83.09261445 -5.27003396 -3.95805902 -1.14837026 -0.1333424 0.93540682\n", + " 3.82624314]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 41 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [73.64825439 -1.98156128 -3.46557617 -4.51177979 -3.01362915 0.8461792\n", - " 3.54425049]\n", - "score for next parameter: -0.8096393762183236 \n", + "next parameter: [50.8193283 -3.05975379 -6.27466769 -6.83094636 -3.91334651 0.89702417\n", + " 2.40270554]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 42 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [18.34004701 -2.09680433 7.53517739 -7.51198309 -0.44065179 0.88448689\n", - " 2.21917284]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [79.0743103 -0.51142273 -3.43200684 -3.78585815 -5.21802673 0.8743103\n", + " 3.13931274]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 43 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [32.92175293 -1.79178467 -7.54150391 -2.70178223 -3.77957764 0.9564209\n", - " 1.14099121]\n", - "score for next parameter: -0.5870147630147631 \n", + "next parameter: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 44 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [91.88607788 -1.11208191 -0.47790527 -1.48532104 -1.83157654 0.87640991\n", - " 2.4647522 ]\n", - "score for next parameter: -0.9605653021442496 \n", + "next parameter: [16.06723322 -1.88451362 -2.99815455 -5.95832332 -5.56295557 0.86632232\n", + " 1.36581272]\n", + "score for next parameter: -0.9252168883747831 \n", "\n", "iteration 45 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [89.00908248 -0.9280715 7.76992743 -8.53901055 -0.27853035 0.96162671\n", " 1.84533372]\n", "score for next parameter: -0.6223212343212342 \n", "\n", "iteration 46 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [91.17562866 -0.86720886 1.95373535 -2.86959839 -3.42469177 0.84682007\n", - " 2.82949829]\n", - "score for next parameter: -0.9280578898225957 \n", + "next parameter: [91.32067871 -0.48099365 -0.59814453 -4.98254395 -4.53724365 0.9932373\n", + " 2.99401855]\n", + "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 47 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [85.22265625 -1.41367187 -3.203125 -3.42578125 -5.88476562 0.85078125\n", - " 3.68359375]\n", + "next parameter: [30.58615112 -0.68355408 -3.36120605 -5.19100952 -3.20214539 0.9291687\n", + " 3.86624146]\n", "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 48 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [18.28057861 -1.09137573 0.25512695 -5.88726807 -0.5850647 0.98846436\n", - " 3.36700439]\n", - "score for next parameter: -0.9602256458138811 \n", + "next parameter: [71.6708374 -0.30562134 -6.09008789 -3.37908936 -5.08136597 0.87388916\n", + " 3.31170654]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 49 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [15.46838379 -1.38126221 -2.90771484 -8.72888184 -1.65206299 0.85168457\n", - " 1.55334473]\n", - "score for next parameter: -0.9602801120448179 \n", + "next parameter: [93.07015991 -0.52150574 -7.34313965 -1.35787964 -4.92273865 0.91166382\n", + " 2.65371704]\n", + "score for next parameter: -0.951255917571707 \n", "\n", "iteration 50 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [59.91882324 -1.23289795 -2.83447266 -3.20275879 -5.69822998 0.92536621\n", - " 3.85681152]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [26.27313232 -1.22605591 1.4050293 -3.08685303 -5.61000366 0.94552002\n", + " 3.40472412]\n", + "score for next parameter: -0.8517489046900814 \n", "\n", "Global iteration #1 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", "score for next parameter: -0.9763060428849902 \n", "\n", @@ -712,400 +712,400 @@ "iteration 1 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [48.84765625 -0.67617187 -5.703125 -2.30078125 -5.14726563 0.97578125\n", - " 1.05859375]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [35.40536499 -0.70155945 -9.74060059 -4.56808472 -5.51187439 0.97723999\n", + " 1.78286743]\n", + "score for next parameter: -0.909962821835887 \n", "\n", "iteration 2 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [ 7.85473633 -0.36071777 -5.04394531 -4.95727539 -5.17751465 0.83149414\n", - " 2.30004883]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", + " 1.00860596]\n", + "score for next parameter: -0.9589390961062788 \n", "\n", "iteration 3 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [40.4850769 -1.48155212 -5.30456543 -6.33798218 -3.18774109 0.91832886\n", - " 2.64602661]\n", - "score for next parameter: -0.9593748259537733 \n", + "next parameter: [78.29155828 -2.57441955 -0.13075297 -4.26919887 -5.98512685 0.81986148\n", + " 1.1709052 ]\n", + "score for next parameter: -0.9248040916771567 \n", "\n", "iteration 4 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [14.43231201 -0.21775513 -9.00512695 -8.56243896 -3.18432007 0.82618408\n", - " 1.64984131]\n", - "score for next parameter: -0.8624923419660261 \n", + "next parameter: [38.64086914 -4.9182373 -8.30566406 -6.77661133 -4.22683105 0.94536133\n", + " 1.59985352]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 5 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [13.43768311 -0.61243286 -5.47973633 -4.70843506 -4.46054077 0.87198486\n", - " 1.82122803]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [11.3359375 -2.54296875 5.15625 -4.4453125 -5.86171875 0.9609375\n", + " 1.2578125 ]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 6 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "next parameter: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 7 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [ 4.75961374 -5.93055824 -3.35033501 -7.81930084 -5.3436628 0.9203518\n", " 2.84529444]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 8 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [32.69381714 -0.44876404 -6.11022949 -4.34066772 -3.67028503 0.831073\n", - " 1.99783325]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [86.23144474 -1.26062895 2.30159918 -9.94778117 -4.96713712 0.85116269\n", + " 3.56545594]\n", + "score for next parameter: -0.8234725829153074 \n", "\n", "iteration 9 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [62.84350586 -0.95129395 -6.98730469 -4.70678711 -4.52932129 0.90737305\n", - " 1.10620117]\n", - "score for next parameter: -0.943198355365538 \n", + "next parameter: [45.22140503 -0.11026306 -9.40612793 -3.64852905 -5.36567078 0.95856323\n", + " 1.74954224]\n", + "score for next parameter: -0.9435018919848641 \n", "\n", "iteration 10 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [53.05706787 -0.26817017 -4.06860352 -3.04949951 -5.36080933 0.87476807\n", - " 1.78094482]\n", + "next parameter: [22.16732788 -0.55895691 -2.35290527 -2.32907104 -4.59720154 0.89515991\n", + " 1.6210022 ]\n", "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 11 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [17.05505371 -0.57318115 -7.16064453 -6.81066895 -4.26068115 0.8151123\n", - " 1.54089355]\n", - "score for next parameter: -0.9116067947646895 \n", + "next parameter: [30.75916535 -2.8936722 4.84967267 -2.92231716 -1.66099424 0.9341604\n", + " 1.27986004]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 12 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [82.50814819 -2.45456238 -5.26306152 -5.83590698 -2.54026794 0.92660522\n", - " 1.17276001]\n", - "score for next parameter: -0.9577635327635328 \n", + "next parameter: [88.35076069 -3.08514709 -0.69249388 -3.63324951 -5.10104874 0.84445155\n", + " 1.84595775]\n", + "score for next parameter: -0.47852991452991456 \n", "\n", "iteration 13 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [23.58526611 -1.32184448 -6.77612305 -2.58258057 -2.56709595 0.89315186\n", - " 1.46856689]\n", - "score for next parameter: -0.8192078148142221 \n", + "next parameter: [32.00704956 -0.5971283 -8.3807373 -2.35214233 -5.80068054 0.91998901\n", + " 2.94338989]\n", + "score for next parameter: -0.8083947677136532 \n", "\n", "iteration 14 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 3.41948841 -1.51446798 2.47332694 -4.49869456 -1.32837366 0.82960593\n", - " 3.54826113]\n", - "score for next parameter: -0.26623712581636844 \n", + "next parameter: [39.54077148 -0.45578613 1.02050781 -3.45874023 -5.6701416 0.92885742\n", + " 2.2487793 ]\n", + "score for next parameter: -0.9280034235916588 \n", "\n", "iteration 15 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [55.36898804 -2.58420105 -3.16345215 -7.07077026 -4.95730896 0.85736694\n", - " 1.71035767]\n", - "score for next parameter: -0.7706998315693968 \n", + "next parameter: [18.3340623 -5.20831098 -9.34621063 -5.03040926 -1.16238501 0.89684234\n", + " 2.9677441 ]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 16 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 3.62756348 -3.97979736 -4.88037109 -4.00915527 -4.97657471 0.98430176\n", - " 1.18127441]\n", + "next parameter: [26.59363994 -5.45847167 7.66782133 -6.80583503 -1.92765282 0.85876589\n", + " 2.62865945]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 17 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [15.84432983 -0.98676453 -5.78552246 -2.08517456 -2.55323181 0.85487671\n", - " 2.42300415]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [17.50807616 -3.63641938 -0.81516959 -6.73703575 -2.78494567 0.90551361\n", + " 1.54231583]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 18 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [63.28753662 -1.07481079 -2.89672852 -6.74090576 -5.15338745 0.88492432\n", - " 3.22235107]\n", + "next parameter: [79.0743103 -0.51142273 -3.43200684 -3.78585815 -5.21802673 0.8743103\n", + " 3.13931274]\n", "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 19 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [40.57980347 -3.15821228 -6.26159668 -2.19833374 -5.57885437 0.94860229\n", - " 2.7661438 ]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [21.12237549 -1.26422729 -3.22143555 -1.47515869 -5.78213501 0.96776123\n", + " 2.03692627]\n", + "score for next parameter: -0.9527221648893477 \n", "\n", "iteration 20 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [29.49975586 -0.76691895 -5.11230469 -3.30053711 -1.76369629 0.91362305\n", - " 1.76245117]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [33.75061035 -0.6725708 -3.04443359 -2.0579834 -5.88692627 0.92141113\n", + " 2.19494629]\n", + "score for next parameter: -0.951255917571707 \n", "\n", "iteration 21 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [77.18461444 -1.55721418 -0.92942319 -4.17010123 -4.20746241 0.97039887\n", " 1.73840401]\n", "score for next parameter: -0.9680687830687831 \n", "\n", "iteration 22 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [25.40875244 -0.80473022 6.82250977 -7.19024658 -4.44109497 0.96156006\n", - " 2.55181885]\n", - "score for next parameter: -0.7987501433321866 \n", + "next parameter: [88.82471824 -1.04253491 -7.11007017 -3.61726928 -1.05564586 0.89139124\n", + " 3.27569318]\n", + "score for next parameter: -0.762376978141684 \n", "\n", "iteration 23 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [88.79562378 -1.47002869 -3.39050293 -8.1836853 -2.25434265 0.94371948\n", - " 2.01907349]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [44.34003693 -1.63440122 -6.86964265 -8.83658586 -4.06036562 0.99535025\n", + " 1.12731739]\n", + "score for next parameter: -0.8154217762913415 \n", "\n", "iteration 24 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [48.97459547 -0.48934498 4.02367628 -2.68769112 -1.12635245 0.89247043\n", " 3.60488843]\n", "score for next parameter: -0.7683943810286521 \n", "\n", "iteration 25 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [63.23129272 -0.64250183 -3.8079834 -5.1635437 -4.79021912 0.95404663\n", - " 1.83633423]\n", + "next parameter: [31.67550659 -1.11856384 -3.80065918 -2.18075562 -2.61733093 0.89274292\n", + " 1.98684692]\n", "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 26 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [56.74252319 -0.51862488 -3.70056152 -5.97653198 -4.10745544 0.96723022\n", - " 2.43838501]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [ 8.97756801 -3.35099037 5.00761608 -8.45276339 -5.84574241 0.88054979\n", + " 1.30676987]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 27 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [55.91662598 -0.33839111 -6.28662109 -6.04821777 -4.93048096 0.81398926\n", - " 3.03283691]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [24.42004395 -1.20552979 -3.71826172 -1.71960449 -3.60240479 0.92717285\n", + " 2.31945801]\n", + "score for next parameter: -0.9521992890723542 \n", "\n", "iteration 28 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [24.97840402 -4.09657569 -3.3203752 -9.48069362 -2.14510979 0.83312004\n", " 2.0846341 ]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 29 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [17.42803955 -0.23287964 -6.4831543 -5.50933838 -5.41914673 0.94373779\n", - " 3.18829346]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [77.54980469 -1.29267578 -1.81640625 -2.87207031 -0.62431641 0.97207031\n", + " 3.38769531]\n", + "score for next parameter: -0.9513976179765653 \n", "\n", "iteration 30 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [10.12521362 -0.36089783 -4.14245605 -7.65194702 -2.78730164 0.8119812\n", - " 3.70217896]\n", + "next parameter: [46.75183105 -0.90447998 -0.86181641 -4.26623535 -2.63875732 0.92946777\n", + " 3.05700684]\n", "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 31 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [85.3114624 -1.13530884 -8.90258789 -9.70721436 -3.32980347 0.82076416\n", - " 2.88983154]\n", - "score for next parameter: -0.7987501433321866 \n", + "next parameter: [76.09042358 -1.42465515 -2.89489746 -2.61251831 -3.22159119 0.89940796\n", + " 2.3644104 ]\n", + "score for next parameter: -0.951255917571707 \n", "\n", "iteration 32 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [36.39274637 -5.06301976 -7.24479204 -2.74657433 -1.66871527 0.8429524\n", " 3.9728427 ]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 33 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [63.32794828 -0.30289793 0.99469241 -2.74332929 -2.84288681 0.8113242\n", " 2.69867417]\n", "score for next parameter: -0.9118212197159565 \n", "\n", "iteration 34 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [24.73678589 -0.24134216 -7.75085449 -5.00863647 -5.67536316 0.86310425\n", - " 3.415802 ]\n", - "score for next parameter: -0.9367056530214425 \n", + "next parameter: [36.10101318 -0.89619751 -4.47875977 -2.33758545 -5.22828979 0.940979\n", + " 2.22918701]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 35 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [56.88165283 -0.40861206 -4.69604492 -5.59283447 -3.77993774 0.84364014\n", - " 2.78546143]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [13.42880249 -1.3007782 -3.02185059 -3.93527222 -5.37359314 0.94130249\n", + " 2.83755493]\n", + "score for next parameter: -0.9515861549298081 \n", "\n", "iteration 36 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [79.45617676 -0.1050415 -5.37841797 -5.85925293 -5.79761963 0.87111816\n", - " 3.6348877 ]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [69.08953857 -0.60379028 -1.7980957 -1.92669678 -1.02367554 0.85098877\n", + " 1.86956787]\n", + "score for next parameter: -0.9521067374318148 \n", "\n", "iteration 37 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [90.32012939 -0.96749878 -5.02807617 -4.65240479 -4.39644165 0.8618042\n", - " 3.02862549]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [88.0132581 -3.76422671 6.57971842 -5.82198753 -4.33375148 0.8005958\n", + " 2.77675216]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 38 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [38.37445068 -0.11260376 3.17749023 -5.36102295 -2.23219604 0.9612915\n", - " 1.87762451]\n", - "score for next parameter: -0.839233125548915 \n", + "next parameter: [88.37823486 -0.74567261 -2.16674805 -4.37554932 -0.83858032 0.92518311\n", + " 2.08966064]\n", + "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 39 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [71.58203125 -0.76835937 -1.640625 -9.47265625 -4.13320312 0.80390625\n", - " 2.51171875]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [96.66088867 -0.99162598 -5.91308594 -2.88745117 -1.74641113 0.87749023\n", + " 3.21264648]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 40 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [71.6708374 -0.30562134 -6.09008789 -3.37908936 -5.08136597 0.87388916\n", - " 3.31170654]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [83.09261445 -5.27003396 -3.95805902 -1.14837026 -0.1333424 0.93540682\n", + " 3.82624314]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 41 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [50.8193283 -3.05975379 -6.27466769 -6.83094636 -3.91334651 0.89702417\n", " 2.40270554]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 42 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [21.67297363 -0.66968994 -6.58935547 -6.4041748 -3.22789307 0.95275879\n", - " 2.71496582]\n", - "score for next parameter: -0.9445751633986929 \n", + "next parameter: [77.31890869 -0.8277771 -8.56811523 -2.30352783 -1.1914856 0.88890381\n", + " 2.2119751 ]\n", + "score for next parameter: -0.8225459072517897 \n", "\n", "iteration 43 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [16.67318726 -0.22477722 -4.11071777 -4.38571167 -3.73294373 0.81820679\n", - " 2.41201782]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [ 3.7153757 -0.54264509 -7.58613214 -5.06055548 -0.84674669 0.86606726\n", + " 2.55714102]\n", + "score for next parameter: -0.583122507122507 \n", "\n", "iteration 44 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [16.06723322 -1.88451362 -2.99815455 -5.95832332 -5.56295557 0.86632232\n", " 1.36581272]\n", "score for next parameter: -0.9252168883747831 \n", "\n", "iteration 45 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [89.00908248 -0.9280715 7.76992743 -8.53901055 -0.27853035 0.96162671\n", " 1.84533372]\n", "score for next parameter: -0.6223212343212342 \n", "\n", "iteration 46 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [67.5887146 -0.35441589 -9.7064209 -7.25534058 -4.87088318 0.94506226\n", - " 3.0843811 ]\n", - "score for next parameter: -0.9033919010699197 \n", + "next parameter: [89.26795476 -1.9373047 -3.79085411 -8.26376342 -2.26006856 0.97236419\n", + " 2.19545 ]\n", + "score for next parameter: -0.9515861549298081 \n", "\n", "iteration 47 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [34.81126277 -5.45807985 -6.70723536 -4.40920268 -4.24782511 0.99682821\n", " 3.73510775]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 48 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [21.99268954 -2.8553348 4.28831457 -9.26887409 -1.73455867 0.94088029\n", - " 2.90010999]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [97.92489624 -1.09335632 -5.75622559 -4.39230347 -0.32632751 0.91083374\n", + " 2.70864868]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 49 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [33.37298024 -1.53918059 -7.67205338 -2.09071315 -3.16740687 0.84715434\n", " 2.65307455]\n", "score for next parameter: -0.827206273258905 \n", "\n", "iteration 50 -----\n", - "current minimum: [13.05285645 -0.97506104 -5.74951172 -6.28991699 -4.84693604 0.93811035\n", - " 3.37414551]\n", + "current minimum: [52.0831604 -0.89205627 -4.44885254 -1.4737854 -5.71461487 0.91365356\n", + " 3.03146362]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [12.57431669 -0.36696139 6.24173089 -9.82896983 -1.69082019 0.83776172\n", " 2.84046913]\n", "score for next parameter: -0.8213828689370486 \n", "\n", "Global iteration #2 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", "score for next parameter: -0.9763060428849902 \n", "\n", @@ -1124,107 +1124,107 @@ "iteration 1 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [48.84765625 -0.67617187 -5.703125 -2.30078125 -5.14726563 0.97578125\n", - " 1.05859375]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [10.59884644 -1.13872986 -2.1697998 -4.02206421 -3.96845398 0.92584839\n", + " 1.64846802]\n", + "score for next parameter: -0.9602801120448179 \n", "\n", "iteration 2 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", - " 1.00860596]\n", - "score for next parameter: -0.9589390961062788 \n", + "next parameter: [18.33978271 -0.17310181 -2.08618164 -4.72381592 -5.55958862 0.9776001\n", + " 1.57440186]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 3 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [78.29155828 -2.57441955 -0.13075297 -4.26919887 -5.98512685 0.81986148\n", - " 1.1709052 ]\n", - "score for next parameter: -0.9248040916771567 \n", + "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", + " 1.00860596]\n", + "score for next parameter: -0.9589390961062788 \n", "\n", "iteration 4 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [30.69567871 -1.21849365 -8.09814453 -1.60754395 -5.27474365 0.8682373\n", - " 1.86901855]\n", - "score for next parameter: -0.8506349206349206 \n", + "next parameter: [22.16732788 -0.55895691 -2.35290527 -2.32907104 -4.59720154 0.89515991\n", + " 1.6210022 ]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 5 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [58.11309814 -1.1288269 -8.54370117 -3.63287354 -4.92651978 0.84383545\n", - " 1.63409424]\n", - "score for next parameter: -0.8622472848788638 \n", + "next parameter: [35.93976104 -3.31832619 2.34293083 -9.17399315 -0.70438412 0.83299588\n", + " 1.92984919]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 6 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [50.44024658 -1.76837769 -7.89916992 -5.62799072 -4.35610962 0.83504639\n", - 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"next parameter: [45.22140503 -0.11026306 -9.40612793 -3.64852905 -5.36567078 0.95856323\n", - " 1.74954224]\n", - "score for next parameter: -0.9435018919848641 \n", + "next parameter: [43.08117676 -0.8425415 -2.87841797 -9.23425293 -5.06011963 0.99611816\n", + " 1.0098877 ]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 10 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [20.27696505 -5.48194447 -8.70541165 -7.41702071 -3.24336578 0.86186647\n", - " 2.90761422]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [11.67932129 -0.13673096 -0.56396484 -6.83044434 -5.38565674 0.93449707\n", + " 2.04553223]\n", + "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 11 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [72.28952026 -0.64466248 -7.39929199 -3.6902771 -5.5025116 0.94943237\n", - 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"next parameter: [33.67364502 -0.54113159 -0.84838867 -3.33404541 -4.63843384 0.90125732\n", - " 1.01885986]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [10.44491577 -0.7620575 -3.14880371 -2.74435425 -4.47188416 0.91640015\n", + " 2.10366821]\n", + "score for next parameter: -0.9593748259537733 \n", "\n", "iteration 15 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [88.57064819 -1.34831238 -1.51306152 -3.02340698 -5.85901794 0.91410522\n", - " 1.36026001]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [18.3340623 -5.20831098 -9.34621063 -5.03040926 -1.16238501 0.89684234\n", + " 2.9677441 ]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 16 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", @@ -1236,273 +1236,292 @@ "iteration 17 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [53.05706787 -0.26817017 -4.06860352 -3.04949951 -5.36080933 0.87476807\n", - " 1.78094482]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [17.50807616 -3.63641938 -0.81516959 -6.73703575 -2.78494567 0.90551361\n", + " 1.54231583]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 18 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [21.12237549 -1.26422729 -3.22143555 -1.47515869 -5.78213501 0.96776123\n", - " 2.03692627]\n", - "score for next parameter: -0.9527221648893477 \n", + "next parameter: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 19 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [31.55709839 -1.48587341 0.84289551 -4.37582397 -5.16833191 0.91466675\n", - " 1.7986145 ]\n", - "score for next parameter: -0.9420227920227919 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [81.91250527 -4.80353203 -3.26054911 -1.17464316 -0.94771943 0.89426076\n", + " 2.25230734]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 20 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [44.56719971 -1.41115112 -4.81323242 -1.28619385 -4.89771118 0.92215576\n", - " 1.25616455]\n", - "score for next parameter: -0.9523280423280424 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 5.86547852 -0.61999512 -6.70410156 -3.41918945 -2.64812012 0.9715332\n", + " 1.14868164]\n", + "score for next parameter: -0.5563076923076923 \n", "\n", "iteration 21 -----\n", - 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"current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [87.08758545 -1.95203247 -3.0090332 -3.2802124 -5.0684021 0.89591064\n", - " 1.652771 ]\n", - "score for next parameter: -0.9602801120448179 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [46.02362061 -2.04133911 -0.63598633 -1.68499756 -5.24413452 0.95479736\n", + " 1.79779053]\n", + "score for next parameter: -0.8548705096073517 \n", "\n", "iteration 30 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [93.0382248 -2.75412712 0.52006781 -5.57328548 -2.8378411 0.98536228\n", - " 2.88598003]\n", - "score for next parameter: -0.6377657527657528 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [43.95443726 -1.88415222 -2.23571777 -6.35446167 -3.91731873 0.92445679\n", + " 3.25576782]\n", + "score for next parameter: -0.9685173718610252 \n", "\n", "iteration 31 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [71.36386837 -4.10036573 6.97359411 -9.02428174 -2.52055746 0.93959145\n", - " 1.15576259]\n", - "score for next parameter: -0.17575757575757572 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [97.084198 -1.80132751 -1.52526855 -6.5093689 -4.84999695 0.94205933\n", + " 1.72756958]\n", + "score for next parameter: -0.9680687830687831 \n", "\n", "iteration 32 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [45.95553589 -1.90071716 -5.87585449 -5.85238647 -4.75348816 0.96935425\n", - " 2.384552 ]\n", - "score for next parameter: -0.9601513587891297 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [87.08758545 -1.95203247 -3.0090332 -3.2802124 -5.0684021 0.89591064\n", + " 1.652771 ]\n", + "score for next parameter: -0.9602801120448179 \n", "\n", "iteration 33 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [63.32794828 -0.30289793 0.99469241 -2.74332929 -2.84288681 0.8113242\n", - " 2.69867417]\n", - "score for next parameter: -0.9118212197159565 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [21.82098389 -1.31248169 -3.65356445 -5.83782959 -4.48646851 0.88594971\n", + " 1.73773193]\n", + "score for next parameter: -0.9602801120448179 \n", "\n", "iteration 34 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [26.27313232 -1.22605591 1.4050293 -3.08685303 -5.61000366 0.94552002\n", - " 3.40472412]\n", - "score for next parameter: -0.8517489046900814 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [31.565979 -1.90521851 -1.00952148 -3.15606689 -4.93084106 0.98597412\n", + " 1.66998291]\n", + "score for next parameter: -0.9247601910759805 \n", "\n", "iteration 35 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [13.42880249 -1.3007782 -3.02185059 -3.93527222 -5.37359314 0.94130249\n", - " 2.83755493]\n", - "score for next parameter: -0.9515861549298081 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [28.30957421 -5.06259382 -8.09861429 -9.34766392 -1.41627948 0.83583128\n", + " 1.66314507]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 36 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [34.35449219 -0.97001953 -6.66015625 -2.52050781 -3.43603516 0.91425781\n", - " 2.09863281]\n", - "score for next parameter: -0.8505446623093682 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [20.50665283 -1.14611206 -7.19604492 -8.96783447 -4.51743774 0.91864014\n", + " 2.41046143]\n", + "score for next parameter: -0.8373871770930595 \n", "\n", "iteration 37 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [45.9644165 -1.49037476 6.02172852 -8.57012939 -4.60818481 0.92816162\n", - " 1.13092041]\n", - "score for next parameter: -0.8436096651886127 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [76.13778687 -0.98964539 -6.26403809 -7.85519409 -4.85503845 0.84872437\n", + " 1.98794556]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 38 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", - "score for next parameter: -0.9763060428849902 \n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [35.77539062 -1.05644531 -1.6796875 -5.30664062 -5.29707031 0.93632812\n", + " 1.14648438]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 39 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [79.45617676 -0.1050415 -5.37841797 -5.85925293 -5.79761963 0.87111816\n", - " 3.6348877 ]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [34.35449219 -0.97001953 -6.66015625 -2.52050781 -3.43603516 0.91425781\n", + " 2.09863281]\n", + "score for next parameter: -0.8505446623093682 \n", "\n", "iteration 40 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [72.64770508 -0.2454834 -3.87207031 -5.83618164 -4.60134277 0.94633789\n", - " 2.33520508]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [75.58126831 -1.95689392 -3.9276123 -2.38729858 -4.90185242 0.90202026\n", + " 1.03323364]\n", + "score for next parameter: -0.9602801120448179 \n", "\n", "iteration 41 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [50.8193283 -3.05975379 -6.27466769 -6.83094636 -3.91334651 0.89702417\n", - " 2.40270554]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [ 6.11117554 -1.6162323 -3.63220215 -3.76608276 -3.98934021 0.99642944\n", + " 2.20254517]\n", + "score for next parameter: -0.6544548784548785 \n", "\n", "iteration 42 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [96.48031616 -1.55861511 -6.01501465 -6.17428589 -5.59109802 0.94838257\n", - " 2.33731079]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [18.34004701 -2.09680433 7.53517739 -7.51198309 -0.44065179 0.88448689\n", + " 2.21917284]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 43 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [58.42095947 -1.06688843 -4.76928711 -8.75909424 -5.76917114 0.95560303\n", - " 3.70465088]\n", - "score for next parameter: -0.9763060428849902 \n", + "next parameter: [ 3.7153757 -0.54264509 -7.58613214 -5.06055548 -0.84674669 0.86606726\n", + " 2.55714102]\n", + "score for next parameter: -0.583122507122507 \n", "\n", "iteration 44 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [16.06723322 -1.88451362 -2.99815455 -5.95832332 -5.56295557 0.86632232\n", - " 1.36581272]\n", - "score for next parameter: -0.9252168883747831 \n", + "next parameter: [79.22528076 -1.11658325 -4.86450195 -6.41790771 -4.86674194 0.99259033\n", + " 1.89593506]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 45 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [89.00908248 -0.9280715 7.76992743 -8.53901055 -0.27853035 0.96162671\n", - " 1.84533372]\n", - "score for next parameter: -0.6223212343212342 \n", + "next parameter: [88.21246338 -1.29447632 -2.92358398 -3.80645752 -3.928302 0.9605835\n", + " 1.14849854]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 46 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [86.29721069 -1.67096863 6.45568848 -8.43746948 -5.53636169 0.96879272\n", - " 1.52432251]\n", - "score for next parameter: -0.8755062870852344 \n", + "next parameter: [89.26795476 -1.9373047 -3.79085411 -8.26376342 -2.26006856 0.97236419\n", + " 2.19545 ]\n", + "score for next parameter: -0.9515861549298081 \n", "\n", "iteration 47 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [79.8291626 -0.50223999 -6.05834961 -7.15948486 -3.91389771 0.99974365\n", - " 2.362854 ]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [34.81126277 -5.45807985 -6.70723536 -4.40920268 -4.24782511 0.99682821\n", + " 3.73510775]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 48 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [39.38684082 -0.64088135 -7.42919922 -4.65515137 -4.69713135 0.92053223\n", - " 3.64953613]\n", - "score for next parameter: -0.879540927482104 \n", + "next parameter: [36.10693359 -1.35893555 -7.52929688 -6.25146484 -3.98051758 0.98740234\n", + " 1.52294922]\n", + "score for next parameter: -0.8773511455864398 \n", "\n", "iteration 49 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [33.37298024 -1.53918059 -7.67205338 -2.09071315 -3.16740687 0.84715434\n", - " 2.65307455]\n", - "score for next parameter: -0.827206273258905 \n", + "next parameter: [42.84140015 -1.16537781 -4.90661621 -7.75411987 -4.32207947 0.94882202\n", + " 2.39077759]\n", + "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 50 -----\n", - "current minimum: [47.23138428 -1.37730103 -3.31665039 -3.64276123 -4.83937378 0.98052979\n", - " 3.84490967]\n", + "current minimum: [96.06958484 -0.2866771 -1.28794547 -6.56640029 -1.79288589 0.9167581\n", + " 3.53500752]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [60.96673584 -2.02837524 -2.67211914 -5.58514404 -3.88869019 0.99049072\n", - " 3.94744873]\n", - "score for next parameter: -0.9685173718610252 \n", + "next parameter: [12.57431669 -0.36696139 6.24173089 -9.82896983 -1.69082019 0.83776172\n", + " 2.84046913]\n", + "score for next parameter: -0.8213828689370486 \n", "\n", "Global iteration #3 -----\n", - "current minimum: [92.69421387 -0.18426514 -3.96728516 -8.28283691 -5.82498779 0.90856934\n", - " 3.56970215]\n", + "current minimum: [81.59640503 -0.84776306 -1.90612793 -2.52352905 -4.62817078 0.88356323\n", + " 3.62454224]\n", "current minimum score: -0.9763060428849902\n", "score for next parameter: -0.9763060428849902 \n", "\n", - "{'parameters': DescribeResult(best_params=array([92.69421387, -0.18426514, -3.96728516, -8.28283691, -5.82498779,\n", - " 0.90856934, 3.56970215]), best_score=-0.9763060428849902, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=100, type_pi='kde')), 'opt_object': }\n", + "{'parameters': DescribeResult(best_params=array([81.59640503, -0.84776306, -1.90612793, -2.52352905, -4.62817078,\n", + " 0.88356323, 3.62454224]), best_score=-0.9763060428849902, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=150, type_pi='kde')), 'opt_object': }\n", " |======================================================================| 100%\n", "\n", - " Elapsed: 2.603921890258789\n", - "\n", "\n", " Test set accuracy: 0.9666666666666667\n", "\n", - " Elapsed: 0.024235010147094727\n" + " Elapsed: 1640.6403279304504\n" ] } ], "source": [ + "start = time()\n", "for elt in datasets:\n", "\n", " dataset = elt()\n", @@ -1517,9 +1536,6 @@ " res1 = optimize_bcn(X_train, y_train)\n", " print(res1)\n", " parameters = res1[\"parameters\"]\n", - " start = time()\n", - "\n", - " start = time()\n", " estimator = bcn.BCNClassifier(B=int(parameters[0][0]),\n", " nu=10**parameters[0][1],\n", " lam=10**parameters[0][2],\n", @@ -1529,10 +1545,8 @@ " n_clusters=np.ceil(parameters[0][6]),\n", " activation=\"tanh\",\n", " type_optim=\"nlminb\").fit(X_train, y_train)\n", - " print(f\"\\n Elapsed: {time() - start}\")\n", - " start = time()\n", - " print(f\"\\n\\n Test set accuracy: {estimator.score(X_test, y_test)}\")\n", - " print(f\"\\n Elapsed: {time() - start}\")" + " print(f\"\\n\\n Test set accuracy: {estimator.score(X_test, y_test)}\") \n", + " print(f\"\\n Elapsed: {time() - start}\") " ] }, { @@ -1626,20 +1640,75 @@ "iteration 1 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9467825589704711\n", - "next parameter: [44.81585693 -0.22783813 -6.11938477 -3.1461792 -4.42164917 0.91676025\n", - " 1.53778076]\n", - "score for next parameter: -1.0 \n", + "next parameter: [25.25482178 -0.68589478 -8.78540039 -5.40057373 -4.60890503 0.93834229\n", + " 1.52459717]\n", + "score for next parameter: -0.9115434958743615 \n", "\n", - "{'parameters': DescribeResult(best_params=array([44.81585693, -0.22783813, -6.11938477, -3.1461792 , -4.42164917,\n", - " 0.91676025, 1.53778076]), best_score=-1.0, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=100, type_pi='bootstrap')), 'opt_object': }\n", - " |======================================================================| 100%\n", + "iteration 2 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [21.75289917 -1.17185974 -8.58093262 -1.59408569 -3.98429871 0.8882019\n", + " 1.14968872]\n", + "score for next parameter: -0.8703990911365164 \n", "\n", - " Elapsed: 1.3154151439666748\n", + "iteration 3 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [ 6.02532959 -1.26782837 -5.56274414 -2.94842529 -5.06408081 0.93502197\n", + " 1.66229248]\n", + "score for next parameter: -0.7336965299744204 \n", + "\n", + "iteration 4 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [18.25097656 -0.63583984 -5.29296875 -8.69042969 -3.65498047 0.94433594\n", + " 2.37402344]\n", + "score for next parameter: -0.9467825589704711 \n", + "\n", + "iteration 5 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [27.53121948 -0.14051208 -8.60046387 -8.49349976 -0.48693542 0.93253784\n", + " 1.82058716]\n", + "score for next parameter: -0.6457346121444794 \n", + "\n", + "iteration 6 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [26.09552002 -1.37081909 -4.28588867 -9.66217041 -3.43999634 0.95438232\n", + " 2.19073486]\n", + "score for next parameter: -0.9467825589704711 \n", + "\n", + "iteration 7 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [ 4.75961374 -5.93055824 -3.35033501 -7.81930084 -5.3436628 0.9203518\n", + " 2.84529444]\n", + "score for next parameter: -0.1932624557014801 \n", + "\n", + "iteration 8 -----\n", + "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", + "current minimum score: -0.9467825589704711\n", + "next parameter: [11.84509277 -1.16663818 -4.52392578 -5.85266113 -2.38812256 0.95124512\n", + " 1.11022949]\n", + "score for next parameter: -0.9782738977419285 \n", + "\n", + "iteration 9 -----\n", + "current minimum: [11.84509277 -1.16663818 -4.52392578 -5.85266113 -2.38812256 0.95124512\n", + " 1.11022949]\n", + "current minimum score: -0.9782738977419285\n", + "next parameter: [20.69906616 -0.26799011 -6.64001465 -7.58053589 -2.45672302 0.92963257\n", + " 1.68106079]\n", + "score for next parameter: -1.0 \n", + "\n", + "{'parameters': DescribeResult(best_params=array([20.69906616, -0.26799011, -6.64001465, -7.58053589, -2.45672302,\n", + " 0.92963257, 1.68106079]), best_score=-1.0, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=150, type_pi='bootstrap')), 'opt_object': }\n", + " |======================================================================| 100%\n", "\n", "\n", " Test set accuracy: 0.9722222222222222\n", "\n", - " Elapsed: 0.026901960372924805\n", + " Elapsed: 127.63698601722717\n", "\n", " adjusting surrogate model # 1 (CustomRegressor(BaggingRegressor))... \n", "\n", @@ -1658,374 +1727,398 @@ "iteration 1 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [52.04171753 -0.43291931 -5.18737793 -2.03134155 -4.76645203 0.84762573\n", - " 1.02297974]\n", + "next parameter: [92.09921265 -0.19740906 -4.43786621 -2.19943237 -4.82911072 0.80975952\n", + " 1.52359009]\n", "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 2 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [21.75289917 -1.17185974 -8.58093262 -1.59408569 -3.98429871 0.8882019\n", - " 1.14968872]\n", - "score for next parameter: -0.8497354497354497 \n", + "next parameter: [54.44836426 -1.16519775 -2.40966797 -7.61706543 -5.84371338 0.81018066\n", + " 1.7364502 ]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 3 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", - " 1.00860596]\n", - "score for next parameter: -0.9589390961062788 \n", + "next parameter: [47.77902222 -1.75235291 -7.12097168 -3.71005249 -3.7120575 0.82125854\n", + " 3.90286255]\n", + "score for next parameter: -0.8085592185592185 \n", "\n", "iteration 4 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [35.56853541 -4.40801453 -7.07957581 -6.35220533 -1.74074379 0.89003471\n", - " 3.937929 ]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [76.31539917 -1.54060974 0.16906738 -8.90658569 -5.82804871 0.8007019\n", + " 3.58718872]\n", + "score for next parameter: -0.952436974789916 \n", "\n", "iteration 5 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [24.36972046 -0.88305359 -4.18395996 -3.19259644 -5.81436462 0.98104858\n", - " 1.08120728]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [47.68725586 -1.87316895 -1.36230469 -9.48803711 -5.08244629 0.92612305\n", + " 1.94995117]\n", + "score for next parameter: -0.9499748617395676 \n", "\n", "iteration 6 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [41.74020386 -1.7422699 -1.60827637 -2.14779663 -5.22306824 0.99308472\n", - " 1.31082153]\n", - "score for next parameter: -0.9602801120448179 \n", + "next parameter: [ 7.33078003 -4.07432556 -3.46862793 -8.00790405 -4.72035828 0.95543823\n", + " 2.92141724]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 7 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [ 4.75961374 -5.93055824 -3.35033501 -7.81930084 -5.3436628 0.9203518\n", - " 2.84529444]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [71.58203125 -0.76835937 -1.640625 -9.47265625 -4.13320312 0.80390625\n", + " 2.51171875]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 8 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [86.23144474 -1.26062895 2.30159918 -9.94778117 -4.96713712 0.85116269\n", - " 3.56545594]\n", - "score for next parameter: -0.8234725829153074 \n", + "next parameter: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 9 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [64.65515137 -1.15223389 -8.18603516 -9.75939941 -5.77889404 0.97263184\n", - " 1.06188965]\n", - "score for next parameter: -0.8552941995511656 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [45.22140503 -0.11026306 -9.40612793 -3.64852905 -5.36567078 0.95856323\n", + " 1.74954224]\n", + "score for next parameter: -0.9435018919848641 \n", "\n", "iteration 10 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [33.67364502 -0.54113159 -0.84838867 -3.33404541 -4.63843384 0.90125732\n", - " 1.01885986]\n", - "score for next parameter: -0.9599498746867168 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [37.8001709 -1.08597412 -1.04736328 -1.19445801 -4.8887085 0.80397949\n", + " 2.03015137]\n", + "score for next parameter: -0.9605653021442496 \n", "\n", "iteration 11 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [70.75021362 -1.09839783 -6.64245605 -8.77694702 -2.04980164 0.9369812\n", - " 1.07717896]\n", - "score for next parameter: -0.9599498746867168 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [54.24707031 -0.98154297 -9.27734375 -8.86621094 -2.89443359 0.96855469\n", + " 2.94824219]\n", + "score for next parameter: -0.7987501433321866 \n", "\n", "iteration 12 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [90.40301514 -0.78240356 -7.79418945 -7.91204834 -5.75404663 0.94454346\n", - " 1.81976318]\n", - "score for next parameter: -0.9599498746867168 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 6.62921143 -1.30455933 -1.2097168 -8.831604 -5.20020142 0.99412842\n", + " 3.10040283]\n", + "score for next parameter: -0.9517495536226187 \n", "\n", "iteration 13 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [57.71051025 -0.91420288 2.66235352 -9.02716064 -1.17420044 0.92269287\n", - " 1.07232666]\n", - "score for next parameter: -0.8031873146919587 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 9.53613281 -1.21201172 -4.12109375 -7.81152344 -5.98271484 0.92011719\n", + " 1.56542969]\n", + "score for next parameter: -0.9602801120448179 \n", "\n", "iteration 14 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [84.92663574 -0.8180542 -9.86572266 -1.30432129 -5.92869873 0.99255371\n", - " 1.53649902]\n", - "score for next parameter: -0.9038725899716612 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [73.67785645 -0.23756104 -3.24951172 -9.66491699 -5.58443604 0.81311035\n", + " 1.49914551]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 15 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [19.15975952 -1.47651062 -7.44567871 -2.4982605 -5.09414978 0.9421814\n", - " 1.31851196]\n", - "score for next parameter: -0.5868205128205128 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 4.5748291 -0.74171143 -8.59130859 -7.22595215 -4.75762939 0.99875488\n", + " 1.80822754]\n", + "score for next parameter: -0.5967955786903155 \n", "\n", "iteration 16 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [31.31140137 -1.70535889 -2.56103516 -4.41564941 -5.59451904 0.99138184\n", - " 2.09313965]\n", - "score for next parameter: -0.9601513587891297 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [83.84320068 -0.29697876 -4.94750977 -7.89227295 -3.89157104 0.8050415\n", + " 1.59637451]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 17 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [61.55581665 -0.45416565 -3.27697754 -6.21987915 -4.81578674 0.92693481\n", - " 1.96505737]\n", - "score for next parameter: -0.9599498746867168 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [36.97131348 -0.47667236 6.99462891 -9.91540527 -5.16094971 0.89055176\n", + " 3.33752441]\n", + "score for next parameter: -0.828478656419833 \n", "\n", "iteration 18 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [15.90649414 -0.2166748 2.00683594 -3.26098633 -5.05651855 0.98598633\n", - " 1.45922852]\n", - "score for next parameter: -0.9241715147597501 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [37.41830444 -1.46354675 -7.68493652 -7.76950073 -5.42112732 0.80082397\n", + " 1.02041626]\n", + "score for next parameter: -0.8744472291840714 \n", "\n", "iteration 19 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", "next parameter: [81.91250527 -4.80353203 -3.26054911 -1.17464316 -0.94771943 0.89426076\n", " 2.25230734]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 20 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [77.43731689 -1.19796753 -2.99682617 -9.08209229 -5.2722229 0.8727417\n", - " 1.27081299]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [78.20697021 -0.40357056 -2.55493164 -3.24725342 -4.59161987 0.8166626\n", + " 1.17596436]\n", "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 21 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [77.18461444 -1.55721418 -0.92942319 -4.17010123 -4.20746241 0.97039887\n", - " 1.73840401]\n", - "score for next parameter: -0.9680687830687831 \n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [69.03033447 -1.52782593 1.16821289 -9.74346924 -4.93948364 0.86497803\n", + " 3.09527588]\n", + "score for next parameter: -0.9197504444872866 \n", "\n", "iteration 22 -----\n", - 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" 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [97.43942261 -0.98172302 -8.87390137 -6.26107788 -4.09377136 0.93136597\n", - " 3.54910278]\n", - "score for next parameter: -0.7987501433321866 \n", + "next parameter: [61.94064331 -1.49595642 -2.9901123 -4.77792358 -4.44091492 0.86139526\n", + " 3.61135864]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 46 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [89.26795476 -1.9373047 -3.79085411 -8.26376342 -2.26006856 0.97236419\n", - " 2.19545 ]\n", - "score for next parameter: -0.9515861549298081 \n", + "next parameter: [28.40447998 -1.1770813 -4.26879883 -1.94866943 -5.57831421 0.87862549\n", + " 3.4911499 ]\n", + "score for next parameter: -0.9605653021442496 \n", "\n", "iteration 47 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [34.81126277 -5.45807985 -6.70723536 -4.40920268 -4.24782511 0.99682821\n", - " 3.73510775]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [87.96380615 -0.37476196 -0.54321289 -9.32049561 -5.47316284 0.84654541\n", + " 3.67498779]\n", + "score for next parameter: -0.9680687830687831 \n", "\n", "iteration 48 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [47.87078857 -1.15691528 -1.1730957 -2.77044678 -3.78930054 0.86973877\n", - " 1.02581787]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [58.64001465 -0.78636475 1.68701172 -9.38586426 -5.87972412 0.86569824\n", + " 3.28405762]\n", + "score for next parameter: -0.9197504444872866 \n", "\n", "iteration 49 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [70.32394409 -0.79590759 -6.14440918 -5.90731812 -4.50717468 0.89743042\n", - " 2.94778442]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [33.37298024 -1.53918059 -7.67205338 -2.09071315 -3.16740687 0.84715434\n", + " 2.65307455]\n", + "score for next parameter: -0.827206273258905 \n", "\n", "iteration 50 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [23.44317627 -1.57824097 -1.39526367 -4.28326416 -2.44898071 0.96610107\n", - " 1.56964111]\n", - "score for next parameter: -0.9515621633268692 \n", + "next parameter: [34.48178101 -0.38610535 -2.00134277 -3.71774292 -5.7841156 0.87523804\n", + " 3.66592407]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "Global iteration #1 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", "score for next parameter: -0.9763060428849902 \n", "\n", @@ -2044,51 +2137,51 @@ "iteration 1 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [44.81585693 -0.22783813 -6.11938477 -3.1461792 -4.42164917 0.91676025\n", - " 1.53778076]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [24.96472168 -1.58436279 -6.05712891 -2.03381348 -5.73856201 0.94938965\n", + " 2.76989746]\n", + "score for next parameter: -0.9685173718610252 \n", "\n", "iteration 2 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [82.9788208 -0.99342651 -9.5300293 -3.78668213 -5.8109436 0.88983154\n", - " 2.45001221]\n", - "score for next parameter: -0.7987501433321866 \n", + "next parameter: [11.72668457 -0.80220947 -8.91357422 -3.63562012 -4.07486572 0.98537598\n", + " 2.41906738]\n", + "score for next parameter: -0.8595710240911479 \n", "\n", "iteration 3 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", - " 1.00860596]\n", - "score for next parameter: -0.9589390961062788 \n", + "next parameter: [12.19439697 -3.32548218 -6.48803711 -1.23565674 -5.81526489 0.84779053\n", + " 1.80621338]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 4 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [35.56853541 -4.40801453 -7.07957581 -6.35220533 -1.74074379 0.89003471\n", - " 3.937929 ]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [29.02316284 -1.51036072 -7.94128418 -3.41122437 -4.11537781 0.94508667\n", + " 2.20950317]\n", + "score for next parameter: -0.7987501433321866 \n", "\n", "iteration 5 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [24.79598999 -1.53124695 -5.05310059 -8.36495972 -4.49781189 0.93036499\n", - " 1.45474243]\n", - "score for next parameter: -0.9602801120448179 \n", + "next parameter: [24.36972046 -0.88305359 -4.18395996 -3.19259644 -5.81436462 0.98104858\n", + " 1.08120728]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 6 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [12.30096436 -1.64954224 8.81713867 -6.36077881 -4.76015015 0.84307861\n", - " 1.57513428]\n", - "score for next parameter: -0.7546547655243308 \n", + "next parameter: [81.04082666 -1.20941908 -7.65014289 -6.15055122 -2.96474279 0.86446771\n", + " 2.67164216]\n", + "score for next parameter: -0.8173744819565254 \n", "\n", "iteration 7 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [34.75411987 -1.3058197 -4.53308105 -9.37460327 -4.37753601 0.91744995\n", - " 1.13577271]\n", - "score for next parameter: -0.9680687830687831 \n", + "next parameter: [ 4.75961374 -5.93055824 -3.35033501 -7.81930084 -5.3436628 0.9203518\n", + " 2.84529444]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 8 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", @@ -2100,328 +2193,341 @@ "iteration 9 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [79.95349121 -0.7114624 -7.62939453 -9.55285645 -3.6614624 0.9791748\n", - " 1.18933105]\n", - "score for next parameter: -0.9521067374318148 \n", + "next parameter: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 10 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "current minimum score: -0.9763060428849902\n", "next parameter: [20.27696505 -5.48194447 -8.70541165 -7.41702071 -3.24336578 0.86186647\n", " 2.90761422]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 11 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [14.62768555 -1.23361816 7.17285156 -9.05737305 -3.3020752 0.93959961\n", - 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"current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [25.49163818 -0.25088501 -0.41625977 -6.13446045 -3.29235229 0.987854\n", - " 1.15106201]\n", - "score for next parameter: -0.9577635327635328 \n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [88.07629395 -0.65240479 -4.34326172 -3.12585449 -0.83677979 0.94592285\n", + " 1.66320801]\n", + "score for next parameter: -0.9680687830687831 \n", "\n", "iteration 14 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [56.13568115 -1.20444946 -4.60571289 -4.11737061 -4.45910034 0.89967041\n", - " 2.50311279]\n", - "score for next parameter: -0.9515316886988714 \n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 3.41948841 -1.51446798 2.47332694 -4.49869456 -1.32837366 0.82960593\n", + " 3.54826113]\n", + "score for next parameter: -0.26623712581636844 \n", "\n", "iteration 15 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [74.37646484 -0.36791992 2.39257812 -9.87255859 -4.6949707 0.93505859\n", - " 1.04248047]\n", - "score for next parameter: -0.9179418380037575 \n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [74.48007202 -1.15385437 -2.28942871 -2.849823 -2.28243103 0.9968689\n", + " 2.65444946]\n", + "score for next parameter: -0.951255917571707 \n", "\n", "iteration 16 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [32.23202515 -1.62631531 -3.34411621 -5.92599487 -5.15176697 0.88944702\n", - " 3.00015259]\n", - "score for next parameter: -0.9685173718610252 \n", - "\n", - "iteration 17 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - 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"current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", - "score for next parameter: -0.9763060428849902 \n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [22.64096069 -1.11784363 2.08068848 -3.65621948 -5.72073669 0.98754272\n", + " 2.36807251]\n", + "score for next parameter: -0.8224974200206399 \n", "\n", "iteration 23 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [44.34003693 -1.63440122 -6.86964265 -8.83658586 -4.06036562 0.99535025\n", - 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" 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [62.13305664 -1.46120605 -3.46191406 -5.72192383 -3.2588623 0.95629883\n", - " 1.48266602]\n", - "score for next parameter: -0.9680687830687831 \n", + "next parameter: [28.57321167 -0.57264099 0.32531738 -1.10189819 -3.10851746 0.9397644\n", + " 2.57937622]\n", + "score for next parameter: -0.9278933444722919 \n", "\n", "iteration 26 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [50.62081909 -0.70372009 -1.45690918 -4.36044312 -4.78373718 0.91930542\n", - " 1.40090942]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [41.10375977 -0.91960449 -4.75097656 -6.2668457 -5.85163574 0.86293945\n", + " 2.07446289]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 27 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [38.31820679 -1.63927917 -7.92907715 -8.93405151 -3.64363708 0.92377319\n", - " 1.83926392]\n", - "score for next parameter: -0.8407557354925776 \n", + "next parameter: [53.04818726 -0.96227722 -6.61071777 -1.01071167 -4.47044373 0.94320679\n", + " 2.78701782]\n", + "score for next parameter: -0.8960237194292923 \n", "\n", "iteration 28 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [25.16601562 -0.41113281 -3.2421875 -8.25976562 -4.28300781 0.98320312\n", - " 2.22460938]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [15.88873291 -1.41835327 -6.97631836 -1.63116455 -2.13352661 0.93118896\n", + " 2.82281494]\n", + "score for next parameter: -0.8175634993026296 \n", "\n", "iteration 29 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [10.81355089 -1.75108923 -0.82173819 -8.17357112 -3.27869316 0.94957804\n", - " 1.75159858]\n", - "score for next parameter: -0.5898696890870804 \n", + "next parameter: [96.86218262 -1.17528076 -2.79541016 -4.02893066 -4.69569092 0.94528809\n", + " 1.4251709 ]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 30 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [93.0382248 -2.75412712 0.52006781 -5.57328548 -2.8378411 0.98536228\n", " 2.88598003]\n", "score for next parameter: -0.6377657527657528 \n", "\n", "iteration 31 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [58.92419434 -0.88431396 -1.34033203 -5.52746582 -4.75618896 0.97331543\n", - " 2.53112793]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [88.37823486 -0.74567261 -2.16674805 -4.37554932 -0.83858032 0.92518311\n", + " 2.08966064]\n", + "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 32 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [36.39274637 -5.06301976 -7.24479204 -2.74657433 -1.66871527 0.8429524\n", " 3.9728427 ]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 33 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [38.7947998 -1.43455811 -4.37744141 -7.6060791 -5.7961792 0.89431152\n", - " 1.45153809]\n", - "score for next parameter: -0.9680687830687831 \n", + "next parameter: [80.62841797 -0.72514648 -2.02148438 -4.08935547 -1.94086914 0.99716797\n", + " 1.10693359]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 34 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [98.4251709 -0.34847412 -8.54736328 -4.56945801 -5.6262085 0.92897949\n", - " 3.15515137]\n", - "score for next parameter: -0.9365686274509806 \n", + "next parameter: [88.21246338 -1.29447632 -2.92358398 -3.80645752 -3.928302 0.9605835\n", + " 1.14849854]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 35 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [28.30957421 -5.06259382 -8.09861429 -9.34766392 -1.41627948 0.83583128\n", " 1.66314507]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 36 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [69.82824076 -3.88455314 -6.66694252 -3.2741885 -2.79463632 0.85075364\n", - " 1.9297718 ]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [20.93588257 -0.66842957 -2.64587402 -3.95504761 -1.19202576 0.97855835\n", + " 1.30752563]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 37 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [88.0132581 -3.76422671 6.57971842 -5.82198753 -4.33375148 0.8005958\n", - " 2.77675216]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [87.56417847 -0.48477478 -2.19909668 -5.71395874 -1.79916687 0.93297729\n", + " 1.7817688 ]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 38 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [80.79418945 -1.31716309 -3.05175781 -5.22094727 -4.75114746 0.91391602\n", - " 2.0480957 ]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [57.55570745 -5.98347499 -9.89074106 -5.24899638 -5.85711424 0.87713217\n", + " 1.99379545]\n", + "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 39 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [70.30914307 -1.48461304 -3.60717773 -7.24298096 -5.42058716 0.91585693\n", - " 2.46392822]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [58.02133179 -1.73146667 -4.49157715 -2.88717651 -5.57957458 0.89564819\n", + " 3.29238892]\n", + "score for next parameter: -0.9685173718610252 \n", "\n", "iteration 40 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [62.48532104 -1.32166443 -4.24499512 -7.06088257 -5.47082214 0.91046753\n", - " 2.1164856 ]\n", + "next parameter: [49.68243408 -1.16915894 -1.80541992 -3.72955322 -3.38814087 0.98973389\n", + " 2.04718018]\n", "score for next parameter: -0.9515316886988714 \n", "\n", "iteration 41 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [50.8193283 -3.05975379 -6.27466769 -6.83094636 -3.91334651 0.89702417\n", " 2.40270554]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 42 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [18.34004701 -2.09680433 7.53517739 -7.51198309 -0.44065179 0.88448689\n", - " 2.21917284]\n", - "score for next parameter: -0.17575757575757572 \n", + "next parameter: [66.44903564 -0.71398315 -6.19995117 -2.85943604 -2.85230103 0.96727295\n", + " 1.75128174]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 43 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [ 3.7153757 -0.54264509 -7.58613214 -5.06055548 -0.84674669 0.86606726\n", - " 2.55714102]\n", - "score for next parameter: -0.583122507122507 \n", + "next parameter: [90.36157227 -0.32038574 -4.59472656 -5.2121582 -3.13210449 0.97700195\n", + " 1.01977539]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 44 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [16.06723322 -1.88451362 -2.99815455 -5.95832332 -5.56295557 0.86632232\n", " 1.36581272]\n", "score for next parameter: -0.9252168883747831 \n", "\n", "iteration 45 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [89.00908248 -0.9280715 7.76992743 -8.53901055 -0.27853035 0.96162671\n", - " 1.84533372]\n", - "score for next parameter: -0.6223212343212342 \n", + "next parameter: [70.48675537 -1.23613892 -1.72485352 -3.40106201 -1.62721558 0.93883057\n", + " 1.61688232]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 46 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [89.26795476 -1.9373047 -3.79085411 -8.26376342 -2.26006856 0.97236419\n", " 2.19545 ]\n", "score for next parameter: -0.9515861549298081 \n", "\n", "iteration 47 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [34.81126277 -5.45807985 -6.70723536 -4.40920268 -4.24782511 0.99682821\n", " 3.73510775]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 48 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [21.99268954 -2.8553348 4.28831457 -9.26887409 -1.73455867 0.94088029\n", " 2.90010999]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 49 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [33.37298024 -1.53918059 -7.67205338 -2.09071315 -3.16740687 0.84715434\n", " 2.65307455]\n", "score for next parameter: -0.827206273258905 \n", "\n", "iteration 50 -----\n", - "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", - " 3.0592041 ]\n", + "current minimum: [35.4498724 -0.6684831 -0.75697184 -3.47174887 -3.14412904 0.92486437\n", + " 3.34970469]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [12.57431669 -0.36696139 6.24173089 -9.82896983 -1.69082019 0.83776172\n", - " 2.84046913]\n", - "score for next parameter: -0.8213828689370486 \n", + "next parameter: [79.75811768 -0.8666687 -0.5065918 -4.92926025 -2.54981079 0.96522217\n", + " 1.04962158]\n", + "score for next parameter: -0.9680687830687831 \n", "\n", "Global iteration #2 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", "score for next parameter: -0.9763060428849902 \n", "\n", @@ -2440,389 +2546,421 @@ "iteration 1 -----\n", "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", "current minimum score: -0.9685185185185186\n", - "next parameter: [44.81585693 -0.22783813 -6.11938477 -3.1461792 -4.42164917 0.91676025\n", - " 1.53778076]\n", - "score for next parameter: -0.9599498746867168 \n", + "next parameter: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 2 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [17.17938232 -1.77918091 -4.2199707 -3.93060303 -3.95062866 0.97677002\n", - " 1.81097412]\n", - "score for next parameter: -0.9496446243814665 \n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [13.42880249 -1.3007782 -3.02185059 -3.93527222 -5.37359314 0.94130249\n", + " 2.83755493]\n", + "score for next parameter: -0.9515861549298081 \n", "\n", "iteration 3 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [ 4.54522705 -0.46334839 -4.1394043 -1.07965088 -4.45117798 0.92967529\n", - " 1.00860596]\n", - "score for next parameter: -0.9589390961062788 \n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 4.40609741 -0.75197449 -8.12438965 -4.24069214 -5.9828949 0.89447632\n", + " 3.09902954]\n", + "score for next parameter: -0.7166694514062935 \n", "\n", "iteration 4 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [35.56853541 -4.40801453 -7.07957581 -6.35220533 -1.74074379 0.89003471\n", - " 3.937929 ]\n", - "score for next parameter: -0.17575757575757572 \n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [ 9.08026123 -1.84544067 -1.22192383 -5.35882568 -5.50917358 0.97471924\n", + " 2.72943115]\n", + "score for next parameter: -0.6422548562548563 \n", "\n", "iteration 5 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [29.02316284 -1.51036072 -7.94128418 -3.41122437 -4.11537781 0.94508667\n", + " 2.20950317]\n", + "score for next parameter: -0.7987501433321866 \n", + "\n", + "iteration 6 -----\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", "next parameter: [24.36972046 -0.88305359 -4.18395996 -3.19259644 -5.81436462 0.98104858\n", " 1.08120728]\n", "score for next parameter: -0.9599498746867168 \n", "\n", - "iteration 6 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [81.04082666 -1.20941908 -7.65014289 -6.15055122 -2.96474279 0.86446771\n", - " 2.67164216]\n", - "score for next parameter: -0.8173744819565254 \n", - "\n", "iteration 7 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", "next parameter: [ 4.75961374 -5.93055824 -3.35033501 -7.81930084 -5.3436628 0.9203518\n", " 2.84529444]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 8 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", "next parameter: [86.23144474 -1.26062895 2.30159918 -9.94778117 -4.96713712 0.85116269\n", " 3.56545594]\n", "score for next parameter: -0.8234725829153074 \n", "\n", "iteration 9 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [34.13839722 -1.10704041 -6.18347168 -1.03817749 -5.647995 0.96813354\n", - " 1.51223755]\n", - "score for next parameter: -0.943198355365538 \n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [79.18383789 -1.39206543 -8.07128906 -2.45239258 -4.34206543 0.93520508\n", + " 1.09594727]\n", + "score for next parameter: -0.8532285842812157 \n", "\n", "iteration 10 -----\n", - "current minimum: [87.875 -0.8375 -7.5 -4.375 -3.7875 0.875 2.875 ]\n", - "current minimum score: -0.9685185185185186\n", - "next parameter: [63.88549805 -0.45002441 -8.60839844 -2.23706055 -5.00754395 0.91616211\n", - " 1.34350586]\n", - "score for next parameter: -0.9517864923747277 \n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", + "current minimum score: -0.9763060428849902\n", + "next parameter: [37.83273315 -0.767099 -4.13269043 -5.95126343 -5.28500671 0.94254761\n", + " 3.36087036]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 11 -----\n", - 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"next parameter: [45.2628479 -1.12252502 -0.23010254 -4.2159729 -5.20758362 0.88084106\n", - " 2.72677612]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [64.29696655 -0.2579071 6.48986816 -7.8991394 -4.78013611 0.93602905\n", + " 3.29165649]\n", + "score for next parameter: -0.8436483668836612 \n", "\n", "iteration 41 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [50.8193283 -3.05975379 -6.27466769 -6.83094636 -3.91334651 0.89702417\n", " 2.40270554]\n", "score for next parameter: -0.17575757575757572 \n", "\n", "iteration 42 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [31.6222229 -1.58346252 -1.79260254 -1.8253479 -4.19352112 0.93396606\n", - " 1.92990112]\n", - "score for next parameter: -0.9602801120448179 \n", + "next parameter: [45.50558472 -0.87657166 -3.21472168 -5.60848999 -4.03471375 0.95407104\n", + " 2.70755005]\n", + "score for next parameter: -0.9434127803168051 \n", "\n", "iteration 43 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [56.12680054 -0.4177948 -7.06970215 -4.46920776 -5.37215271 0.91830444\n", - " 2.06192017]\n", - "score for next parameter: -0.9434127803168051 \n", + "next parameter: [ 3.7153757 -0.54264509 -7.58613214 -5.06055548 -0.84674669 0.86606726\n", + " 2.55714102]\n", + "score for next parameter: -0.583122507122507 \n", "\n", "iteration 44 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [60.55230713 -1.45580444 -0.65795898 -4.47442627 -4.82713013 0.94573975\n", - " 2.77740479]\n", - "score for next parameter: -0.9593748259537733 \n", + "next parameter: [16.06723322 -1.88451362 -2.99815455 -5.95832332 -5.56295557 0.86632232\n", + " 1.36581272]\n", + "score for next parameter: -0.9252168883747831 \n", "\n", "iteration 45 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [89.00908248 -0.9280715 7.76992743 -8.53901055 -0.27853035 0.96162671\n", " 1.84533372]\n", "score for next parameter: -0.6223212343212342 \n", "\n", "iteration 46 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [89.26795476 -1.9373047 -3.79085411 -8.26376342 -2.26006856 0.97236419\n", - " 2.19545 ]\n", - "score for next parameter: -0.9515861549298081 \n", + "next parameter: [77.72149658 -0.47775269 2.72583008 -5.90924072 -4.90923462 0.96629639\n", + " 2.02374268]\n", + "score for next parameter: -0.927004477004477 \n", "\n", "iteration 47 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [25.88238525 -1.74389038 -2.65014648 -1.57403564 -4.40076294 0.91956787\n", - " 2.90045166]\n", - "score for next parameter: -0.9094324045407639 \n", + "next parameter: [85.23745728 -0.71920471 -5.65979004 -5.46401978 -3.85934143 0.93279419\n", + " 1.7482605 ]\n", + "score for next parameter: -0.9599498746867168 \n", "\n", "iteration 48 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [49.78012085 -1.66808777 -5.2532959 -2.79049683 -4.2025238 0.93803101\n", - " 3.02578735]\n", - "score for next parameter: -0.9685173718610252 \n", + "next parameter: [15.45358276 -0.13763123 -2.24304199 -3.9012146 -2.59860535 0.98849487\n", + " 3.08181763]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "iteration 49 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", "next parameter: [33.37298024 -1.53918059 -7.67205338 -2.09071315 -3.16740687 0.84715434\n", " 2.65307455]\n", "score for next parameter: -0.827206273258905 \n", "\n", "iteration 50 -----\n", - "current minimum: [28.31567383 -0.95993652 -2.07519531 -3.48071289 -4.9470459 0.89868164\n", - " 3.07348633]\n", + "current minimum: [16.03674316 -0.77052002 -5.91552734 -4.45739746 -5.30499268 0.9630127\n", + " 3.0592041 ]\n", "current minimum score: -0.9763060428849902\n", - "next parameter: [87.88980103 -1.52584534 -4.95666504 -4.58511353 -4.66598206 0.90701294\n", - " 2.43966675]\n", - "score for next parameter: -0.9515316886988714 \n", + "next parameter: [67.97058105 -0.72010498 -1.48681641 -5.10998535 -5.40438232 0.94821777\n", + " 3.71325684]\n", + "score for next parameter: -0.9763060428849902 \n", "\n", "Global iteration #3 -----\n", - "current minimum: [46.49133301 -0.40465088 -4.20654297 -5.05065918 -5.4519165 0.95627441\n", - " 3.99816895]\n", + "current minimum: [63.15136719 -0.87783203 -0.72265625 -9.97363281 -5.37197266 0.89238281\n", + " 3.55175781]\n", "current minimum score: -0.9763060428849902\n", "score for next parameter: -0.9763060428849902 \n", "\n", - "{'parameters': DescribeResult(best_params=array([46.49133301, -0.40465088, -4.20654297, -5.05065918, -5.4519165 ,\n", - " 0.95627441, 3.99816895]), best_score=-0.9763060428849902, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=100, type_pi='bootstrap')), 'opt_object': }\n", + "{'parameters': DescribeResult(best_params=array([63.15136719, -0.87783203, -0.72265625, -9.97363281, -5.37197266,\n", + " 0.89238281, 3.55175781]), best_score=-0.9763060428849902, best_surrogate=CustomRegressor(obj=BaggingRegressor(), replications=150, type_pi='bootstrap')), 'opt_object': }\n", " |======================================================================| 100%\n", "\n", - " Elapsed: 4.222970008850098\n", - "\n", "\n", " Test set accuracy: 0.9666666666666667\n", "\n", - " Elapsed: 0.03116631507873535\n" + " Elapsed: 2256.0045511722565\n" ] } ], "source": [ + "start = time()\n", "for elt in datasets:\n", "\n", " dataset = elt()\n", @@ -2837,9 +2975,7 @@ " res1 = optimize_bcn2(X_train, y_train)\n", " print(res1)\n", " parameters = res1[\"parameters\"]\n", - " start = time()\n", "\n", - " start = time()\n", " estimator = bcn.BCNClassifier(B=int(parameters[0][0]),\n", " nu=10**parameters[0][1],\n", " lam=10**parameters[0][2],\n", @@ -2849,8 +2985,6 @@ " n_clusters=np.ceil(parameters[0][6]),\n", " activation=\"tanh\",\n", " type_optim=\"nlminb\").fit(X_train, y_train)\n", - " print(f\"\\n Elapsed: {time() - start}\")\n", - " start = time()\n", " print(f\"\\n\\n Test set accuracy: {estimator.score(X_test, y_test)}\")\n", " print(f\"\\n Elapsed: {time() - start}\")" ]