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itaicaspi-intel
2018-09-12 15:29:42 +03:00
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rl_coach/traces/Atari_NStepQ_space_invaders/trace.csv
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@@ -1,21 +1,26 @@
Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,Q Values/Mean,Q Values/Stdev,Q Values/Max,Q Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min
1,0.0,1.0,486.0,1.0,486.0,486.0,0.5,,,0.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
2,0.0,1.0,87.0,1.0,87.0,573.0,0.5,,,0.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
3,0.0,1.0,149.0,1.0,149.0,722.0,0.5,,,0.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
4,0.0,1.0,335.0,1.0,335.0,1057.0,0.5,,,0.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
5,30.0,0.0,152.0,1.0,152.0,1209.0,0.4985103999999994,2.0,15.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.01806015,0.031154681,0.11256089999999999,-0.03153646,0.040528998,0.15495184,0.7766681,7.3362275999999995e-06
6,84.0,0.0,270.0,1.0,270.0,1479.0,0.4958643999999982,8.0,120.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.04832644,0.029433122000000003,0.116728835,-0.013950496000000001,0.054705366,0.14291170000000003,0.70854425,0.00038360796
7,149.0,0.0,324.0,1.0,324.0,1803.0,0.4926891999999968,9.0,120.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.06519938,0.036996773999999996,0.20431875,-0.0006479138,0.09192595,0.23194770000000003,0.8836251,9.27005e-05
8,197.0,0.0,237.0,1.0,237.0,2040.0,0.4903665999999958,6.0,70.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.081993505,0.031750474,0.17067611,0.01893028,0.06609978,0.17276828,0.84518427,0.00049587624
9,231.0,0.0,171.0,1.0,171.0,2211.0,0.4886907999999951,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.06561219,0.027578448999999998,0.16583520000000002,0.0023947426000000003,0.0045568603,0.0040728809999999996,0.019272441,0.0012047348
10,352.0,0.0,604.0,1.0,604.0,2815.0,0.4827715999999925,16.0,240.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.054065555,0.029770117000000002,0.14167584,-0.025165185,0.06984026,0.19431692,0.8947495999999999,1.5888494e-05
11,399.0,0.0,232.0,1.0,232.0,3047.0,0.4804979999999915,4.0,25.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.09317397,0.037268302999999996,0.1879414,0.017247636,0.04507253,0.13425689999999998,0.7788928,0.0016535529999999999
12,430.0,0.0,154.0,1.0,154.0,3201.0,0.4789887999999909,2.0,15.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.060374584,0.026983725,0.1327358,0.00017325346999999997,0.03700112,0.15603235,0.8584324000000001,9.365492e-05
13,464.0,0.0,169.0,1.0,169.0,3370.0,0.4773325999999902,3.0,60.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.07076912,0.024960317000000003,0.171489,0.022848563,0.07708849,0.23528506,0.8999446,0.0009268887
14,502.0,0.0,189.0,1.0,189.0,3559.0,0.4754803999999894,4.0,50.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.08175371599999999,0.059707563,0.23806223,-0.0022388997,0.080376275,0.21826938,0.9014337,0.000156738
15,530.0,0.0,138.0,1.0,138.0,3697.0,0.4741279999999888,1.0,25.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.06588258599999999,0.031772457000000004,0.16913122,-0.0033009246000000004,0.037671477,0.17314273,0.92035943,0.0008084267599999999
16,549.0,0.0,95.0,1.0,95.0,3792.0,0.4731969999999884,1.0,30.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.08419551,0.021721134,0.13456126,0.042178745999999996,0.022773635,0.08062003,0.35514408,0.00152435
17,630.0,0.0,404.0,1.0,404.0,4196.0,0.4692377999999866,9.0,75.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.06739886,0.03467486,0.14949478,-0.03615028,0.063086614,0.17489205,0.7053564,0.00030611295
18,714.0,0.0,420.0,1.0,420.0,4616.0,0.4651217999999849,10.0,160.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.06760059,0.022386358999999998,0.1480442,0.0114746755,0.065966256,0.18684588,0.90956885,0.00010415676
19,809.0,0.0,473.0,1.0,473.0,5089.0,0.4604863999999829,7.0,135.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.057970256,0.020290807,0.13571687,0.012275728,0.04331644,0.16250839999999997,0.8834267,0.00020417363000000002
20,850.0,0.0,204.0,1.0,204.0,5293.0,0.45848719999998205,3.0,20.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,0.07100958,0.030987637000000002,0.14825977,0.011810873000000001,0.047851723,0.16509958,0.8592968000000001,0.00032094717999999996
Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,Q Values/Mean,Q Values/Stdev,Q Values/Max,Q Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min
1,0.0,1.0,486.0,1.0,486.0,486.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.027285241237078,0.8961037725396955,3.502959469093688,0.0,,,,,,,,,,,,,,,,
2,0.0,1.0,87.0,1.0,87.0,573.0,0.5,,,0.0,,,,,,,,,,,,,,,,0.2991949731169189,0.4147830569909918,1.0,0.0,,,,,,,,,,,,,,,,
3,0.0,1.0,149.0,1.0,149.0,722.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.089942054123867,0.6773639260883686,1.9560606270183023,0.0,,,,,,,,,,,,,,,,
4,0.0,1.0,335.0,1.0,335.0,1057.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.6150170189100268,1.2171006279541683,4.3034191502088746,0.0,,,,,,,,,,,,,,,,
5,49.0,0.0,250.0,1.0,250.0,1307.0,0.4975499999999989,3.0,60.0,0.0,,,,,,,,,,,,,,,,0.9619660716012052,0.5271840370028462,1.9877214348890249,0.0,,,,,,,,,0.06523297,0.039132793,0.16515993,-0.04698263,0.03715847,0.16062164,0.9986223,5.2241390000000005e-06
6,105.0,0.0,278.0,1.0,278.0,1585.0,0.4948255999999978,2.0,25.0,0.0,,,,,,,,,,,,,,,,0.6504435080212637,0.4990360198105554,1.877521022998968,0.0,,,,,,,,,0.06105925,0.028913812999999997,0.2251295,0.00031058473,0.025028551,0.12800282,0.8860348,4.704531e-05
7,215.0,0.0,547.0,1.0,547.0,2132.0,0.4894649999999954,9.0,70.0,0.0,,,,,,,,,,,,,,,,1.1668219204868608,1.139774286228071,3.981172292031248,0.0,,,,,,,,,0.09291774,0.041909117,0.29434606,0.016387725,0.06240651,0.19966795,0.9046893,0.00021752282999999999
8,256.0,0.0,202.0,1.0,202.0,2334.0,0.4874853999999946,3.0,30.0,0.0,,,,,,,,,,,,,,,,1.143254407638888,0.7651739473233898,2.6822034344079513,0.0,,,,,,,,,0.0812066,0.034699347,0.22075215,0.033963714,0.06826939,0.23026471,0.8968558000000001,5.273441e-06
9,271.0,0.0,76.0,1.0,76.0,2410.0,0.4867405999999943,2.0,45.0,0.0,,,,,,,,,,,,,,,,0.6040699250474294,0.6770046574946313,1.8097278682212583,0.0,,,,,,,,,0.08223315,0.042012982000000004,0.20047347,0.0048412476,0.0409274,0.09979676,0.36558379999999996,0.0012286354
10,330.0,0.0,292.0,1.0,292.0,2702.0,0.483878999999993,2.0,35.0,0.0,,,,,,,,,,,,,,,,0.5188424987401079,0.3205545284923169,1.1982742565889144,0.0,,,,,,,,,0.07179869,0.028891182999999997,0.1457309,-0.0005440897,0.020115541,0.114067726,0.85806334,1.0554600499999999e-05
11,368.0,0.0,189.0,1.0,189.0,2891.0,0.4820267999999922,5.0,55.0,0.0,,,,,,,,,,,,,,,,1.6514130362698112,1.0340472182590057,3.338928212866469,0.0,,,,,,,,,0.10357409,0.038070783,0.19072735,0.013136728,0.07165525,0.20934153,0.96637666,9.3623305e-05
12,385.0,0.0,85.0,1.0,85.0,2976.0,0.4811937999999918,2.0,55.0,0.0,,,,,,,,,,,,,,,,0.6644740252476246,0.6445878033949242,1.7547192872036326,0.0,,,,,,,,,0.08559471,0.036382526,0.19190781,0.038743064,0.09200458,0.2459315,0.92060333,0.001493881
13,439.0,0.0,271.0,1.0,271.0,3247.0,0.4785379999999907,3.0,30.0,0.0,,,,,,,,,,,,,,,,0.9805352211608988,0.7225009315821939,2.6900602158160227,0.0,,,,,,,,,0.07257719,0.036623262000000004,0.22449888,0.017026702,0.051612765,0.19161709,0.93902147,6.006258000000001e-05
14,489.0,0.0,247.0,1.0,247.0,3494.0,0.4761173999999896,3.0,30.0,0.0,,,,,,,,,,,,,,,,0.7239330793237315,0.6866779551191587,2.2598491521703985,0.0,,,,,,,,,0.09624664,0.028458447999999997,0.18122105,0.04136644,0.04521184,0.17329727,0.93528235,0.00010959508
15,554.0,0.0,322.0,1.0,322.0,3816.0,0.4729617999999883,7.0,75.0,0.0,,,,,,,,,,,,,,,,1.7027014745135145,0.8785415129990072,3.3646815869626545,0.0,,,,,,,,,0.08818049,0.03232697,0.19298476,0.01802668,0.06566782,0.20002598,0.93202585,0.000119806835
16,591.0,0.0,185.0,1.0,185.0,4001.0,0.4711487999999875,3.0,35.0,0.0,,,,,,,,,,,,,,,,0.906880276626358,0.5305160768996153,1.8687458127689778,0.0,,,,,,,,,0.10646282,0.030883757,0.19681731,0.052096736,0.062161777,0.18977489,0.77037257,0.0006098728
17,628.0,0.0,186.0,1.0,186.0,4187.0,0.4693259999999867,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.10503617,0.02636908,0.17513691,0.058163125,0.0040708557,0.0018935091,0.008554585,0.0012393859
18,644.0,0.0,80.0,1.0,80.0,4267.0,0.4685419999999864,2.0,15.0,0.0,,,,,,,,,,,,,,,,0.702410295740766,0.7598837978189577,1.886384871716129,0.0,,,,,,,,,0.088057734,0.014962838999999999,0.13839622,0.06381006,0.077688575,0.20810342,0.7685311,5.7868005e-05
19,663.0,0.0,93.0,1.0,93.0,4360.0,0.467630599999986,2.0,35.0,0.0,,,,,,,,,,,,,,,,0.7877925962882179,0.6771086001101679,1.8016305895390456,0.0,,,,,,,,,0.07237811400000001,0.03177111,0.15346664,0.027509372999999997,0.07317008,0.22093417,0.92313504,0.00035924176
20,705.0,0.0,210.0,1.0,210.0,4570.0,0.465572599999985,3.0,30.0,0.0,,,,,,,,,,,,,,,,1.1264211896676488,0.6963700234551127,2.5143201556468044,0.0,,,,,,,,,0.07745734,0.03569484,0.17048967,-0.0018016198,0.033146697999999995,0.11387434,0.54282963,9.045503e-05
21,724.0,0.0,94.0,1.0,94.0,4664.0,0.4646513999999847,2.0,45.0,0.0,,,,,,,,,,,,,,,,0.7487142977587385,0.6585762420290013,1.770043145805155,0.0,,,,,,,,,0.085581295,0.031317193,0.16033286,0.03945991,0.031889725,0.09107567,0.37029892,0.00048189453
22,846.0,0.0,608.0,1.0,608.0,5272.0,0.4586929999999821,12.0,340.0,0.0,,,,,,,,,,,,,,,,1.7842522377946013,1.2596094953837684,4.9927930148931186,0.0,,,,,,,,,0.104008555,0.040039804,0.20478153,0.008027065,0.06521728,0.18897916,0.82046026,5.0944614e-05
23,885.0,0.0,194.0,1.0,194.0,5466.0,0.4567917999999813,6.0,80.0,0.0,,,,,,,,,,,,,,,,2.0644794324027784,1.0634426104295631,3.98052088029283,0.0,,,,,,,,,0.119464405,0.034119558,0.18460895,0.039233252,0.06616199,0.16974789,0.8555218000000001,0.0008571786999999999
24,904.0,0.0,95.0,1.0,95.0,5561.0,0.4558607999999809,1.0,30.0,0.0,,,,,,,,,,,,,,,,0.21724812248036252,0.3855022238888541,1.0,0.0,,,,,,,,,0.09762655,0.029675594,0.1733855,0.06255842,0.031556234,0.11838596,0.5196432,0.0013286468
25,923.0,0.0,94.0,1.0,94.0,5655.0,0.4549395999999805,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.06350739,0.014013496,0.10299649999999999,0.03182298,0.00033242480000000006,0.00019209432000000002,0.0007463536500000001,0.000114553884
1 Episode # Training Iter In Heatup ER #Transitions ER #Episodes Episode Length Total steps Epsilon Shaped Training Reward Training Reward Update Target Network Evaluation Reward Shaped Evaluation Reward Success Rate Loss/Mean Loss/Stdev Loss/Max Loss/Min Learning Rate/Mean Learning Rate/Stdev Learning Rate/Max Learning Rate/Min Grads (unclipped)/Mean Grads (unclipped)/Stdev Grads (unclipped)/Max Grads (unclipped)/Min Discounted Return/Mean Discounted Return/Stdev Discounted Return/Max Discounted Return/Min Entropy/Mean Entropy/Stdev Entropy/Max Entropy/Min Q/Mean Q/Stdev Q/Max Q/Min Q Values/Mean Q Values/Stdev Q Values/Max Q Values/Min Value Loss/Mean Value Loss/Stdev Value Loss/Max Value Loss/Min
2 1 0.0 1.0 486.0 1.0 486.0 486.0 0.5 0.0 1.027285241237078 0.8961037725396955 3.502959469093688 0.0
3 2 0.0 1.0 87.0 1.0 87.0 573.0 0.5 0.0 0.2991949731169189 0.4147830569909918 1.0 0.0
4 3 0.0 1.0 149.0 1.0 149.0 722.0 0.5 0.0 1.089942054123867 0.6773639260883686 1.9560606270183023 0.0
5 4 0.0 1.0 335.0 1.0 335.0 1057.0 0.5 0.0 1.6150170189100268 1.2171006279541683 4.3034191502088746 0.0
6 5 30.0 49.0 0.0 152.0 250.0 1.0 152.0 250.0 1209.0 1307.0 0.4985103999999994 0.4975499999999989 2.0 3.0 15.0 60.0 0.0 0.9619660716012052 0.5271840370028462 1.9877214348890249 0.0 0.01806015 0.06523297 0.031154681 0.039132793 0.11256089999999999 0.16515993 -0.03153646 -0.04698263 0.040528998 0.03715847 0.15495184 0.16062164 0.7766681 0.9986223 7.3362275999999995e-06 5.2241390000000005e-06
7 6 84.0 105.0 0.0 270.0 278.0 1.0 270.0 278.0 1479.0 1585.0 0.4958643999999982 0.4948255999999978 8.0 2.0 120.0 25.0 0.0 0.6504435080212637 0.4990360198105554 1.877521022998968 0.0 0.04832644 0.06105925 0.029433122000000003 0.028913812999999997 0.116728835 0.2251295 -0.013950496000000001 0.00031058473 0.054705366 0.025028551 0.14291170000000003 0.12800282 0.70854425 0.8860348 0.00038360796 4.704531e-05
8 7 149.0 215.0 0.0 324.0 547.0 1.0 324.0 547.0 1803.0 2132.0 0.4926891999999968 0.4894649999999954 9.0 120.0 70.0 0.0 1.1668219204868608 1.139774286228071 3.981172292031248 0.0 0.06519938 0.09291774 0.036996773999999996 0.041909117 0.20431875 0.29434606 -0.0006479138 0.016387725 0.09192595 0.06240651 0.23194770000000003 0.19966795 0.8836251 0.9046893 9.27005e-05 0.00021752282999999999
9 8 197.0 256.0 0.0 237.0 202.0 1.0 237.0 202.0 2040.0 2334.0 0.4903665999999958 0.4874853999999946 6.0 3.0 70.0 30.0 0.0 1.143254407638888 0.7651739473233898 2.6822034344079513 0.0 0.081993505 0.0812066 0.031750474 0.034699347 0.17067611 0.22075215 0.01893028 0.033963714 0.06609978 0.06826939 0.17276828 0.23026471 0.84518427 0.8968558000000001 0.00049587624 5.273441e-06
10 9 231.0 271.0 0.0 171.0 76.0 1.0 171.0 76.0 2211.0 2410.0 0.4886907999999951 0.4867405999999943 0.0 2.0 0.0 45.0 0.0 0.6040699250474294 0.6770046574946313 1.8097278682212583 0.0 0.06561219 0.08223315 0.027578448999999998 0.042012982000000004 0.16583520000000002 0.20047347 0.0023947426000000003 0.0048412476 0.0045568603 0.0409274 0.0040728809999999996 0.09979676 0.019272441 0.36558379999999996 0.0012047348 0.0012286354
11 10 352.0 330.0 0.0 604.0 292.0 1.0 604.0 292.0 2815.0 2702.0 0.4827715999999925 0.483878999999993 16.0 2.0 240.0 35.0 0.0 0.5188424987401079 0.3205545284923169 1.1982742565889144 0.0 0.054065555 0.07179869 0.029770117000000002 0.028891182999999997 0.14167584 0.1457309 -0.025165185 -0.0005440897 0.06984026 0.020115541 0.19431692 0.114067726 0.8947495999999999 0.85806334 1.5888494e-05 1.0554600499999999e-05
12 11 399.0 368.0 0.0 232.0 189.0 1.0 232.0 189.0 3047.0 2891.0 0.4804979999999915 0.4820267999999922 4.0 5.0 25.0 55.0 0.0 1.6514130362698112 1.0340472182590057 3.338928212866469 0.0 0.09317397 0.10357409 0.037268302999999996 0.038070783 0.1879414 0.19072735 0.017247636 0.013136728 0.04507253 0.07165525 0.13425689999999998 0.20934153 0.7788928 0.96637666 0.0016535529999999999 9.3623305e-05
13 12 430.0 385.0 0.0 154.0 85.0 1.0 154.0 85.0 3201.0 2976.0 0.4789887999999909 0.4811937999999918 2.0 15.0 55.0 0.0 0.6644740252476246 0.6445878033949242 1.7547192872036326 0.0 0.060374584 0.08559471 0.026983725 0.036382526 0.1327358 0.19190781 0.00017325346999999997 0.038743064 0.03700112 0.09200458 0.15603235 0.2459315 0.8584324000000001 0.92060333 9.365492e-05 0.001493881
14 13 464.0 439.0 0.0 169.0 271.0 1.0 169.0 271.0 3370.0 3247.0 0.4773325999999902 0.4785379999999907 3.0 60.0 30.0 0.0 0.9805352211608988 0.7225009315821939 2.6900602158160227 0.0 0.07076912 0.07257719 0.024960317000000003 0.036623262000000004 0.171489 0.22449888 0.022848563 0.017026702 0.07708849 0.051612765 0.23528506 0.19161709 0.8999446 0.93902147 0.0009268887 6.006258000000001e-05
15 14 502.0 489.0 0.0 189.0 247.0 1.0 189.0 247.0 3559.0 3494.0 0.4754803999999894 0.4761173999999896 4.0 3.0 50.0 30.0 0.0 0.7239330793237315 0.6866779551191587 2.2598491521703985 0.0 0.08175371599999999 0.09624664 0.059707563 0.028458447999999997 0.23806223 0.18122105 -0.0022388997 0.04136644 0.080376275 0.04521184 0.21826938 0.17329727 0.9014337 0.93528235 0.000156738 0.00010959508
16 15 530.0 554.0 0.0 138.0 322.0 1.0 138.0 322.0 3697.0 3816.0 0.4741279999999888 0.4729617999999883 1.0 7.0 25.0 75.0 0.0 1.7027014745135145 0.8785415129990072 3.3646815869626545 0.0 0.06588258599999999 0.08818049 0.031772457000000004 0.03232697 0.16913122 0.19298476 -0.0033009246000000004 0.01802668 0.037671477 0.06566782 0.17314273 0.20002598 0.92035943 0.93202585 0.0008084267599999999 0.000119806835
17 16 549.0 591.0 0.0 95.0 185.0 1.0 95.0 185.0 3792.0 4001.0 0.4731969999999884 0.4711487999999875 1.0 3.0 30.0 35.0 0.0 0.906880276626358 0.5305160768996153 1.8687458127689778 0.0 0.08419551 0.10646282 0.021721134 0.030883757 0.13456126 0.19681731 0.042178745999999996 0.052096736 0.022773635 0.062161777 0.08062003 0.18977489 0.35514408 0.77037257 0.00152435 0.0006098728
18 17 630.0 628.0 0.0 404.0 186.0 1.0 404.0 186.0 4196.0 4187.0 0.4692377999999866 0.4693259999999867 9.0 0.0 75.0 0.0 0.0 0.0 0.0 0.0 0.0 0.06739886 0.10503617 0.03467486 0.02636908 0.14949478 0.17513691 -0.03615028 0.058163125 0.063086614 0.0040708557 0.17489205 0.0018935091 0.7053564 0.008554585 0.00030611295 0.0012393859
19 18 714.0 644.0 0.0 420.0 80.0 1.0 420.0 80.0 4616.0 4267.0 0.4651217999999849 0.4685419999999864 10.0 2.0 160.0 15.0 0.0 0.702410295740766 0.7598837978189577 1.886384871716129 0.0 0.06760059 0.088057734 0.022386358999999998 0.014962838999999999 0.1480442 0.13839622 0.0114746755 0.06381006 0.065966256 0.077688575 0.18684588 0.20810342 0.90956885 0.7685311 0.00010415676 5.7868005e-05
20 19 809.0 663.0 0.0 473.0 93.0 1.0 473.0 93.0 5089.0 4360.0 0.4604863999999829 0.467630599999986 7.0 2.0 135.0 35.0 0.0 0.7877925962882179 0.6771086001101679 1.8016305895390456 0.0 0.057970256 0.07237811400000001 0.020290807 0.03177111 0.13571687 0.15346664 0.012275728 0.027509372999999997 0.04331644 0.07317008 0.16250839999999997 0.22093417 0.8834267 0.92313504 0.00020417363000000002 0.00035924176
21 20 850.0 705.0 0.0 204.0 210.0 1.0 204.0 210.0 5293.0 4570.0 0.45848719999998205 0.465572599999985 3.0 20.0 30.0 0.0 1.1264211896676488 0.6963700234551127 2.5143201556468044 0.0 0.07100958 0.07745734 0.030987637000000002 0.03569484 0.14825977 0.17048967 0.011810873000000001 -0.0018016198 0.047851723 0.033146697999999995 0.16509958 0.11387434 0.8592968000000001 0.54282963 0.00032094717999999996 9.045503e-05
22 21 724.0 0.0 94.0 1.0 94.0 4664.0 0.4646513999999847 2.0 45.0 0.0 0.7487142977587385 0.6585762420290013 1.770043145805155 0.0 0.085581295 0.031317193 0.16033286 0.03945991 0.031889725 0.09107567 0.37029892 0.00048189453
23 22 846.0 0.0 608.0 1.0 608.0 5272.0 0.4586929999999821 12.0 340.0 0.0 1.7842522377946013 1.2596094953837684 4.9927930148931186 0.0 0.104008555 0.040039804 0.20478153 0.008027065 0.06521728 0.18897916 0.82046026 5.0944614e-05
24 23 885.0 0.0 194.0 1.0 194.0 5466.0 0.4567917999999813 6.0 80.0 0.0 2.0644794324027784 1.0634426104295631 3.98052088029283 0.0 0.119464405 0.034119558 0.18460895 0.039233252 0.06616199 0.16974789 0.8555218000000001 0.0008571786999999999
25 24 904.0 0.0 95.0 1.0 95.0 5561.0 0.4558607999999809 1.0 30.0 0.0 0.21724812248036252 0.3855022238888541 1.0 0.0 0.09762655 0.029675594 0.1733855 0.06255842 0.031556234 0.11838596 0.5196432 0.0013286468
26 25 923.0 0.0 94.0 1.0 94.0 5655.0 0.4549395999999805 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.06350739 0.014013496 0.10299649999999999 0.03182298 0.00033242480000000006 0.00019209432000000002 0.0007463536500000001 0.000114553884