new

4 years ago · 3b9839eaa6
parent cd445f1fcc
commit 3b9839eaa6
161 changed files with 1053 additions and 36 deletions
--- a/XData.csv
+++ b/XData.csv
@ -0,0 +1,838 @@
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 65,0.862,7.794,2,0,2.115,0,0,2.741,0.0,0,1,9.067,33.3,0,3.3382,1.289,0,0.998,0.956,0,0,0,0,1.152,2.194,4.303,1,0,0,0,0.0,1,0,0,0.137,0,3.627,0,4,1,0
 66,1.125,7.967,1,0,2.136,0,0,3.013,0.0,2,0,9.311,46.7,0,3.1284,1.299,0,0.984,1.481,0,0,0,0,1.116,2.208,4.499,0,0,0,0,0.0,1,0,0,0.045,0,3.608,0,3,0,0
 67,1.591,8.325,2,4,2.407,0,2,3.764,0.0,2,2,10.691,28.9,0,1.89,1.132,0,1.003,3.261,0,0,0,0,1.151,2.154,5.361,4,0,0,16,0.0,2,0,1,0.0,0,3.495,0,2,0,0
 68,1.013,9.511,2,2,2.526,0,4,4.113,24.788,2,0,10.917,58.3,0,2.228,1.377,0,1.037,1.706,2,2,0,0,1.07,2.8,5.336,0,0,0,6,0.284,6,0,0,0.0,0,4.238,0,2,0,0
 69,1.125,7.32,1,1,2.136,0,0,2.889,0.0,0,1,9.311,28.6,0,2.3906,1.131,0,0.987,1.481,0,0,0,0,1.152,1.875,4.499,0,0,0,0,0.0,1,0,0,0.041,0,3.229,0,3,0,0
 70,1.409,7.385,3,0,2.149,0,3,2.994,0.0,0,1,9.391,25.0,0,2.2821,1.129,0,0.984,2.036,0,0,0,0,1.166,1.944,4.517,3,0,0,0,0.0,1,0,0,-0.023,0,3.219,0,6,0,0
 71,0.762,8.272,1,2,2.424,0,2,3.329,22.106,2,0,10.226,40.0,0,2.3549,1.216,0,1.015,1.027,0,0,0,2,1.129,2.682,4.982,1,0,0,6,-0.186,3,0,0,0.004,0,3.673,0,2,0,0
 72,0.875,8.812,1,0,2.175,2,0,3.382,0.0,1,0,9.54,45.5,1,3.4161,1.35,0,1.047,1.069,0,2,0,0,1.111,2.569,4.596,0,0,0,0,0.0,1,0,0,0.047,0,3.992,0,2,0,0
 73,0.906,8.818,1,1,2.278,1,0,3.349,10.529,0,0,9.773,33.3,1,3.0402,1.331,0,1.05,1.017,0,2,0,0,1.117,2.785,4.651,0,0,0,2,0.498,1,0,0,0.046,0,4.116,0,2,0,0
 74,0.664,8.695,1,1,2.376,0,2,3.395,10.934,2,0,10.037,46.7,0,2.7189,1.327,0,1.018,1.057,2,1,0,0,1.097,2.433,4.923,1,0,1,2,0.014,3,0,0,-0.008,0,4.009,0,2,0,0
 75,1.0,8.243,0,0,1.618,2,0,2.889,0.0,0,2,7.408,25.0,0,2.2062,1.28,0,1.037,1.707,0,2,0,0,1.142,2.806,3.414,0,0,0,0,0.0,0,0,0,-0.57,0,3.676,0,0,0,0
 76,1.185,8.087,0,0,2.267,0,0,3.164,0.0,0,3,9.911,41.7,0,3.0313,1.299,0,0.966,1.563,2,0,0,0,1.121,1.867,4.923,0,0,0,0,0.0,1,0,0,0.012,0,3.669,0,0,0,0
 77,1.16,9.499,2,2,2.311,0,3,3.492,21.362,4,0,10.388,31.6,0,3.4071,1.244,0,1.031,1.833,2,1,0,0,1.136,3.114,5.313,4,0,2,4,0.0,1,0,0,-0.008,0,4.725,0,3,0,0
 78,0.703,8.803,0,3,2.363,0,0,3.72,11.937,0,0,10.481,50.0,0,2.4738,1.267,0,1.015,2.723,4,0,0,0,1.104,2.708,5.072,2,0,2,9,-0.266,2,0,0,0.0,0,3.827,0,0,0,0
 79,0.648,8.658,0,2,2.314,0,0,3.633,0.0,0,0,10.338,48.1,0,2.3426,1.281,0,0.998,2.863,4,0,0,0,1.108,2.411,4.912,2,0,2,6,0.0,2,0,0,0.0,0,3.733,0,0,0,0
 80,1.299,7.401,0,0,2.149,0,0,2.821,0.0,0,5,10.01,30.8,0,3.3889,1.246,0,0.96,2.097,0,0,0,0,1.144,1.76,5.125,0,0,0,0,0.0,0,0,1,-0.062,0,3.283,0,0,0,0
 81,0.722,9.115,0,0,2.0,4,0,3.4,0.0,0,1,9.657,20.0,0,3.756,1.407,0,1.212,0.8,0,4,0,0,1.121,3.539,5.0,0,0,0,0,0.0,0,0,1,0.42,0,4.385,0,0,0,0
 82,0.811,9.531,0,0,2.303,6,0,3.827,0.0,0,2,10.505,25.0,0,4.6399,1.392,0,1.199,1.411,0,6,0,0,1.114,3.396,5.646,0,0,0,0,0.0,0,0,2,-0.086,0,4.444,0,0,0,2
 83,0.811,12.274,0,0,2.303,6,0,4.249,0.0,0,2,10.505,25.0,0,4.8079,1.138,0,1.27,1.411,0,2,0,0,1.286,5.0,5.646,0,0,0,0,0.0,0,0,2,-0.098,0,6.925,1,0,0,2
 84,1.837,7.316,1,0,2.074,0,0,2.939,0.0,2,4,9.454,28.6,0,3.4355,1.173,0,0.966,2.57,0,0,0,0,1.151,1.796,4.523,1,0,0,0,0.0,0,0,0,0.038,0,3.177,0,4,0,0
 85,1.5,8.058,4,2,2.0,0,2,3.044,19.316,0,0,9.309,16.7,0,4.368,1.095,0,1.088,2.682,0,0,0,0,1.201,3.917,4.343,4,0,0,0,-2.076,0,1,0,-0.099,0,3.563,0,2,0,0
 86,2.074,8.938,3,2,2.175,0,4,3.693,21.065,2,0,10.071,24.1,0,4.1851,1.233,0,1.014,3.255,0,2,0,0,1.146,2.81,4.737,4,0,0,2,-0.804,0,0,0,-0.002,0,3.856,0,2,0,0
 87,3.113,9.274,0,7,2.258,0,0,4.111,12.646,0,3,10.545,27.7,0,4.758,1.156,0,0.999,4.518,0,1,0,0,1.146,2.204,5.262,0,0,0,12,0.0,0,0,0,0.0,0,4.415,0,0,0,0
 88,2.205,14.005,0,0,2.303,0,0,4.471,0.0,0,4,10.331,30.2,0,4.0653,1.366,0,0.957,1.951,0,1,0,0,1.134,1.554,5.333,0,0,0,0,0.0,0,0,0,0.0,0,10.319,0,0,0,0
 89,1.187,8.078,0,0,2.194,0,0,3.102,0.0,0,1,9.642,47.4,0,2.9815,1.324,0,0.969,1.659,1,0,0,0,1.109,2.037,4.732,0,0,0,0,1.121,1,0,0,-0.024,0,3.632,0,0,0,0
 90,0.881,8.09,0,0,2.264,0,0,3.075,0.0,0,3,9.863,42.9,0,3.2478,1.32,0,0.967,0.95,3,0,0,0,1.119,1.889,4.912,0,0,0,0,0.0,1,0,0,-0.023,0,3.714,0,0,0,0
 91,1.261,8.107,0,0,2.247,0,0,3.188,0.0,0,1,9.749,45.5,0,3.0766,1.31,0,0.968,1.436,2,0,0,0,1.113,1.983,4.828,0,0,0,0,0.0,1,0,0,0.013,0,3.665,0,0,0,0
 92,1.261,8.015,0,0,2.214,0,0,3.157,0.0,0,2,9.714,41.7,0,2.7973,1.279,0,0.966,1.783,2,0,0,0,1.121,1.833,4.641,0,0,0,0,0.0,1,0,0,0.012,0,3.623,0,0,0,0
 93,1.261,8.015,0,0,2.222,0,0,3.157,0.0,0,2,9.715,41.7,0,2.8711,1.283,0,0.966,1.695,2,0,0,0,1.121,1.833,4.679,0,0,0,0,0.0,1,0,0,0.012,0,3.627,0,0,0,0
 94,1.261,8.189,0,0,2.247,0,0,3.219,0.0,0,0,9.749,50.0,0,3.1972,1.335,0,0.971,1.436,2,0,0,0,1.104,2.133,4.828,0,0,0,0,0.0,1,0,0,0.013,0,3.687,0,0,0,0
 95,1.187,11.597,0,0,2.194,1,0,3.844,0.0,0,0,9.642,50.0,0,3.0207,1.395,1,0.985,1.659,1,1,0,0,1.094,2.12,4.732,0,0,0,0,0.933,1,0,0,-0.024,0,6.881,1,0,0,0
 96,1.409,11.589,0,0,2.149,1,0,3.84,0.0,0,0,9.391,50.0,0,2.8827,1.389,1,0.985,2.036,1,1,0,0,1.094,2.046,4.517,0,0,0,0,0.0,1,0,0,-0.024,0,6.872,1,0,0,0
 97,0.875,8.792,0,0,2.175,2,0,3.373,0.0,0,0,9.54,50.0,1,3.2349,1.377,0,1.025,1.069,2,2,0,0,1.094,2.444,4.596,0,0,2,0,0.0,1,0,0,0.045,0,3.973,0,0,0,0
 98,0.875,8.792,0,0,2.17,2,0,3.373,0.0,0,0,9.54,50.0,1,3.1831,1.372,0,1.025,1.14,2,2,0,0,1.094,2.444,4.562,0,0,2,0,0.0,1,0,0,0.045,0,3.955,0,0,0,0
 99,0.875,8.794,0,0,2.194,2,0,3.373,0.0,0,0,9.579,50.0,1,3.3007,1.374,0,1.025,0.854,2,2,0,0,1.094,2.444,4.732,0,0,2,0,0.0,1,0,0,0.045,0,4.034,0,0,0,0
 100,0.875,12.272,0,0,2.17,2,0,4.225,0.0,0,0,9.54,50.0,0,3.1356,1.482,1,1.009,1.14,2,2,0,0,1.077,2.104,4.562,0,0,2,0,0.0,1,0,0,0.043,0,6.886,1,0,0,0
 101,0.881,8.857,0,0,2.246,2,0,3.444,0.0,0,1,9.833,46.7,1,3.3045,1.366,0,1.012,1.06,3,2,0,0,1.103,2.358,4.807,0,0,2,0,0.0,1,0,0,-0.025,0,4.005,0,0,0,0
 102,0.881,8.859,0,0,2.264,2,0,3.444,0.0,0,1,9.863,46.7,1,3.3884,1.365,0,1.012,0.95,3,2,0,0,1.103,2.358,4.912,0,0,2,0,0.0,1,0,0,-0.025,0,4.025,0,0,0,0
 103,1.187,8.001,1,0,2.2,0,2,3.08,0.0,2,1,9.631,40.0,0,3.0494,1.275,0,0.976,1.487,2,0,0,0,1.129,1.981,4.642,1,0,1,0,0.0,1,0,0,-0.024,0,3.634,0,2,0,0
 104,0.0,8.469,1,0,2.236,0,2,3.486,0.0,4,0,9.971,50.0,0,2.2988,1.315,0,0.98,2.829,2,0,0,0,1.107,1.987,4.675,1,0,2,0,0.0,2,0,0,0.001,0,3.648,0,4,1,0
 105,0.881,8.863,1,0,2.246,2,1,3.453,0.0,2,0,9.833,42.9,1,3.3502,1.332,0,1.029,1.06,3,2,0,0,1.117,2.58,4.807,2,0,3,0,0.0,1,0,0,-0.025,0,4.007,0,2,0,0
 106,0.881,8.863,1,0,2.246,2,1,3.453,0.0,2,0,9.833,42.9,1,3.3499,1.334,0,1.029,1.06,3,2,0,0,1.117,2.58,4.807,2,0,3,0,0.0,1,0,0,-0.025,0,3.996,0,2,0,0
 107,0.521,8.678,3,0,2.236,0,7,3.639,0.0,10,0,10.185,46.2,0,2.3407,1.285,0,0.994,3.626,3,0,0,0,1.121,2.2,4.649,2,0,3,0,0.0,2,1,0,0.0,0,3.712,0,8,0,0
 108,1.185,8.508,2,2,2.267,0,2,3.288,20.295,4,0,9.911,37.5,0,3.5484,1.225,0,1.039,1.563,2,0,1,0,1.14,3.133,4.923,2,0,2,4,0.0,1,0,0,0.015,0,3.857,0,4,0,0
 109,1.16,8.892,2,2,2.305,1,2,3.52,20.482,4,0,10.099,37.5,1,3.6277,1.249,0,1.059,1.553,3,1,1,0,1.137,3.192,4.965,2,0,3,4,0.0,1,0,0,-0.008,0,3.969,0,4,0,0
 110,1.197,9.191,3,4,2.38,1,3,3.761,41.432,6,0,10.456,33.3,1,3.9386,1.217,0,1.101,1.74,4,1,2,0,1.15,3.627,5.103,2,0,4,8,0.0,1,0,0,0.001,0,4.048,0,6,0,0
 111,1.185,8.825,1,2,2.267,1,1,3.445,20.286,2,0,9.911,42.9,1,3.5714,1.273,0,1.061,1.563,2,1,1,0,1.121,3.144,4.923,0,0,2,4,0.0,1,0,0,0.015,0,3.988,0,2,0,0
 112,1.258,8.854,2,4,2.323,0,2,3.513,40.909,4,0,10.159,37.5,0,3.8356,1.204,0,1.087,1.711,2,0,2,0,1.141,3.611,5.04,0,0,2,8,0.0,1,0,0,0.005,0,3.946,0,4,0,0
 113,1.23,8.914,2,4,2.351,0,3,3.576,41.436,4,1,10.309,36.8,0,3.8515,1.216,0,1.067,1.581,3,0,2,0,1.14,3.462,5.068,0,0,2,8,0.0,1,0,0,-0.002,0,3.962,0,4,0,0
 114,1.23,8.914,2,4,2.338,0,2,3.576,41.299,5,1,10.309,36.8,0,3.7359,1.216,0,1.067,1.873,3,0,2,0,1.14,3.462,5.006,0,0,2,8,0.0,1,0,0,-0.002,0,3.936,0,4,0,0
 115,1.16,8.886,1,2,2.292,1,1,3.512,20.423,2,1,10.099,41.2,1,3.4879,1.278,0,1.043,1.696,3,1,1,0,1.124,3.01,4.895,0,0,2,4,0.0,1,0,0,-0.008,0,3.974,0,2,0,0
 116,1.197,9.077,1,2,2.403,4,1,3.76,20.484,3,1,10.666,41.2,1,3.7849,1.15,0,1.133,1.679,3,1,1,0,1.184,4.026,5.402,0,0,2,4,0.0,1,0,1,0.001,0,3.991,0,2,0,1
 117,1.23,9.141,2,4,2.338,1,2,3.703,41.044,4,0,10.309,37.5,1,3.7801,1.231,0,1.108,1.873,3,1,2,0,1.137,3.624,5.006,0,0,3,8,0.0,1,0,0,-0.003,0,4.032,0,4,0,0
 118,1.16,9.118,1,2,2.292,2,1,3.647,20.337,2,0,10.099,42.9,1,3.54,1.296,0,1.084,1.696,3,2,1,0,1.117,3.202,4.895,0,0,3,4,0.0,1,0,0,-0.008,0,4.073,0,2,0,0
 119,1.16,9.118,1,2,2.303,2,1,3.647,20.422,2,0,10.099,42.9,1,3.5995,1.299,0,1.084,1.602,3,2,1,0,1.117,3.202,4.958,0,0,3,4,0.0,1,0,0,-0.008,0,4.057,0,2,0,0
 120,0.875,8.719,3,0,2.358,0,10,3.695,0.0,8,0,10.386,44.8,0,2.6361,1.287,0,0.99,2.298,2,0,0,0,1.123,2.25,5.098,3,0,2,0,0.011,2,0,0,0.0,0,3.746,0,4,1,0
 121,1.185,8.228,0,1,2.236,0,0,3.217,0.0,0,1,9.882,45.0,0,3.0583,1.288,0,0.987,1.74,2,0,0,0,1.114,2.4,4.77,1,0,1,2,1.014,1,0,0,0.014,0,3.69,0,0,0,0
 122,1.455,8.152,0,1,2.282,0,0,3.266,0.0,0,2,9.974,40.0,0,2.9807,1.253,0,0.981,1.887,2,0,0,0,1.125,2.197,4.947,1,0,1,3,0.0,1,0,0,-0.007,0,3.683,0,0,0,0
 123,1.455,8.148,0,1,2.251,0,0,3.266,0.0,0,2,9.947,40.0,0,2.8459,1.25,0,0.981,2.041,2,0,0,0,1.125,2.197,4.805,1,0,1,2,0.0,1,0,0,-0.007,0,3.657,0,0,0,0
 124,1.571,8.48,0,1,2.378,0,0,3.547,0.0,0,5,10.843,37.8,0,2.9274,1.265,0,0.974,2.74,2,0,0,0,1.129,2.089,5.459,1,0,1,2,0.0,1,0,2,-0.001,0,3.704,0,0,0,0
 125,3.025,8.397,0,1,2.236,0,0,3.74,0.0,0,1,10.128,36.7,0,1.9089,1.238,0,0.971,6.687,2,0,0,0,1.131,1.886,4.793,1,0,1,3,0.0,1,0,0,0.0,0,3.657,0,0,0,0
 126,1.494,8.588,0,1,2.436,0,0,3.66,0.0,0,6,10.995,37.2,0,3.3208,1.245,0,0.972,2.399,3,0,0,0,1.13,2.029,5.466,1,0,1,3,0.0,1,0,2,0.0,0,3.798,0,0,0,0
 127,1.161,8.548,0,1,2.417,0,0,3.551,0.0,0,6,10.929,37.8,0,3.3311,1.265,0,0.974,2.084,3,0,0,0,1.129,2.1,5.422,1,0,1,3,0.0,1,0,2,-0.001,0,3.799,0,0,0,0
 128,1.23,8.348,0,1,2.358,0,0,3.419,0.0,0,4,10.328,38.7,0,3.2259,1.26,0,0.977,1.856,3,0,0,0,1.127,2.128,5.102,1,0,1,4,0.0,1,0,0,-0.002,0,3.765,0,0,0,0
 129,1.124,8.354,0,1,2.368,0,0,3.351,0.0,0,4,10.524,39.3,0,3.2786,1.266,0,0.978,1.671,3,0,0,0,1.126,2.188,5.375,1,0,1,3,0.0,1,0,1,0.004,0,3.766,0,0,0,0
 130,1.16,8.236,0,1,2.303,0,0,3.272,0.0,0,3,10.099,40.0,0,3.1448,1.268,0,0.981,1.602,3,0,0,0,1.125,2.212,4.958,1,0,1,3,0.0,1,0,0,-0.007,0,3.731,0,0,0,0
 131,1.194,8.65,0,1,2.463,0,0,3.664,0.0,0,7,11.033,37.2,0,3.563,1.253,0,0.972,1.828,4,0,0,0,1.13,2.039,5.489,1,0,1,4,0.0,1,0,2,0.0,0,3.852,0,0,0,0
 132,1.194,8.662,0,2,2.463,0,0,3.678,0.0,0,7,11.033,36.6,0,3.5897,1.237,0,0.982,1.828,4,0,0,0,1.132,2.275,5.489,2,0,1,6,0.0,1,0,2,0.0,0,3.853,0,0,0,0
 133,0.544,8.558,0,1,2.259,0,0,3.558,0.0,0,0,10.149,50.0,0,2.1739,1.304,0,0.986,2.952,3,0,0,0,1.104,2.179,4.709,1,0,1,2,0.0,2,0,0,-0.001,0,3.676,0,0,0,0
 134,1.169,8.497,0,2,2.301,0,0,3.573,0.0,0,2,10.26,39.4,0,2.0469,1.215,0,0.988,3.268,2,0,0,0,1.126,1.967,4.817,0,0,1,3,0.0,2,0,0,0.0,0,3.665,0,0,0,0
 135,2.125,8.337,0,2,2.27,0,0,3.601,0.0,0,2,10.029,36.8,0,2.7759,1.217,0,0.984,3.574,2,0,0,0,1.131,1.958,4.845,0,0,2,6,0.0,1,0,0,0.0,0,3.678,0,0,0,0
 136,1.23,8.414,0,2,2.375,0,0,3.437,0.0,0,3,10.559,37.9,0,3.3527,1.23,0,0.99,1.809,3,0,0,0,1.129,2.288,5.377,1,0,2,5,0.0,1,0,1,-0.002,0,3.774,0,0,0,0
 137,1.273,8.551,1,3,2.288,0,2,3.37,20.612,2,0,9.975,38.9,0,3.6002,1.21,0,1.041,1.602,2,0,1,0,1.132,2.985,4.953,0,0,2,6,0.0,1,0,0,-0.008,0,3.861,0,2,0,0
 138,1.16,8.601,1,3,2.305,0,1,3.375,20.537,3,1,10.099,38.9,0,3.6001,1.218,0,1.041,1.553,3,0,1,0,1.132,3.182,4.965,1,0,2,6,0.0,1,0,0,-0.008,0,3.88,0,2,0,0
 139,1.16,8.601,1,3,2.303,0,1,3.375,20.514,3,1,10.099,38.9,0,3.552,1.226,0,1.041,1.602,3,0,1,0,1.132,3.182,4.958,1,0,2,6,0.0,1,0,0,-0.008,0,3.876,0,2,0,0
 140,1.16,8.601,1,3,2.292,0,1,3.375,20.318,2,1,10.099,38.9,0,3.4973,1.222,0,1.041,1.696,3,0,1,0,1.132,3.182,4.895,1,0,2,7,0.0,1,0,0,-0.008,0,3.863,0,2,0,0
 141,1.45,9.052,2,5,2.417,0,4,3.798,42.668,4,2,10.639,34.5,0,3.8233,1.196,0,1.043,1.814,4,0,2,0,1.142,3.265,5.171,1,0,3,11,0.0,1,0,0,0.0,0,3.972,0,4,0,0
 142,0.875,8.476,0,1,2.194,1,0,3.214,0.0,0,0,9.579,46.2,1,3.3162,1.296,0,1.023,0.854,2,1,0,0,1.108,2.681,4.732,1,0,2,2,0.0,1,0,0,0.046,0,3.907,0,0,0,0
 143,0.875,8.473,0,1,2.175,1,0,3.214,0.0,0,0,9.54,46.2,1,3.2495,1.3,0,1.023,1.069,2,1,0,0,1.108,2.681,4.596,1,0,2,2,0.0,1,0,0,0.046,0,3.879,0,0,0,0
 144,0.875,11.593,0,1,2.17,1,0,3.796,0.0,0,0,9.54,46.2,0,3.173,1.347,1,1.016,1.14,2,1,0,0,1.1,2.51,4.562,1,0,2,2,0.0,1,0,0,0.045,0,6.879,1,0,0,0
 145,0.875,11.593,0,1,2.175,1,0,3.796,0.0,0,0,9.54,46.2,0,3.2243,1.355,1,1.016,1.069,2,1,0,0,1.1,2.51,4.596,1,0,2,2,0.0,1,0,0,0.045,0,6.88,1,0,0,0
 146,0.875,11.593,0,1,2.194,1,0,3.796,0.0,0,0,9.579,46.2,0,3.2896,1.351,1,1.016,0.854,2,1,0,0,1.1,2.51,4.732,1,0,2,2,0.0,1,0,0,0.045,0,6.88,1,0,0,0
 147,2.305,14.223,0,2,2.208,2,0,4.594,0.0,0,0,9.896,45.5,1,2.6198,1.412,0,1.021,4.243,2,2,0,0,1.098,2.326,4.619,0,0,2,5,0.0,1,0,0,0.001,0,10.695,0,0,0,0
 148,0.881,8.562,0,1,2.246,1,0,3.297,0.0,0,1,9.833,43.8,1,3.3155,1.296,0,1.012,1.06,3,1,0,0,1.113,2.568,4.807,1,0,2,2,0.0,1,0,0,-0.025,0,3.921,0,0,0,0
 149,0.881,8.87,0,1,2.246,2,0,3.462,0.0,0,0,9.833,46.2,1,3.3875,1.317,0,1.048,1.06,3,2,0,0,1.103,2.802,4.807,1,0,3,2,0.0,1,0,0,-0.026,0,4.009,0,0,0,0
 150,0.881,12.274,0,1,2.246,2,0,4.264,0.0,0,0,9.833,46.2,0,3.3439,1.415,1,1.034,1.06,3,2,0,0,1.088,2.5,4.807,1,0,3,2,0.0,1,0,0,-0.025,0,6.892,1,0,0,0
 151,0.881,8.872,0,1,2.264,2,0,3.462,0.0,0,0,9.863,46.2,1,3.4778,1.318,0,1.048,0.95,3,2,0,0,1.103,2.802,4.912,1,0,3,2,0.0,1,0,0,-0.026,0,4.068,0,0,0,0
 152,0.881,8.872,0,1,2.264,2,0,3.462,0.0,0,0,9.863,46.2,1,3.4781,1.317,0,1.048,0.95,3,2,0,0,1.103,2.802,4.912,1,0,3,2,0.0,1,0,0,-0.026,0,4.032,0,0,0,0
 153,0.881,8.87,0,1,2.246,2,0,3.462,0.0,0,0,9.833,46.2,1,3.3873,1.318,0,1.048,1.06,3,2,0,0,1.103,2.802,4.807,1,0,3,2,0.0,1,0,0,-0.026,0,4.05,0,0,0,0
 154,0.881,8.868,0,1,2.236,2,0,3.462,0.0,0,0,9.803,46.2,1,3.3803,1.328,0,1.048,0.95,3,2,0,0,1.103,2.802,4.732,1,0,3,2,0.0,1,0,0,-0.026,0,3.998,0,0,0,0
 155,1.124,9.175,1,3,2.353,2,1,3.715,20.509,2,0,10.277,40.0,1,3.8133,1.261,0,1.1,1.513,4,2,1,0,1.123,3.407,5.071,1,0,4,6,0.0,1,0,0,0.005,0,4.076,0,2,0,0
 156,0.0,8.536,0,1,2.194,0,0,3.609,0.0,0,0,10.054,48.3,0,1.9651,1.296,0,0.983,4.13,2,0,0,0,1.107,1.989,4.562,0,0,0,4,0.0,2,0,0,0.0,0,3.587,0,0,0,0
 157,0.544,8.63,0,1,2.307,0,0,3.579,11.846,0,0,10.193,54.2,0,2.3618,1.313,0,0.989,2.627,2,0,0,0,1.095,2.286,4.962,0,0,0,4,0.075,2,0,0,-0.001,0,3.755,0,0,0,0
 158,1.261,8.435,2,0,2.214,0,4,3.292,0.0,4,0,9.714,57.1,0,3.0954,1.35,0,1.006,1.783,2,0,0,0,1.101,2.833,4.641,0,0,0,0,0.0,1,0,0,0.015,0,3.726,0,2,0,0
 159,1.197,9.543,2,0,2.438,4,4,4.005,0.0,4,0,10.51,57.1,1,3.9658,1.402,0,1.099,1.254,6,4,0,0,1.085,3.103,5.267,0,0,4,0,0.0,1,0,0,0.001,0,4.254,0,2,0,0
 160,1.831,9.113,2,2,2.296,2,4,3.83,11.353,4,0,10.363,36.0,1,3.0922,1.25,0,1.037,3.18,3,2,0,0,1.135,2.659,4.869,1,0,3,2,-0.393,1,0,0,-0.001,0,4.051,0,3,0,0
 161,0.824,10.284,2,5,2.42,4,7,4.622,35.742,6,0,11.344,44.2,1,2.1249,1.296,0,1.056,5.31,9,5,0,0,1.108,2.823,5.387,3,0,9,12,-0.656,3,0,0,0.0,0,4.741,0,4,0,0
 162,1.805,8.49,1,2,2.322,0,2,3.582,11.111,1,2,10.269,37.5,0,3.2017,1.221,0,0.995,2.668,2,0,0,0,1.132,2.322,4.994,1,0,1,6,-0.425,1,0,0,-0.001,0,3.713,0,0,0,0
 163,1.733,8.464,1,2,2.311,0,2,3.525,11.023,1,2,10.222,37.9,0,3.2319,1.222,0,0.998,2.571,2,0,0,0,1.132,2.381,4.975,1,0,1,6,-0.432,1,0,0,0.001,0,3.713,0,0,0,0
 164,1.604,8.667,2,2,2.294,0,2,3.533,19.925,5,1,10.05,47.4,0,3.4872,1.275,0,1.033,2.223,3,0,0,0,1.118,2.923,4.872,0,0,2,2,0.0,1,0,0,-0.002,0,3.783,0,4,0,0
 165,1.125,7.158,0,0,2.136,0,0,2.843,0.0,0,1,9.311,33.3,0,2.125,1.199,0,0.961,1.481,0,0,0,1,1.138,1.542,4.499,0,0,0,0,0.0,1,0,0,0.034,0,3.15,0,0,0,0
 166,0.0,6.76,0,0,2.0,0,0,2.565,0.0,0,0,8.623,33.3,0,2.0,1.167,0,0.961,0.667,0,0,0,0,1.138,1.5,4.0,0,0,0,0,0.0,1,0,0,0.103,0,3.003,0,0,0,0
 167,0.0,7.081,0,0,2.0,0,0,2.618,0.0,0,0,8.623,37.5,0,2.2551,1.226,0,0.964,0.667,0,0,0,0,1.13,1.667,4.0,0,0,0,0,0.0,1,0,0,0.112,0,3.175,0,0,0,0
 168,0.799,13.179,0,0,2.414,6,0,5.031,0.0,0,0,10.434,33.3,1,2.8937,1.534,1,1.043,0.873,0,6,0,0,1.091,2.155,5.236,0,0,0,0,0.0,1,0,0,0.004,0,6.951,1,0,0,0
 169,0.802,7.988,0,0,2.101,1,0,2.995,0.0,0,0,9.183,33.3,1,2.1712,1.23,0,0.979,0.975,0,1,0,0,1.135,1.849,4.414,0,0,0,0,0.0,1,0,0,-0.064,0,3.658,0,0,0,0
 170,0.827,12.953,0,0,2.247,4,0,4.816,0.0,0,0,10.135,33.3,0,2.5137,1.457,1,0.999,1.244,0,4,0,0,1.112,1.861,4.814,0,0,0,0,0.0,1,0,0,0.003,0,6.915,1,0,0,0
 171,2.184,14.019,0,1,2.466,5,0,4.883,0.0,0,3,11.058,34.6,1,3.3983,1.391,0,0.998,3.079,6,6,0,0,1.12,2.159,5.401,0,0,6,5,0.0,1,0,0,0.0,0,10.323,0,0,0,0
 172,1.693,9.707,1,5,2.357,0,1,3.931,21.265,3,1,10.742,31.0,0,3.4588,1.273,0,1.038,3.021,3,2,1,0,1.127,2.822,5.276,0,0,2,12,0.0,1,0,0,0.0,0,4.702,0,2,0,0
 173,0.799,13.184,0,1,2.414,5,0,5.017,0.0,0,0,10.434,46.2,0,3.8407,1.542,1,1.086,0.873,6,5,0,0,1.051,2.479,5.236,1,0,6,2,0.0,1,0,0,0.004,0,6.982,1,0,0,0
 174,1.162,8.814,0,3,2.467,0,0,3.762,11.22,0,6,11.1,37.5,0,3.6981,1.233,0,0.993,1.737,4,0,0,0,1.13,2.546,5.459,2,0,1,8,-1.093,1,0,2,0.0,0,3.883,0,0,0,0
 175,1.846,9.894,0,4,2.394,4,0,4.233,11.888,0,0,10.866,35.7,1,3.5985,1.297,0,1.063,3.082,4,5,0,0,1.116,2.794,5.295,0,0,3,11,-0.016,1,0,0,0.0,0,4.432,0,0,0,0
 176,0.816,8.539,0,0,2.307,0,0,3.542,0.0,0,1,10.187,50.0,0,2.343,1.322,0,0.971,2.434,3,0,0,0,1.104,1.893,4.868,0,0,0,0,0.0,2,0,0,-0.001,0,3.738,0,0,0,0
 177,0.703,8.682,0,0,2.374,0,0,3.66,0.0,0,3,10.497,47.1,0,2.4193,1.324,0,0.969,2.706,4,0,0,0,1.11,1.875,5.114,0,0,0,0,0.0,2,0,0,0.0,0,3.771,0,0,0,0
 178,0.648,8.636,2,0,2.275,0,2,3.617,0.0,4,0,10.3,44.8,0,2.1649,1.293,0,0.983,3.095,4,0,0,0,1.12,2.144,4.732,4,0,2,0,0.0,2,0,0,0.0,0,3.694,0,4,0,0
 179,0.548,8.859,0,2,2.488,0,0,3.889,0.0,0,0,10.936,45.0,0,2.1018,1.259,0,0.987,2.321,4,0,0,0,1.114,2.171,5.611,2,0,2,4,0.0,3,0,1,0.0,0,3.787,0,0,0,0
 180,0.732,9.249,0,2,2.349,2,0,3.947,0.0,0,0,10.578,48.1,1,2.4328,1.305,0,1.022,3.001,6,2,0,0,1.104,2.572,4.961,2,0,4,6,0.0,2,0,0,0.0,0,3.939,0,0,0,0
 181,0.74,9.891,0,2,2.449,6,0,4.379,0.0,0,0,10.991,48.1,1,2.7448,1.336,0,1.07,3.068,10,6,0,0,1.095,2.802,5.221,2,0,8,6,0.0,2,0,0,0.0,0,4.183,0,0,0,0
 182,0.732,9.239,2,0,2.329,2,2,3.936,0.0,4,0,10.577,44.8,1,2.291,1.32,0,1.005,3.219,6,2,0,0,1.116,2.337,4.887,4,0,4,0,0.0,2,0,0,0.0,0,3.954,0,4,0,0
 183,1.006,9.14,0,2,2.459,0,0,4.08,0.0,0,8,11.361,40.4,0,2.605,1.277,0,0.979,3.688,8,0,0,0,1.124,2.133,5.415,2,0,2,8,0.0,2,0,2,0.0,0,3.872,0,0,0,0
 184,0.732,8.174,2,0,2.329,0,2,3.616,0.0,6,2,10.577,31.9,0,1.7855,1.211,0,0.97,3.219,0,0,0,4,1.145,1.794,4.887,4,0,0,0,0.0,2,0,0,0.0,0,3.374,0,4,0,0
 185,0.732,8.784,0,2,2.42,0,0,3.741,0.0,0,2,10.806,45.5,0,2.4453,1.271,0,0.992,2.731,4,0,0,0,1.113,2.348,5.511,2,0,2,4,0.0,2,0,1,0.0,0,3.785,0,0,0,0
 186,2.094,8.963,0,3,2.372,0,0,4.049,12.363,0,1,10.679,42.0,0,1.9467,1.25,0,0.989,5.623,4,0,0,0,1.121,2.222,5.076,1,0,2,10,-0.185,2,0,0,0.0,0,3.827,0,0,0,0
 187,1.33,9.362,0,3,2.481,2,0,4.116,12.298,0,1,10.978,45.7,1,2.6715,1.279,0,1.02,2.211,4,2,0,0,1.11,2.562,5.656,1,0,2,9,-0.741,2,0,1,0.0,0,3.944,0,0,0,0
 188,0.74,12.971,0,2,2.475,4,0,5.001,0.0,0,2,11.131,45.5,0,2.6742,1.4,1,1.019,2.978,8,4,0,0,1.094,2.361,5.534,2,0,6,4,0.0,2,0,1,0.0,0,6.896,1,0,0,0
 189,0.629,8.48,1,0,2.351,0,3,3.347,0.0,3,0,10.084,50.0,0,2.9434,1.321,0,0.982,1.075,3,0,0,0,1.108,2.091,5.003,2,0,1,0,0.0,3,0,0,0.004,0,3.876,0,2,0,0
 190,0.73,8.577,2,0,2.39,0,6,3.429,0.0,6,0,10.265,45.5,0,2.9965,1.301,0,0.988,1.128,4,0,0,0,1.121,2.222,5.097,4,0,2,0,0.0,3,0,0,-0.002,0,3.918,0,4,0,0
 191,0.73,8.577,2,0,2.394,0,6,3.429,0.0,6,0,10.265,45.5,0,3.0152,1.302,0,0.988,1.098,4,0,0,0,1.121,2.222,5.119,4,0,2,0,0.0,3,0,0,-0.002,0,3.921,0,4,0,0
 192,0.0,8.875,1,0,2.359,0,3,3.772,0.0,4,0,10.465,53.3,0,2.0578,1.34,0,0.98,3.08,4,0,0,0,1.1,1.951,4.933,1,0,2,0,0.0,4,0,0,0.0,0,3.865,0,4,1,0
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 324,2.23,7.528,1,1,2.093,0,2,3.231,0.0,2,3,9.449,28.6,0,3.6384,1.166,0,0.976,2.764,0,0,0,0,1.151,2.0,4.491,1,0,0,0,0.0,0,0,0,-0.007,0,3.167,0,3,0,0
 325,2.281,7.135,0,1,1.902,0,0,2.938,0.0,0,2,8.743,29.6,0,2.8492,1.169,0,0.973,3.685,0,0,0,0,1.146,1.833,3.879,0,0,0,2,0.0,0,0,0,0.04,0,2.997,0,0,0,0
 326,2.161,8.553,0,4,2.298,0,0,3.781,0.0,0,10,11.219,29.6,0,4.9583,1.164,0,0.988,5.013,0,0,0,0,1.146,2.1,5.283,0,0,0,14,0.0,0,0,4,0.0,0,3.48,0,0,0,0
 327,2.027,8.181,0,7,2.303,0,0,3.66,0.0,0,6,10.771,25.6,0,4.7687,1.068,0,1.026,3.918,0,0,0,0,1.155,3.176,5.333,6,0,0,24,0.0,0,0,2,0.0,0,3.394,0,0,0,0
 328,2.192,7.861,0,4,2.098,0,0,3.368,0.0,0,4,9.868,27.3,0,3.906,1.107,0,1.004,4.063,0,0,0,0,1.151,2.577,4.482,2,0,0,3,0.0,0,0,0,0.004,0,3.248,0,0,0,0
 329,4.297,8.904,2,2,2.086,0,4,4.479,24.053,2,2,10.675,32.2,0,3.3381,1.198,0,0.971,15.507,0,0,0,0,1.142,1.841,4.412,2,0,0,4,0.253,0,0,0,0.0,0,3.374,0,4,0,0
 330,2.252,8.066,4,2,2.047,0,4,3.343,21.129,4,0,9.65,23.1,0,3.3651,1.115,0,1.018,4.178,0,0,0,0,1.173,3.028,4.38,6,0,0,2,-0.439,0,2,0,-0.008,2,3.366,0,4,0,0
 331,1.371,12.27,0,4,2.214,2,0,4.298,20.21,0,0,9.956,28.6,0,4.3619,1.246,0,1.101,2.232,0,2,0,0,1.126,3.75,4.947,2,0,0,4,-2.409,0,0,0,-0.028,0,6.911,1,0,0,0
 332,1.776,8.405,1,6,2.175,0,0,3.49,30.436,0,0,10.007,27.3,0,4.5744,1.099,0,1.073,2.211,0,0,0,0,1.155,3.885,4.675,3,0,0,0,-3.785,0,0,0,0.005,0,3.488,0,3,0,0
 333,1.837,9.521,0,2,2.175,0,0,3.463,0.0,0,2,9.966,21.1,0,4.1948,1.35,0,1.007,2.244,0,3,0,0,1.119,2.46,5.182,0,0,0,2,0.0,0,0,0,0.045,0,4.828,0,0,0,0
 334,1.241,9.077,3,1,2.376,0,0,3.361,12.09,12,0,10.509,20.7,0,5.159,1.231,0,0.989,1.357,0,1,0,0,1.164,2.346,5.602,0,0,0,6,0.0,0,0,0,0.013,0,4.468,0,0,0,0
 335,2.388,13.367,0,4,2.284,6,0,5.27,12.499,0,3,10.649,25.7,0,5.1487,1.379,0,1.039,3.036,0,7,0,0,1.119,2.39,5.27,0,0,0,12,0.0,0,0,0,0.0,0,6.912,1,0,0,0
 336,2.47,9.066,0,4,2.194,0,0,3.503,11.075,0,2,10.126,25.0,0,3.9866,1.158,0,1.004,3.798,0,1,0,0,1.147,2.6,5.184,1,0,0,8,0.0,0,0,0,0.004,0,4.432,0,0,0,0
 337,2.383,14.7,0,1,2.414,0,0,5.083,0.0,0,6,10.95,29.6,0,5.4486,1.397,0,0.961,3.022,0,2,0,0,1.132,1.604,5.509,0,0,0,6,0.0,0,0,0,0.0,0,10.428,0,0,0,0
 338,2.184,14.008,0,2,2.318,0,0,4.494,11.379,0,4,10.42,29.8,0,4.4437,1.343,0,0.973,1.951,0,1,0,0,1.134,2.005,5.349,0,0,0,3,-0.024,0,0,0,0.0,0,10.323,0,0,0,0
 339,3.105,14.007,0,0,2.309,0,0,4.785,0.0,0,4,10.724,31.7,0,4.5365,1.292,0,0.959,3.559,0,1,0,0,1.136,1.528,5.333,0,0,0,0,0.0,0,0,0,0.0,0,10.319,0,0,0,0
 340,1.895,7.746,1,0,2.074,0,0,3.135,0.0,3,0,9.292,36.0,0,3.8606,1.285,0,0.971,2.02,0,0,0,0,1.136,2.15,4.481,0,0,0,0,0.0,0,0,0,-0.024,0,3.257,0,3,0,0
 341,2.027,8.143,0,5,2.303,0,0,3.631,0.0,0,6,10.771,27.9,0,4.7127,1.107,0,1.003,3.918,0,0,0,0,1.15,2.706,5.333,4,0,0,18,0.0,0,0,2,0.0,0,3.386,0,0,0,0
 342,0.732,9.875,0,2,2.42,2,0,4.046,24.34,0,0,10.806,48.0,1,2.626,1.347,0,1.032,2.731,4,3,0,0,1.092,2.694,5.511,0,0,4,8,0.0,2,0,0,0.0,0,4.738,0,0,0,0
 343,1.124,9.259,0,2,2.368,3,0,3.792,10.567,0,0,10.297,46.7,1,3.6483,1.31,0,1.085,1.45,4,3,0,0,1.1,3.139,5.138,1,0,3,4,-1.188,1,0,0,0.004,0,4.147,0,0,0,0
 344,1.187,7.982,1,0,2.194,0,1,3.08,0.0,2,0,9.642,40.0,0,3.0271,1.27,0,0.976,1.659,1,0,0,0,1.129,1.963,4.732,0,0,1,0,0.0,1,0,0,-0.024,0,3.601,0,2,0,0
 345,0.881,8.103,1,0,2.264,0,2,3.087,0.0,3,2,9.863,40.0,0,3.2927,1.286,0,0.976,0.95,3,0,0,0,1.129,2.111,4.912,2,0,1,0,0.0,1,0,0,-0.024,0,3.719,0,2,0,0
 346,0.881,8.095,1,0,2.236,0,3,3.087,0.0,2,2,9.803,40.0,0,3.2078,1.298,0,0.976,0.95,3,0,0,0,1.129,2.111,4.732,2,0,1,0,0.0,1,0,0,-0.024,0,3.695,0,2,0,0
 347,1.461,8.047,1,0,2.203,0,1,3.168,0.0,2,2,9.69,39.1,0,2.8239,1.27,0,0.974,2.063,2,0,0,0,1.13,1.933,4.616,1,0,1,0,0.0,1,0,0,0.013,0,3.63,0,3,0,0
 348,1.187,8.005,1,0,2.222,0,1,3.08,0.0,3,1,9.668,40.0,0,3.1257,1.273,0,0.976,1.358,2,0,0,0,1.129,1.981,4.783,1,0,1,0,0.0,1,0,0,-0.024,0,3.65,0,2,0,0
 349,1.491,8.765,2,0,2.285,0,5,3.859,0.0,7,3,10.536,40.9,0,2.0515,1.282,0,0.976,4.361,3,0,0,0,1.126,1.908,4.75,2,0,3,0,0.0,2,0,0,0.0,0,3.689,0,8,1,0
 350,1.085,8.671,2,0,2.279,0,3,3.72,0.0,6,2,10.361,42.9,0,2.1754,1.288,0,0.979,3.551,3,0,0,0,1.123,1.961,4.739,2,0,3,0,0.0,2,0,0,0.0,0,3.688,0,8,1,0
 351,0.0,8.602,1,2,2.375,0,1,3.6,0.0,4,0,10.272,40.0,0,1.8312,1.195,0,0.998,2.221,1,0,0,0,1.127,1.956,4.88,0,0,1,0,0.0,3,0,0,0.0,0,3.627,0,4,0,0
 352,0.875,7.969,2,0,2.175,0,2,2.997,0.0,4,0,9.54,37.5,0,3.1791,1.254,0,0.991,1.069,2,0,0,0,1.14,2.417,4.596,4,0,2,0,0.0,1,0,0,0.045,0,3.638,0,4,0,0
 353,0.875,8.463,1,0,2.175,1,1,3.202,0.0,2,0,9.54,42.9,1,3.2067,1.316,0,1.005,1.069,2,1,0,0,1.121,2.431,4.596,2,0,2,0,0.0,1,0,0,0.045,0,3.876,0,2,0,0
 354,0.875,8.466,1,0,2.194,1,1,3.202,0.0,2,0,9.579,42.9,1,3.271,1.312,0,1.005,0.854,2,1,0,0,1.121,2.431,4.732,2,0,2,0,0.0,1,0,0,0.045,0,3.903,0,2,0,0
 355,1.185,8.096,1,0,2.236,0,1,3.175,0.0,2,2,9.882,39.1,0,2.9221,1.27,0,0.974,1.74,2,0,0,0,1.13,2.067,4.77,2,0,1,0,0.0,1,0,0,0.013,0,3.651,0,2,0,0
 356,0.5,8.68,1,2,2.396,0,1,3.657,0.0,5,1,10.424,39.4,0,1.8996,1.204,0,0.995,2.271,2,0,0,0,1.128,1.938,5.005,0,0,1,0,0.0,3,0,0,0.0,0,3.697,0,4,0,0
 357,1.185,8.497,1,2,2.243,0,2,3.278,20.317,2,1,9.882,41.2,0,3.4006,1.253,0,1.024,1.686,2,0,1,0,1.127,2.933,4.796,0,0,1,4,0.0,1,0,0,0.015,0,3.835,0,2,0,0
 358,1.185,8.499,1,2,2.267,0,1,3.278,20.455,3,1,9.911,41.2,0,3.5053,1.254,0,1.024,1.563,2,0,1,0,1.127,2.933,4.923,0,0,1,4,0.0,1,0,0,0.015,0,3.854,0,2,0,0
 359,1.185,8.497,1,2,2.236,0,1,3.278,20.236,2,1,9.882,41.2,0,3.3176,1.253,0,1.024,1.74,2,0,1,0,1.127,2.933,4.77,0,0,1,4,0.0,1,0,0,0.015,0,3.83,0,2,0,0
 360,0.881,8.118,0,1,2.264,0,0,3.1,0.0,0,2,9.863,42.1,0,3.3307,1.271,0,0.987,0.95,3,0,0,0,1.12,2.333,4.912,1,0,1,4,0.0,1,0,0,-0.024,0,3.728,0,0,0,0
 361,0.861,8.242,0,1,2.318,0,0,3.193,0.0,0,3,10.084,40.9,0,3.4136,1.269,0,0.983,0.984,4,0,0,0,1.123,2.267,5.027,1,0,1,4,0.0,1,0,0,0.013,0,3.784,0,0,0,0
 362,1.185,8.175,1,1,2.267,0,3,3.198,0.0,2,1,9.902,38.1,0,3.2928,1.241,0,0.993,1.393,3,0,0,0,1.133,2.25,4.845,2,0,2,2,0.0,1,0,0,0.014,0,3.718,0,2,0,0
 363,0.544,8.573,0,1,2.264,0,0,3.558,0.0,0,1,10.15,50.0,0,2.4398,1.31,0,0.986,2.919,3,0,0,0,1.104,2.036,4.732,0,0,2,4,0.0,2,0,0,-0.001,0,3.699,0,0,0,0
 364,1.621,9.671,2,4,2.508,7,5,4.672,24.703,6,8,11.98,37.5,0,2.4858,1.152,0,1.033,7.425,6,0,0,0,1.162,3.161,5.979,3,0,4,10,-3.631,2,0,5,0.0,0,3.867,0,6,0,1
 365,1.315,10.183,4,5,2.374,0,8,4.22,45.922,6,0,11.166,32.4,0,2.4228,1.236,0,1.044,4.369,4,2,0,0,1.134,3.0,5.369,6,0,4,12,0.0,2,2,0,0.0,0,4.714,0,2,0,0
 366,1.662,8.804,0,3,2.281,1,0,3.613,10.2,0,1,10.15,40.9,1,3.0549,1.234,0,1.033,2.83,3,1,0,0,1.12,2.829,4.856,1,0,2,3,-0.991,1,0,0,-0.002,0,3.904,0,0,0,0
 367,1.006,9.332,0,2,2.449,0,0,4.144,0.0,0,8,11.361,40.0,0,2.6091,1.301,0,0.982,3.714,8,1,0,0,1.119,2.147,5.395,2,0,4,6,0.0,2,0,2,0.0,0,4.055,0,0,0,0
 368,1.546,8.33,1,1,2.278,0,1,3.442,10.413,2,2,10.067,39.3,0,3.0066,1.246,0,0.986,2.303,2,0,0,0,1.129,2.256,4.849,0,0,1,2,0.0,1,0,0,-0.002,0,3.682,0,4,0,0
 369,1.197,9.544,2,0,2.439,4,6,4.005,0.0,4,0,10.51,57.1,1,3.9791,1.399,0,1.099,1.098,6,4,0,0,1.085,3.103,5.268,0,0,4,0,0.0,1,0,0,0.001,0,4.262,0,2,0,0
 370,1.16,9.496,1,2,2.311,0,2,3.484,21.444,2,1,10.388,35.0,0,3.3759,1.27,0,1.018,1.833,2,1,0,0,1.125,2.932,5.313,2,0,1,4,0.0,1,0,0,-0.008,0,4.725,0,1,0,0
 371,1.197,9.679,1,5,2.389,0,1,3.739,42.164,2,1,10.666,33.3,0,3.8121,1.221,0,1.07,1.962,3,1,1,0,1.129,3.565,5.38,1,0,2,10,0.0,1,0,0,0.001,0,4.74,0,2,0,0
 372,0.662,8.832,3,0,2.298,0,10,3.793,0.0,10,2,10.516,42.9,0,2.3994,1.289,0,0.985,4.008,4,0,0,0,1.126,2.102,4.876,3,0,2,0,0.401,2,0,0,0.0,0,3.742,0,4,0,0
 373,1.662,8.46,1,2,2.278,0,2,3.464,10.87,1,2,10.144,38.5,0,3.1901,1.237,0,1.002,2.609,3,0,0,0,1.131,2.436,4.795,1,0,1,5,-0.44,1,0,0,-0.002,0,3.724,0,0,0,0
 374,0.76,13.359,0,0,2.247,6,0,5.219,0.0,0,0,10.54,33.3,0,2.6622,1.452,1,0.999,1.366,0,6,0,0,1.112,1.861,4.814,0,0,0,0,0.0,1,0,0,0.0,0,6.918,1,0,0,0
 375,0.0,8.16,0,2,2.487,0,0,3.183,0.0,0,0,10.081,36.4,0,1.7046,1.147,0,0.998,1.669,0,0,0,1,1.132,1.833,4.821,0,0,0,4,0.0,4,0,0,0.004,0,3.552,0,0,0,0
 376,0.861,8.072,0,1,2.327,0,0,3.163,11.013,0,3,10.335,37.5,0,2.8227,1.277,0,0.98,1.037,0,0,0,0,1.13,2.258,5.256,0,0,0,2,1.509,1,0,1,0.012,0,3.597,0,0,0,0
 377,1.009,8.901,0,7,2.381,0,0,4.024,46.833,0,0,10.889,35.6,0,2.1775,1.153,0,1.022,4.315,0,0,0,4,1.134,2.935,5.105,2,0,0,18,-3.756,2,0,0,0.0,0,3.644,0,0,0,0
 378,1.773,9.497,0,4,2.351,0,0,4.151,13.18,0,2,10.862,38.5,0,2.3744,1.258,0,0.993,3.749,2,1,0,0,1.123,2.179,5.312,0,0,2,15,0.0,2,0,0,0.0,0,4.432,0,0,0,0
 379,1.11,14.03,1,0,2.527,0,3,4.802,0.0,0,0,11.097,45.7,0,2.1601,1.471,0,0.977,1.942,3,3,0,0,1.09,1.943,5.718,0,0,0,0,0.951,3,0,0,0.0,0,10.349,0,0,0,0
 380,2.058,9.789,0,4,2.36,0,0,4.046,12.071,0,1,10.721,33.3,0,3.2179,1.309,0,1.011,2.598,1,3,0,0,1.115,2.42,5.301,0,0,0,7,-0.331,1,0,0,0.0,0,4.824,0,0,0,0
 381,1.197,9.801,1,4,2.397,0,1,4.116,21.296,2,1,10.882,40.0,0,2.5224,1.308,0,1.018,3.431,3,2,1,0,1.111,2.57,5.446,0,0,3,12,0.0,2,0,0,0.0,0,4.719,0,2,0,0
 382,1.758,8.227,0,1,2.224,0,0,3.361,10.332,0,1,9.82,42.3,0,2.596,1.276,0,0.981,2.705,2,0,0,0,1.12,2.236,4.65,0,0,0,2,0.0,1,0,0,0.004,0,3.652,0,0,0,0
 383,0.799,9.557,0,1,2.414,5,0,3.967,0.0,0,0,10.434,46.2,1,3.9253,1.352,0,1.123,0.873,6,5,0,0,1.09,3.046,5.236,1,0,6,2,0.0,1,0,0,0.004,0,4.295,0,0,0,0
 384,1.781,13.183,0,1,2.35,5,0,5.069,0.0,0,2,10.7,40.0,0,3.1467,1.461,1,1.026,3.228,4,5,0,0,1.093,2.135,5.188,0,0,4,4,0.0,1,0,1,0.0,0,6.914,1,0,0,0
 385,0.569,8.148,0,1,2.327,0,0,3.408,11.653,0,0,10.158,38.7,0,2.0546,1.236,0,0.977,2.096,0,0,0,1,1.127,1.974,4.985,0,0,0,3,1.982,2,0,0,0.001,0,3.547,0,0,0,0
 386,1.555,8.93,0,4,2.426,0,0,4.013,0.0,0,4,10.927,40.4,0,2.2581,1.227,0,0.998,4.054,4,0,0,0,1.124,2.301,5.512,2,0,2,4,0.0,2,0,1,0.0,0,3.787,0,0,0,0
 387,0.541,9.367,0,1,2.5,0,0,4.332,0.0,0,3,11.225,49.2,0,1.9393,1.312,0,0.977,2.737,7,0,0,0,1.106,1.989,5.349,1,0,1,3,0.0,4,0,0,0.0,0,3.882,0,0,0,0
 388,1.707,13.654,0,2,2.484,8,0,5.587,0.0,0,4,11.349,41.2,0,2.4918,1.429,1,1.017,4.711,8,8,0,0,1.097,2.073,5.535,0,0,6,6,0.0,2,0,1,0.0,0,6.912,1,0,0,0
 389,1.126,8.899,0,3,2.384,0,0,3.829,23.875,0,0,10.558,50.0,0,2.5259,1.269,0,1.009,2.895,3,0,0,0,1.104,2.546,5.131,0,1,0,9,-0.688,2,0,0,0.0,0,3.833,0,0,0,0
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 393,1.139,8.536,1,0,2.369,0,3,3.479,0.0,3,1,10.174,46.2,0,2.7083,1.312,0,0.977,1.808,3,0,0,0,1.115,1.923,5.029,1,0,1,0,0.0,3,0,0,0.001,0,3.875,0,3,0,0
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 397,0.73,11.646,1,3,2.551,1,3,4.305,24.769,3,0,10.964,51.9,0,2.4805,1.309,1,1.031,1.407,7,1,0,0,1.097,2.724,5.416,3,0,3,11,-0.735,6,0,0,0.0,0,6.88,1,2,0,0
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 400,0.72,13.877,0,0,2.532,10,0,5.692,0.0,0,0,11.151,54.5,0,3.1295,1.617,1,1.078,2.359,12,10,0,0,1.022,2.159,5.418,0,0,10,0,0.0,2,0,0,0.0,0,6.991,1,0,0,0
 401,0.75,9.228,2,0,2.368,2,2,3.896,0.0,4,0,10.568,46.2,1,2.5599,1.323,0,1.01,2.478,6,2,0,0,1.114,2.389,4.992,4,0,4,0,0.0,2,0,0,0.0,0,3.989,0,4,0,0
 402,1.745,8.855,1,0,2.33,0,2,3.88,0.0,2,1,10.484,46.3,0,1.9828,1.311,0,0.974,4.222,4,0,0,0,1.113,2.033,4.89,0,0,0,0,0.0,2,0,0,0.0,0,3.779,0,1,0,0
 403,0.648,8.623,0,0,2.312,0,0,3.603,0.0,0,2,10.32,48.4,0,2.2807,1.334,0,0.97,2.866,4,0,0,0,1.107,1.878,4.893,0,0,0,0,0.0,2,0,0,0.0,0,3.728,0,0,0,0
 404,4.12,8.485,2,1,2.306,0,2,3.937,11.381,4,1,10.222,31.8,0,1.6696,1.175,0,0.973,9.52,0,0,0,0,1.144,1.819,4.644,1,0,0,3,0.135,1,0,0,0.0,0,3.532,0,1,0,0
 405,0.862,8.506,0,0,2.115,0,0,2.938,0.0,0,1,9.067,41.7,0,3.1007,1.439,0,0.977,0.956,0,1,0,0,1.097,1.917,4.303,0,0,0,0,0.0,1,0,0,0.125,0,4.069,0,0,0,0
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 407,0.0,9.901,2,0,2.406,0,4,4.212,0.0,4,0,10.767,50.0,0,1.7012,1.455,0,1.006,4.164,4,4,0,0,1.069,1.967,4.802,0,0,0,0,0.0,6,0,0,0.0,0,4.462,0,4,0,0
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 409,0.802,7.821,1,0,2.101,0,0,2.868,0.0,1,1,9.183,42.9,0,3.1806,1.295,0,0.982,0.975,0,0,0,0,1.125,2.095,4.414,0,0,0,0,0.0,1,0,0,-0.077,0,3.579,0,3,0,0
 410,0.802,7.817,1,0,2.101,0,0,2.868,0.0,2,1,9.183,42.9,0,3.1554,1.298,0,0.982,0.975,0,0,0,0,1.125,2.095,4.414,0,0,0,0,0.0,1,0,0,-0.077,0,3.573,0,2,0,0
 411,0.802,8.386,1,0,2.101,1,0,3.11,0.0,1,0,9.183,45.5,1,3.2871,1.323,0,1.018,0.975,0,1,0,0,1.116,2.397,4.414,0,0,0,0,0.0,1,0,0,-0.081,0,3.867,0,2,0,0
 412,1.125,8.126,2,0,2.136,0,1,3.059,0.0,4,0,9.311,50.0,0,3.1749,1.315,0,1.007,1.481,0,0,0,0,1.118,2.646,4.499,0,0,0,0,0.0,1,0,0,0.047,0,3.653,0,3,0,0
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 414,0.0,8.4,1,0,2.303,0,1,3.268,0.0,3,0,9.863,52.9,0,2.9856,1.338,0,0.985,1.047,2,0,0,0,1.103,2.033,4.861,0,0,0,0,0.0,3,0,0,-0.007,0,3.842,0,3,0,0
 415,1.25,8.634,1,1,2.447,0,2,3.647,0.0,3,4,10.764,40.0,0,2.5675,1.265,0,0.982,1.996,3,0,0,1,1.127,1.964,5.325,1,0,2,2,1.306,3,0,1,0.0,0,3.826,0,5,0,0
 416,0.0,8.885,2,2,2.211,0,4,3.676,0.0,0,0,10.013,26.7,0,1.8586,1.215,0,1.007,3.499,0,2,0,0,1.139,1.905,4.599,0,0,0,0,0.0,2,0,0,-0.001,0,4.125,0,4,0,0
 417,0.0,6.883,2,0,2.0,0,0,2.605,0.0,0,0,8.623,25.0,0,2.1902,1.107,0,0.984,0.667,0,0,0,0,1.166,1.833,4.0,2,0,0,0,0.0,1,0,0,0.121,0,3.061,0,4,0,0
 418,0.673,8.682,5,0,2.334,0,7,3.584,0.0,11,0,10.289,39.1,0,2.6974,1.242,0,1.012,2.214,1,0,0,0,1.144,2.405,4.93,4,0,0,0,0.0,2,0,0,-0.001,0,3.835,0,2,0,0
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 421,0.584,9.377,2,4,2.419,0,2,4.252,46.841,4,0,11.145,51.2,0,1.5353,1.286,0,1.02,4.947,4,0,0,0,1.105,2.623,5.067,0,0,2,12,-1.375,4,0,0,0.0,0,3.833,0,8,0,0
 422,1.251,9.397,2,3,2.473,2,6,4.14,12.059,8,5,11.115,37.5,1,2.7525,1.26,0,1.02,3.069,4,2,0,0,1.131,2.446,5.31,0,0,4,8,-0.278,2,1,1,0.0,0,4.063,0,6,0,0
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 424,0.875,7.325,1,0,2.175,0,0,2.867,0.0,1,2,9.54,30.4,0,2.3621,1.2,0,0.969,1.069,0,0,0,0,1.148,1.708,4.596,1,0,0,0,0.0,1,0,0,0.037,0,3.247,0,4,0,0
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 426,1.59,8.773,5,0,2.294,1,6,3.637,0.0,11,3,10.18,28.6,1,3.2336,1.221,0,1.009,2.457,0,1,0,0,1.161,2.282,4.816,2,0,0,0,0.0,1,0,0,0.001,0,3.951,0,3,0,0
 427,1.362,9.014,0,3,2.616,0,0,3.964,24.463,0,5,11.07,39.6,0,2.2204,1.257,0,0.989,4.097,0,0,0,2,1.126,2.322,5.219,0,0,0,11,2.753,2,0,1,0.0,0,3.791,0,0,0,0
 428,1.938,8.541,1,1,2.337,0,2,3.587,11.766,4,3,10.289,40.6,0,3.2439,1.276,0,0.984,2.563,2,0,0,0,1.126,2.233,5.065,0,0,1,3,0.036,1,0,0,-0.001,0,3.728,0,4,0,0
 429,1.092,9.13,1,4,2.613,0,3,4.066,37.047,3,4,11.197,38.8,0,1.781,1.225,0,1.0,4.681,0,0,0,2,1.129,2.413,5.216,0,0,0,15,1.53,4,0,1,0.0,0,3.848,0,2,0,0
 430,0.75,8.764,2,0,2.368,0,2,3.677,0.0,6,2,10.568,43.8,0,2.5242,1.298,0,0.981,2.478,6,0,0,0,1.122,2.125,4.992,4,0,2,0,0.0,2,0,0,0.0,0,3.822,0,4,0,0
 431,0.697,9.469,2,1,2.299,3,6,4.117,11.732,6,0,10.609,46.4,1,2.209,1.318,0,1.033,4.266,5,3,0,0,1.111,2.544,4.85,2,0,5,2,-0.374,2,0,0,0.0,0,4.051,0,4,0,0
 432,1.461,8.2,2,1,2.175,0,3,3.232,10.28,3,0,9.665,38.9,0,2.9033,1.231,0,1.01,2.298,1,0,0,0,1.136,2.683,4.593,3,0,1,1,-0.536,1,0,0,0.015,0,3.601,0,2,0,0
 433,0.0,8.83,0,1,2.469,0,0,3.556,0.0,0,0,10.384,57.1,0,2.7382,1.356,0,0.993,1.305,4,0,0,0,1.089,2.013,5.014,0,0,0,4,0.0,6,0,0,-0.001,0,4.066,0,0,0,0
 434,2.585,7.937,0,0,1.942,0,0,3.303,0.0,0,1,9.11,40.0,0,3.2848,1.304,0,0.965,4.891,0,0,0,0,1.125,1.958,3.932,0,0,0,0,0.0,0,0,0,-0.007,0,3.244,0,0,0,0
 435,0.918,8.225,0,0,1.414,2,0,2.771,0.0,0,1,6.594,20.0,0,1.9808,1.306,0,1.083,1.333,0,2,0,0,1.144,3.241,3.0,0,0,0,0,0.0,0,0,0,0.87,0,3.813,0,0,0,0
 436,0.918,11.578,0,0,1.414,2,0,3.572,0.0,0,1,6.594,20.0,0,1.9184,1.439,0,1.064,1.333,0,2,0,0,1.123,2.787,3.0,0,0,0,0,0.0,0,0,0,0.803,0,6.87,1,0,0,0
 437,1.522,12.253,0,0,1.732,2,0,4.081,0.0,0,2,7.853,27.3,0,2.2995,1.43,0,0.999,2.094,0,2,0,0,1.122,2.0,3.618,0,0,0,0,0.0,0,0,0,0.319,0,6.873,1,0,0,0
 438,1.585,8.315,0,0,1.802,2,0,3.09,0.0,0,2,8.16,28.6,1,2.4553,1.258,0,1.005,2.488,0,2,0,0,1.14,2.37,3.732,0,0,0,0,0.0,0,0,0,-0.211,0,3.578,0,0,0,0
 439,1.585,11.564,0,0,1.802,1,0,3.605,0.0,0,2,8.16,29.4,0,2.3783,1.297,1,0.972,2.488,0,1,0,0,1.137,1.792,3.732,0,0,0,0,0.0,0,0,0,-0.187,0,6.866,1,0,0,0
 440,2.585,12.258,0,0,1.942,2,0,4.294,0.0,0,2,9.11,31.3,0,2.7496,1.306,1,0.974,4.891,0,2,0,0,1.133,1.708,3.932,0,0,0,0,0.0,0,0,0,-0.006,0,6.867,1,0,0,0
 441,1.392,12.947,0,0,2.236,4,0,4.758,0.0,0,4,10.053,29.4,0,4.0011,1.461,0,1.013,1.164,0,4,0,0,1.109,2.028,5.303,0,0,0,0,0.0,0,0,1,0.038,0,6.89,1,0,0,0
 442,0.811,9.233,0,0,2.303,6,0,3.647,0.0,0,2,10.505,25.0,0,4.7601,1.216,0,1.246,1.411,0,4,0,0,1.213,4.368,5.646,0,0,0,0,0.0,0,0,2,-0.094,0,4.281,0,0,0,2
 443,0.918,9.146,0,0,2.0,4,0,3.486,0.0,0,0,9.184,33.3,0,4.3417,1.384,0,1.177,1.521,0,4,0,0,1.101,3.296,4.562,0,0,0,0,-0.198,0,0,0,-0.257,0,4.265,0,0,0,0
 444,1.371,9.591,0,0,2.214,6,0,3.939,0.0,0,0,9.956,40.0,1,5.2014,1.396,0,1.159,2.232,0,6,0,0,1.091,3.133,4.947,0,0,0,0,-0.481,0,0,0,-0.028,0,4.288,0,0,0,0
 445,1.761,7.587,0,1,2.175,0,0,3.061,0.0,0,5,10.106,30.0,0,3.5144,1.2,0,0.972,2.729,0,0,0,0,1.145,2.108,5.13,1,0,0,1,0.0,0,0,1,-0.021,0,3.292,0,0,0,0
 446,1.823,7.569,0,2,2.255,0,0,3.168,0.0,0,4,10.13,29.0,0,3.9327,1.137,0,0.984,2.301,0,0,0,0,1.147,2.386,5.311,2,0,0,6,0.0,0,0,1,0.012,0,3.316,0,0,0,0
 447,1.406,7.385,0,3,2.189,0,0,2.906,0.0,0,4,9.967,25.0,0,3.8422,1.063,0,1.014,1.309,0,0,0,0,1.156,3.219,5.236,3,0,0,9,0.0,0,0,1,-0.08,0,3.306,0,0,0,0
 448,1.392,7.491,0,4,2.236,0,0,3.037,0.0,0,4,10.053,23.8,0,4.1328,1.044,0,1.029,1.164,0,0,0,0,1.159,3.472,5.303,4,0,0,12,0.0,0,0,1,0.047,0,3.331,0,0,0,0
 449,1.617,8.943,0,1,2.605,12,0,4.01,0.0,0,2,11.591,29.2,0,6.591,0.908,0,1.231,2.885,0,0,0,0,1.317,5.554,6.177,1,0,0,1,0.0,0,0,5,0.0,0,3.896,0,0,0,0
 450,1.906,7.228,1,2,2.0,0,0,2.882,0.0,0,2,9.059,23.8,0,3.2686,1.1,0,1.003,2.524,0,0,0,0,1.162,2.75,4.362,2,0,0,0,0.0,0,0,0,-0.079,0,3.13,0,2,0,0
 451,2.3,7.732,0,2,2.011,0,0,3.192,10.622,0,1,9.338,31.0,0,3.0603,1.167,0,0.986,4.098,0,0,0,0,1.143,2.288,4.347,0,0,0,3,-0.082,0,0,0,0.013,0,3.357,0,0,0,0
 452,2.231,7.58,0,1,2.074,0,0,3.169,0.0,0,2,9.373,32.3,0,3.5147,1.193,0,0.973,3.015,0,0,0,0,1.141,1.939,4.471,0,0,0,2,0.0,0,0,0,0.012,0,3.178,0,0,0,0
 453,0.0,8.242,0,4,2.24,0,0,3.474,0.0,0,0,9.8,31.3,0,1.4085,1.099,0,1.008,5.475,0,0,0,0,1.143,2.048,4.243,0,0,0,4,0.0,2,0,0,-0.001,0,3.347,0,0,0,0
 454,2.322,8.497,0,2,1.919,2,0,3.437,0.0,0,2,8.881,27.3,0,3.1373,1.168,0,1.022,4.086,0,2,0,0,1.146,2.422,3.902,0,0,0,0,0.0,0,0,0,-0.026,0,3.553,0,0,0,0
 455,3.459,8.864,0,0,1.981,0,0,3.955,0.0,0,2,9.814,31.3,0,2.974,1.254,0,0.964,8.931,0,2,0,0,1.134,1.576,3.98,0,0,0,0,0.0,0,0,0,0.0,0,4.047,0,0,0,0
 456,1.436,7.817,0,2,2.194,0,0,3.027,10.538,0,3,10.091,30.4,0,3.9762,1.177,0,0.993,2.176,0,0,0,0,1.145,2.546,5.197,0,0,0,2,0.168,0,0,1,0.044,0,3.434,0,0,0,0
 457,0.971,7.151,1,1,1.848,0,0,2.488,9.431,0,0,8.597,25.0,0,3.2655,1.161,0,1.007,1.542,0,0,0,0,1.163,3.0,4.17,0,0,0,2,0.0,0,0,0,0.397,0,3.232,0,0,0,0
 458,2.273,8.991,0,6,2.328,0,0,4.052,34.898,0,4,10.952,36.0,0,5.7899,1.204,0,1.009,3.178,0,0,0,0,1.133,2.74,5.334,0,0,0,24,-0.95,0,0,1,0.0,0,3.593,0,0,0,0
 459,3.128,8.07,1,1,1.991,0,1,3.64,10.523,1,1,9.766,31.4,0,2.9329,1.192,0,0.972,7.244,0,0,0,0,1.144,1.981,4.236,2,0,0,1,-0.155,0,0,0,0.0,0,3.309,0,1,0,0
 460,3.711,8.645,0,3,2.31,0,0,4.016,22.241,0,1,10.425,34.9,0,1.7824,1.212,0,0.98,9.474,0,0,0,1,1.135,2.087,4.724,0,0,0,6,-0.779,1,0,0,0.0,0,3.637,0,0,0,0
 461,2.396,8.803,0,6,2.315,0,0,3.932,33.525,0,1,10.694,36.6,0,5.554,1.184,0,1.02,2.891,0,0,0,0,1.132,2.893,5.332,0,0,0,18,-1.839,0,0,1,0.0,0,3.527,0,0,0,0
 462,2.396,8.813,0,7,2.315,0,0,3.942,33.28,0,1,10.694,35.9,0,5.581,1.169,0,1.032,2.891,0,0,0,0,1.133,3.083,5.332,1,0,0,21,-2.172,0,0,1,0.0,0,3.529,0,0,0,0
 463,1.371,8.085,0,2,2.205,0,0,3.159,10.837,0,4,10.236,33.3,0,4.4958,1.22,0,0.993,2.499,0,0,0,0,1.139,2.608,5.145,0,0,0,5,0.113,0,0,1,-0.025,0,3.578,0,0,0,0
 464,1.379,8.259,0,2,2.0,1,0,3.059,9.797,0,2,9.222,28.6,1,3.81,1.195,0,1.037,2.133,0,1,0,0,1.145,3.087,4.414,0,0,0,1,-0.741,0,0,0,0.149,0,3.822,0,0,0,0
 465,0.863,9.0,0,2,2.175,3,0,3.438,9.625,0,1,10.026,25.0,0,4.373,1.244,0,1.174,1.435,0,3,0,0,1.135,4.036,5.262,1,0,0,0,-1.461,0,0,1,0.161,0,4.263,0,0,0,1
 466,1.975,8.234,0,4,2.288,0,0,3.468,11.395,0,6,10.725,29.4,0,4.5704,1.132,0,1.004,3.488,0,0,0,0,1.147,2.798,5.35,2,0,0,16,-0.443,0,0,2,-0.002,0,3.56,0,0,0,0
 467,4.189,9.972,0,8,2.338,0,0,5.191,53.149,0,4,11.504,32.3,0,5.7766,1.218,0,0.979,7.261,0,4,0,0,1.135,1.938,5.342,0,0,0,24,-1.429,0,0,1,0.0,0,3.663,0,0,0,0
 468,1.686,8.163,0,3,2.244,0,0,3.262,21.759,0,3,10.308,32.0,0,4.2076,1.185,0,1.007,2.733,0,0,0,0,1.141,2.871,5.291,0,0,0,7,-0.561,0,0,1,0.014,0,3.567,0,0,0,0
 469,0.811,8.637,0,1,1.732,0,0,2.615,9.556,0,0,8.318,20.0,0,3.0897,1.288,0,1.005,1.0,0,1,0,0,1.138,3.056,4.0,0,0,0,0,0.0,0,0,0,-0.557,0,4.218,0,0,0,0
 470,1.792,8.131,0,4,2.165,0,0,3.329,10.731,0,5,10.281,28.6,0,4.6435,1.135,0,1.014,3.506,0,0,0,0,1.149,2.646,5.103,0,0,0,5,-0.806,0,0,1,-0.008,0,3.496,0,0,0,0
 471,1.5,8.427,3,0,2.0,0,1,3.126,0.0,2,2,9.309,23.5,0,4.0038,1.25,0,1.002,2.682,0,1,0,0,1.157,2.563,4.343,3,0,0,0,1.101,0,1,0,-0.083,0,3.859,0,4,0,0
 472,1.379,8.139,4,2,2.0,0,0,2.946,18.567,0,0,9.222,9.1,0,4.3883,1.074,0,1.097,2.133,0,0,0,0,1.219,4.167,4.414,4,0,0,2,-0.662,0,1,0,0.171,0,3.689,0,1,0,0
 473,0.971,8.452,1,0,1.848,0,0,2.959,0.0,0,0,8.597,20.0,0,3.1822,1.408,0,1.002,1.542,0,2,0,0,1.117,2.611,4.17,1,0,0,0,0.532,0,0,0,0.387,0,4.016,0,0,0,0
 474,2.217,9.522,0,4,2.25,3,0,3.907,11.647,0,3,10.2,23.1,0,4.7497,1.207,0,1.051,2.369,0,4,0,0,1.143,2.831,5.262,0,0,0,9,0.0,0,0,0,-0.002,0,4.416,0,0,0,0
 475,2.187,9.752,0,6,2.314,0,0,4.028,23.28,0,2,10.651,26.3,0,5.2824,1.244,0,1.024,2.965,0,3,0,0,1.131,2.709,5.284,0,0,0,10,-1.009,0,0,0,0.0,0,4.823,0,0,0,0
 476,2.797,9.217,0,4,2.242,0,0,3.904,11.913,0,4,10.588,28.6,0,4.4911,1.181,0,0.986,5.313,0,1,0,0,1.143,2.213,5.192,1,0,0,10,0.0,0,0,0,0.0,0,4.433,0,0,0,0
 477,0.811,8.986,0,1,2.303,3,0,3.465,0.0,0,3,10.505,26.7,1,4.4339,1.264,0,1.048,1.411,0,3,0,0,1.141,3.104,5.646,1,0,0,0,0.0,0,0,2,-0.08,0,4.26,0,0,0,1
 478,2.388,9.047,3,3,2.284,0,0,3.885,0.0,6,6,10.649,27.7,0,5.6107,1.235,0,0.993,3.036,0,1,0,0,1.145,2.185,5.27,0,0,0,6,2.593,0,0,0,0.0,0,4.075,0,6,0,0
 479,1.95,8.583,1,3,2.292,0,0,3.511,0.0,1,4,10.236,24.3,0,4.3397,1.225,0,0.989,2.105,0,1,0,0,1.146,2.157,5.331,2,0,0,9,0.0,0,0,0,-0.002,0,4.023,0,1,0,0
 480,1.392,12.258,0,2,2.236,2,0,4.229,0.0,0,4,10.053,26.3,0,4.066,1.25,0,1.022,1.164,0,2,0,0,1.136,2.75,5.303,2,0,0,6,0.0,0,0,1,0.043,0,6.874,1,0,0,0
 481,1.891,7.315,1,2,2.053,0,0,2.988,0.0,0,3,9.202,25.0,0,3.5378,1.101,0,0.998,2.244,0,0,0,0,1.159,2.611,4.461,2,0,0,0,0.0,0,0,0,0.044,0,3.155,0,3,0,0
 482,1.5,7.433,0,2,2.112,0,0,2.876,0.0,0,4,9.872,27.3,0,3.6085,1.122,0,0.993,2.472,0,0,0,0,1.151,2.469,5.098,1,0,0,0,0.0,0,0,1,-0.077,0,3.304,0,0,0,0
 483,1.371,7.704,0,2,2.288,0,0,3.094,0.0,0,5,10.315,28.6,0,4.1685,1.138,0,0.986,1.985,0,0,0,0,1.148,2.542,5.384,2,0,0,8,0.0,0,0,1,-0.023,0,3.426,0,0,0,0
 484,1.436,7.893,0,3,2.136,0,0,3.054,10.143,0,4,10.05,28.6,0,4.3332,1.138,0,1.014,2.695,0,0,0,0,1.149,2.769,5.102,0,0,0,4,-0.426,0,0,1,0.047,0,3.446,0,0,0,0
 485,3.066,14.009,0,2,2.328,0,0,4.697,12.585,0,4,10.673,31.2,0,4.2358,1.294,0,0.969,6.801,0,1,0,0,1.136,1.818,5.351,0,0,0,5,0.15,0,0,0,0.0,0,10.323,0,0,0,0
 486,2.1,8.883,3,3,2.267,0,2,3.766,0.0,11,0,10.646,24.4,0,4.467,1.239,0,0.993,4.692,0,1,0,0,1.152,2.131,5.311,0,0,0,9,0.953,0,0,0,0.0,0,4.029,0,1,0,0
 487,1.455,8.128,0,0,2.315,0,0,3.245,0.0,0,3,10.315,40.7,0,2.9284,1.279,0,0.966,1.897,1,0,0,0,1.123,1.856,5.365,0,0,0,0,0.0,1,0,1,-0.007,0,3.641,0,0,0,0
 488,1.185,8.671,0,2,2.267,1,0,3.413,10.337,0,0,9.911,46.7,1,3.303,1.268,0,1.042,1.563,2,1,0,0,1.107,3.011,4.923,1,0,1,4,-0.995,1,0,0,0.015,0,3.933,0,0,0,0
 489,1.936,8.783,2,0,2.283,0,4,3.937,0.0,7,2,10.509,40.0,0,1.8876,1.269,0,0.974,5.249,3,0,0,0,1.128,1.856,4.745,2,0,3,0,0.0,2,0,0,0.0,0,3.689,0,8,1,0
 490,0.875,7.959,1,0,2.194,0,1,2.984,0.0,3,1,9.579,41.2,0,3.1875,1.287,0,0.979,0.854,2,0,0,0,1.127,2.167,4.732,2,0,1,0,0.0,1,0,0,0.043,0,3.648,0,2,0,0
 491,0.875,7.954,1,0,2.17,0,1,2.984,0.0,2,1,9.54,41.2,0,3.0804,1.282,0,0.979,1.14,2,0,0,0,1.127,2.167,4.562,2,0,1,0,0.0,1,0,0,0.043,0,3.627,0,2,0,0
 492,1.876,8.55,1,2,2.263,0,2,3.547,21.912,4,2,10.186,40.7,0,2.8214,1.261,0,1.002,3.249,2,0,0,0,1.126,2.619,4.835,1,0,1,3,-0.386,1,0,0,0.001,0,3.681,0,3,0,0
 493,1.662,9.03,1,1,2.283,2,1,3.715,10.99,3,1,10.166,40.9,1,3.0136,1.285,0,1.022,2.652,3,2,0,0,1.121,2.607,4.843,1,0,3,2,-0.043,1,0,0,-0.002,0,4.05,0,3,0,0
 494,1.831,8.63,1,2,2.297,0,2,3.607,22.051,4,3,10.332,40.0,0,2.8874,1.264,0,0.998,3.288,3,0,0,0,1.127,2.556,4.883,1,0,1,3,-0.383,1,0,0,-0.001,0,3.726,0,3,0,0
 495,1.887,8.005,2,0,2.157,0,3,3.253,0.0,2,1,9.535,36.0,0,2.3963,1.231,0,0.98,3.141,1,0,0,0,1.14,2.061,4.522,3,0,0,0,0.0,1,0,0,-0.007,0,3.555,0,3,0,0
 496,1.23,8.92,3,4,2.338,0,3,3.583,41.057,6,0,10.309,33.3,0,3.7647,1.194,0,1.083,1.873,3,0,2,0,1.153,3.615,5.006,2,0,3,8,0.0,1,0,0,-0.003,0,3.938,0,6,0,0
 497,1.708,9.257,3,4,2.479,3,9,4.091,44.711,8,3,11.059,33.3,0,4.1216,1.142,0,1.057,2.168,4,0,2,0,1.171,3.475,5.386,0,0,3,8,0.0,1,0,1,0.0,0,4.004,0,8,0,1
 498,1.187,8.405,1,2,2.194,0,1,3.193,20.013,2,0,9.642,42.9,0,3.3706,1.241,0,1.037,1.659,1,0,1,0,1.125,3.074,4.732,0,0,1,4,0.0,1,0,0,-0.027,0,3.813,0,2,0,0
 499,1.16,9.12,1,2,2.318,2,1,3.647,20.473,2,0,10.122,42.9,1,3.701,1.297,0,1.084,1.572,3,2,1,0,1.117,3.202,5.029,0,0,3,4,0.0,1,0,0,-0.008,0,4.106,0,2,0,0
 500,1.16,9.118,1,2,2.305,2,1,3.647,20.473,2,0,10.099,42.9,1,3.6476,1.295,0,1.084,1.553,3,2,1,0,1.117,3.202,4.965,0,0,3,4,0.0,1,0,0,-0.008,0,4.054,0,2,0,0
 501,0.0,8.488,0,1,2.236,0,0,3.495,0.0,0,0,9.971,52.2,0,2.4203,1.306,0,0.989,2.829,2,0,0,0,1.099,2.064,4.675,0,0,2,4,0.0,2,0,0,0.001,0,3.664,0,0,0,0
 502,0.875,7.986,1,1,2.17,0,1,3.011,0.0,2,0,9.54,40.0,0,3.17,1.226,0,1.005,1.14,2,0,0,0,1.13,2.667,4.562,3,0,2,2,0.0,1,0,0,0.046,0,3.639,0,2,0,0
 503,1.604,8.395,1,2,2.242,0,1,3.459,10.681,2,2,10.007,38.5,0,2.9071,1.229,0,1.002,2.731,2,0,0,0,1.131,2.423,4.687,1,0,2,3,-0.066,1,0,0,-0.002,0,3.666,0,3,0,0
 504,1.185,8.516,1,3,2.236,0,1,3.299,20.072,2,0,9.882,40.0,0,3.3837,1.212,0,1.057,1.74,2,0,1,0,1.13,3.333,4.77,1,0,2,6,0.0,1,0,0,0.015,0,3.834,0,2,0,0
 505,1.225,9.217,3,7,2.411,0,3,3.817,62.168,6,0,10.607,31.6,0,4.1935,1.167,0,1.137,1.526,4,0,3,0,1.156,4.042,5.163,1,0,4,14,0.0,1,0,0,0.0,0,4.018,0,6,0,0
 506,0.881,8.87,0,1,2.246,2,0,3.462,0.0,0,0,9.833,46.2,1,3.3877,1.321,0,1.048,1.06,3,2,0,0,1.103,2.802,4.807,1,0,3,2,0.0,1,0,0,-0.026,0,3.999,0,0,0,0
 507,1.886,9.042,1,4,2.366,1,3,3.891,22.352,3,1,10.548,37.5,1,3.2862,1.23,0,1.029,3.188,4,1,0,0,1.131,2.728,5.019,1,0,4,7,-0.627,1,0,0,0.0,0,3.96,0,3,0,0
 508,0.832,9.376,0,1,2.365,4,0,3.825,0.0,0,0,10.265,46.2,1,3.7467,1.344,0,1.098,0.952,5,4,0,0,1.095,2.98,5.119,1,0,5,2,0.0,1,0,0,-0.008,0,4.216,0,0,0,0
 509,2.929,9.725,0,2,2.438,5,0,4.387,11.973,0,1,10.814,37.5,1,2.4916,1.281,0,1.013,6.971,6,5,0,0,1.124,2.389,5.26,0,0,6,5,-0.416,1,0,0,0.0,0,4.295,0,0,0,0
 510,1.187,8.565,0,1,2.222,1,0,3.319,10.143,0,0,9.668,50.0,1,3.2512,1.321,0,1.022,1.358,2,1,0,0,1.1,2.716,4.783,0,0,1,2,0.0,1,0,0,-0.026,0,3.911,0,0,0,0
 511,1.705,8.295,0,1,2.166,0,0,3.315,10.53,0,1,9.722,47.6,0,2.7404,1.296,0,0.988,2.905,1,0,0,0,1.109,2.394,4.543,0,0,0,1,0.078,1,0,0,-0.008,0,3.611,0,0,0,0
 512,3.61,9.08,0,4,2.351,0,0,4.429,25.194,0,2,10.833,35.4,0,2.2317,1.212,0,0.978,10.844,2,0,0,0,1.134,1.991,5.072,0,2,0,12,-0.862,1,0,0,0.0,0,3.794,0,0,0,0
 513,1.23,8.485,0,2,2.334,0,0,3.461,10.562,0,3,10.548,40.7,0,3.0581,1.243,0,0.994,2.215,2,0,0,0,1.123,2.558,5.315,1,0,0,4,-0.875,1,0,1,-0.002,0,3.743,0,0,0,0
 514,1.876,8.491,0,3,2.248,0,0,3.533,11.344,0,3,10.447,39.3,0,2.9658,1.217,0,1.006,3.439,1,0,0,0,1.126,2.47,5.107,0,0,0,8,-0.472,1,0,1,0.001,0,3.678,0,0,0,0
 515,1.258,8.704,1,4,2.288,0,2,3.483,30.73,2,0,10.136,41.2,0,3.4294,1.199,0,1.069,2.011,2,0,1,0,1.127,3.5,4.882,1,0,1,8,-1.168,1,0,0,0.005,0,3.857,0,2,0,0
 516,3.682,9.163,0,3,2.466,0,0,4.423,12.336,0,7,11.345,35.0,0,2.1976,1.225,0,0.974,11.779,4,0,0,0,1.135,1.943,5.489,1,0,1,8,-0.117,1,0,2,0.0,0,3.854,0,0,0,0
 517,1.261,8.437,2,0,2.247,0,6,3.292,0.0,4,0,9.749,57.1,0,3.3085,1.35,0,1.006,1.436,2,0,0,0,1.101,2.833,4.828,0,0,0,0,0.0,1,0,0,0.015,0,3.761,0,2,0,0
 518,1.426,8.913,2,3,2.328,0,4,3.986,12.142,6,2,10.632,40.5,0,2.2884,1.232,0,1.003,4.181,3,0,0,0,1.128,2.462,4.914,3,0,2,3,-0.173,2,0,0,0.0,0,3.733,0,7,0,0
 519,0.0,7.439,0,0,2.0,0,0,3.22,0.0,0,0,9.314,33.3,0,2.0,1.205,0,0.961,1.244,0,0,0,0,1.138,1.5,4.0,0,0,0,0,0.0,1,0,0,0.003,0,3.009,0,0,0,0
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 536,0.0,9.301,2,0,2.384,0,5,3.892,0.0,4,0,10.46,39.4,0,1.7802,1.339,0,0.986,3.735,2,2,0,0,1.113,1.824,4.802,1,0,0,0,0.0,4,0,0,0.0,0,4.341,0,5,0,0
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 539,0.881,8.76,2,0,2.246,0,0,3.352,0.0,4,0,9.833,26.3,0,2.7734,1.334,0,0.994,1.06,0,2,0,0,1.131,2.019,4.807,0,0,0,0,1.008,1,0,0,-0.023,0,4.094,0,0,0,0
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 541,0.964,10.274,6,8,2.399,4,16,5.032,50.918,20,2,11.786,41.9,1,1.6237,1.265,0,1.032,9.592,14,4,0,0,1.124,2.595,5.051,2,0,12,14,-2.695,4,2,0,0.0,0,4.016,0,18,0,0
 542,0.0,7.6,0,1,2.0,0,0,2.593,0.0,0,0,8.412,44.4,0,3.4245,1.332,0,1.011,0.579,0,0,0,0,1.116,2.3,3.618,0,0,0,0,0.0,1,0,0,-0.237,0,3.526,0,0,0,0
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 551,1.273,8.521,1,2,2.288,0,2,3.351,20.772,3,1,9.975,40.0,0,3.4085,1.241,0,1.015,1.602,2,0,1,0,1.129,2.803,4.953,0,0,1,4,0.0,1,0,0,-0.008,0,3.853,0,2,0,0
 552,0.72,10.237,0,0,2.532,10,0,4.608,0.0,0,0,11.151,54.5,1,3.1768,1.413,0,1.121,2.359,12,10,0,0,1.069,2.778,5.418,0,0,10,0,0.0,2,0,0,0.0,0,4.361,0,0,0,0
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 557,2.753,8.003,0,4,1.985,0,0,3.449,10.348,0,2,9.528,29.4,0,3.3944,1.137,0,1.004,5.588,0,0,0,0,1.147,2.405,4.236,0,0,0,2,-0.271,0,0,0,-0.002,0,3.351,0,0,0,0
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 559,0.722,9.303,0,3,2.0,0,0,2.872,18.375,0,0,9.657,11.1,0,5.0476,1.125,0,1.092,0.8,0,1,0,0,1.153,4.583,5.0,1,0,0,0,0.0,0,0,0,0.446,0,4.712,0,0,0,0
 560,2.468,7.95,0,2,2.119,0,0,3.418,11.115,0,3,9.786,31.6,0,3.8301,1.179,0,0.98,3.889,0,0,0,0,1.142,2.143,4.525,0,0,0,5,-0.039,0,0,0,-0.002,0,3.379,0,0,0,0
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 563,0.629,8.427,0,2,2.333,0,0,3.364,10.717,0,0,10.06,52.9,0,2.7414,1.279,0,1.018,1.207,2,0,0,0,1.098,2.5,4.91,0,0,1,5,-0.302,3,0,0,0.004,0,3.767,0,0,0,0
 564,1.522,6.333,0,0,1.732,0,0,2.333,0.0,0,2,7.853,29.4,0,2.1906,1.178,0,0.959,2.094,0,0,0,0,1.147,1.7,3.618,0,0,0,0,0.0,0,0,0,0.294,0,2.794,0,0,0,0
 565,1.459,6.77,0,0,1.902,0,0,2.523,0.0,0,3,8.755,30.0,0,2.6272,1.213,0,0.959,2.052,0,0,0,0,1.145,1.722,4.214,0,0,0,0,0.0,0,0,0,-0.181,0,2.998,0,0,0,0
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 567,2.281,7.029,0,0,1.902,0,0,2.908,0.0,0,2,8.743,31.0,0,2.5951,1.202,0,0.96,3.685,0,0,0,0,1.143,1.611,3.879,0,0,0,0,0.0,0,0,0,0.036,0,2.924,0,0,0,0
 568,2.777,8.127,0,0,1.95,1,0,3.44,0.0,0,2,9.207,31.6,1,2.7719,1.22,0,0.969,5.294,0,1,0,0,1.141,1.739,3.942,0,0,0,0,0.0,0,0,0,0.003,0,3.542,0,0,0,0
 569,3.146,11.578,0,0,1.97,1,0,4.075,0.0,0,2,9.522,32.0,0,2.852,1.243,1,0.965,6.909,0,1,0,0,1.138,1.603,3.966,0,0,0,0,0.0,0,0,0,0.0,0,6.866,1,0,0,0
 570,1.585,6.599,1,0,1.802,0,1,2.532,0.0,1,2,8.16,26.3,0,2.3761,1.152,0,0.969,2.488,0,0,0,0,1.157,2.0,3.732,2,0,0,0,0.0,0,0,0,-0.195,0,2.858,0,1,0,0
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 573,1.585,6.649,0,1,1.802,0,0,2.555,0.0,0,2,8.16,27.8,0,2.4062,1.134,0,0.979,2.488,0,0,0,0,1.15,2.333,3.732,1,0,0,1,0.0,0,0,0,-0.205,0,2.874,0,0,0,0
 574,1.0,7.174,0,1,2.17,0,0,2.273,0.0,0,1,8.482,30.0,0,2.3699,1.09,0,0.998,1.0,0,0,0,0,1.146,2.083,4.0,0,0,0,0,0.0,1,0,0,0.34,0,3.302,0,0,0,0
 575,1.0,6.32,0,2,1.618,0,0,2.243,0.0,0,2,7.408,20.0,0,2.2525,0.98,0,1.031,1.707,0,0,0,0,1.166,3.75,3.414,2,0,0,0,0.0,0,0,0,-0.642,0,2.817,0,0,0,0
 576,0.971,6.782,0,2,1.848,0,0,2.449,0.0,0,2,8.597,23.1,0,2.8042,1.044,0,1.015,1.542,0,0,0,0,1.16,3.367,4.17,2,0,0,1,0.0,0,0,0,0.391,0,3.047,0,0,0,0
 577,1.459,6.914,0,2,1.932,0,0,2.608,0.0,0,2,8.815,25.0,0,2.9558,1.056,0,1.005,1.745,0,0,0,0,1.156,3.056,4.303,2,0,0,2,0.0,0,0,0,-0.229,0,3.083,0,0,0,0
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 580,2.0,7.074,0,2,1.879,0,0,2.858,0.0,0,2,8.584,27.3,0,2.8521,1.117,0,0.993,3.284,0,0,0,0,1.151,2.375,3.848,1,0,0,1,0.0,0,0,0,-0.076,0,2.997,0,0,0,0
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 650,0.971,6.635,1,0,1.848,0,0,2.373,0.0,2,3,8.597,25.0,0,2.607,1.133,0,0.97,1.542,0,0,0,0,1.161,2.167,4.17,2,0,0,0,0.0,0,0,0,0.322,0,2.983,0,1,0,0
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 653,0.918,5.86,0,1,1.414,0,0,1.926,0.0,0,2,6.594,22.2,0,1.8205,1.06,0,0.998,1.333,0,0,0,0,1.162,3.167,3.0,1,0,0,0,0.0,0,0,0,0.826,0,2.651,0,0,0,0
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 655,1.891,7.197,0,1,2.042,0,0,2.946,0.0,0,3,9.202,29.6,0,3.1402,1.16,0,0.973,2.602,0,0,0,0,1.146,2.093,4.444,1,0,0,2,0.0,0,0,0,0.038,0,3.096,0,0,0,0
 656,2.281,7.087,0,1,1.902,0,0,2.938,0.0,0,2,8.743,29.6,0,2.6274,1.161,0,0.973,3.685,0,0,0,0,1.146,2.056,3.879,1,0,0,1,0.0,0,0,0,0.039,0,2.936,0,0,0,0
 657,2.807,7.552,0,1,1.956,0,0,3.364,0.0,0,2,9.296,31.0,0,2.7989,1.18,0,0.969,5.698,0,0,0,0,1.143,1.857,3.95,1,0,0,1,0.0,0,0,0,-0.002,0,2.976,0,0,0,0
 658,1.735,9.921,0,4,2.358,0,0,3.838,0.0,0,8,10.648,26.7,0,3.7046,1.532,0,0.979,1.69,0,1,0,0,1.139,2.108,5.391,0,0,0,12,0.0,0,0,0,0.0,0,5.127,0,0,0,0
 659,1.585,6.732,0,2,1.802,0,0,2.597,0.0,0,2,8.16,25.0,0,2.477,1.069,0,1.005,2.488,0,0,0,0,1.156,3.0,3.732,2,0,0,2,0.0,0,0,0,-0.229,0,2.897,0,0,0,0
 660,3.301,7.984,0,1,1.975,0,0,3.68,0.0,0,2,9.649,32.7,0,3.0163,1.202,0,0.968,7.718,0,0,0,0,1.14,1.816,3.973,1,0,0,1,0.0,0,0,0,0.0,0,3.129,0,0,0,0
 661,1.0,6.631,0,1,1.618,0,0,2.263,0.0,0,1,7.408,30.0,0,2.4719,1.141,0,0.998,1.707,0,0,0,0,1.146,3.125,3.414,1,0,0,1,0.0,0,0,0,-0.611,0,2.974,0,0,0,0
 662,1.0,6.251,1,1,1.618,0,0,2.211,0.0,0,2,7.408,18.2,0,2.1848,0.999,0,1.007,1.707,0,0,0,0,1.178,3.25,3.414,3,0,0,0,0.0,0,0,0,-0.603,0,2.79,0,1,0,0
 663,1.557,7.098,0,2,1.97,0,0,2.746,0.0,0,2,8.944,26.3,0,3.1387,1.099,0,0.998,2.195,0,0,0,0,1.153,2.548,4.334,1,0,0,2,0.0,0,0,0,0.135,0,3.114,0,0,0,0
 664,0.918,6.578,0,1,1.414,0,0,2.03,8.806,0,1,6.594,28.6,0,2.311,1.177,0,1.014,1.333,0,0,0,0,1.149,3.667,3.0,0,0,0,0,0.0,0,0,0,0.903,0,2.991,0,0,0,0
 665,0.971,7.056,0,1,1.848,0,0,2.466,9.505,0,2,8.597,30.8,0,2.8963,1.196,0,0.989,1.542,0,0,0,0,1.144,2.867,4.17,0,0,0,2,0.0,0,0,0,0.363,0,3.18,0,0,0,0
 666,1.379,7.473,0,1,2.0,0,0,2.768,10.254,0,3,9.222,31.6,0,3.1682,1.224,0,0.98,2.133,0,0,0,0,1.142,2.5,4.414,0,0,0,1,0.287,0,0,0,0.126,0,3.325,0,0,0,0
 667,1.379,7.758,0,2,2.0,0,0,2.847,20.067,0,2,9.222,33.3,0,3.4137,1.209,0,1.013,2.133,0,0,0,0,1.139,3.262,4.414,0,0,0,2,-0.125,0,0,0,0.144,0,3.426,0,0,0,0
 668,3.284,8.337,0,2,1.993,0,0,3.78,10.319,0,1,9.867,34.6,0,3.1869,1.212,0,0.977,8.066,0,0,0,0,1.136,2.133,4.236,1,0,0,2,-0.671,0,0,0,0.0,0,3.33,0,0,0,0
 669,1.837,7.912,0,3,2.074,0,0,3.082,20.676,0,2,9.454,31.6,0,4.0241,1.121,0,1.021,2.57,0,0,0,0,1.142,3.093,4.523,0,0,0,6,-0.913,0,0,0,0.048,0,3.494,0,0,0,0
 670,3.664,8.622,0,4,2.105,0,0,4.103,23.157,0,2,10.32,32.4,0,3.5408,1.181,0,0.982,9.847,0,0,0,0,1.14,2.083,4.475,0,0,0,6,-0.855,0,0,0,0.0,0,3.474,0,0,0,0
 671,2.929,8.951,0,6,2.262,0,0,4.293,37.824,0,6,10.906,32.5,0,5.6969,1.178,0,0.989,4.685,0,0,0,0,1.14,2.268,4.836,0,0,0,17,-0.851,0,0,0,0.0,0,3.526,0,0,0,0
 672,1.5,7.628,0,2,2.042,0,0,2.917,10.191,0,3,9.345,30.0,0,3.7418,1.153,0,0.998,2.34,0,0,0,0,1.146,2.625,4.476,0,0,0,2,-0.195,0,0,0,-0.079,0,3.389,0,0,0,0
 673,1.975,7.677,0,3,1.962,0,0,3.039,10.129,0,2,9.118,28.6,0,3.3919,1.124,0,1.014,3.449,0,0,0,0,1.149,2.685,4.235,0,0,0,1,-0.255,0,0,0,0.048,0,3.35,0,0,0,0
 674,2.252,8.09,0,4,2.044,0,0,3.345,20.772,0,1,9.625,30.8,0,3.3996,1.138,0,1.019,4.178,0,0,0,0,1.144,3.028,4.38,1,0,0,5,-1.068,0,0,0,-0.008,0,3.379,0,0,0,0
 675,4.437,9.075,0,4,2.086,0,0,4.587,23.892,0,2,10.757,33.9,0,3.4435,1.208,0,0.974,17.114,0,0,0,0,1.137,1.899,4.412,0,0,0,8,-0.268,0,0,0,0.0,0,3.395,0,0,0,0
 676,2.522,8.169,0,4,2.0,0,0,3.477,20.288,0,0,9.716,31.3,0,3.0402,1.139,0,1.008,5.475,0,0,0,0,1.143,2.952,4.243,2,0,0,4,-1.48,0,0,0,-0.002,0,3.337,0,0,0,0
 677,2.948,8.317,0,4,2.0,0,0,3.699,20.53,0,0,9.917,31.8,0,3.0152,1.158,0,0.995,7.174,0,0,0,0,1.142,2.63,4.237,2,0,0,4,-1.396,0,0,0,0.0,0,3.335,0,0,0,0
 678,3.774,8.752,0,8,2.085,0,0,4.201,23.21,0,2,10.379,30.6,0,3.7308,1.146,0,1.002,10.723,0,0,0,0,1.144,2.311,4.412,0,0,0,8,-0.554,0,0,0,0.0,0,3.397,0,0,0,0
 679,2.187,8.051,0,4,2.101,0,0,3.272,21.21,0,2,9.59,30.4,0,3.9936,1.142,0,1.027,3.207,0,0,0,0,1.145,2.985,4.544,0,0,0,6,-1.072,0,0,0,0.015,0,3.486,0,0,0,0
 680,4.044,9.017,0,4,2.08,0,0,4.363,23.602,0,2,10.513,32.3,0,3.455,1.202,0,0.979,12.745,0,1,0,0,1.138,1.976,4.399,0,0,0,8,-0.228,0,0,0,0.0,0,3.645,0,0,0,0
 681,1.922,8.016,0,4,2.127,0,0,3.192,20.872,0,2,9.565,30.0,0,4.2802,1.13,0,1.036,2.691,0,0,0,0,1.146,3.133,4.706,0,0,0,2,-1.853,0,0,0,-0.028,0,3.586,0,0,0,0
 682,2.21,8.143,0,2,2.147,0,0,3.447,11.115,0,3,9.961,33.3,0,4.0218,1.203,0,0.983,3.769,0,0,0,0,1.139,2.262,4.67,0,0,0,7,0.218,0,0,0,-0.002,0,3.53,0,0,0,0
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 684,3.418,8.459,0,2,2.094,0,0,3.939,11.181,0,2,10.195,33.3,0,3.122,1.21,0,0.973,9.52,0,0,0,0,1.138,1.931,4.644,0,0,0,6,0.238,0,0,0,0.0,0,3.525,0,0,0,0
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 700,1.409,7.884,1,0,2.149,0,2,3.073,0.0,1,1,9.391,40.0,0,2.6422,1.266,0,0.976,2.036,1,0,0,0,1.129,2.074,4.517,2,0,0,0,0.0,1,0,0,-0.024,0,3.553,0,1,0,0
 701,0.802,7.811,0,1,2.101,0,0,2.884,0.0,0,0,9.183,46.2,0,3.135,1.264,0,0.998,0.975,1,0,0,0,1.112,2.524,4.414,1,0,1,2,0.0,1,0,0,-0.08,0,3.566,0,0,0,0
 702,0.875,8.008,0,2,2.194,0,0,3.025,0.0,0,0,9.579,42.9,0,3.3319,1.219,0,1.022,0.854,2,0,0,0,1.119,2.917,4.732,2,0,2,4,0.0,1,0,0,0.047,0,3.67,0,0,0,0
 703,1.187,8.058,0,2,2.194,0,0,3.118,0.0,0,0,9.631,41.2,0,3.1517,1.214,0,1.011,1.544,2,0,0,0,1.122,2.537,4.607,1,0,2,4,0.0,1,0,0,-0.026,0,3.649,0,0,0,0
 704,1.546,8.364,0,2,2.305,0,0,3.451,0.0,0,0,10.067,40.7,0,3.1976,1.248,0,0.994,2.0,3,0,0,0,1.123,2.192,4.898,0,0,2,4,0.0,1,0,0,-0.002,0,3.729,0,0,0,0
 705,0.861,9.154,0,1,2.307,3,0,3.66,0.0,0,0,10.06,46.2,1,3.567,1.334,0,1.073,0.962,4,3,0,0,1.099,2.9,4.97,1,0,4,2,0.0,1,0,0,0.015,0,4.106,0,0,0,0
 706,1.273,8.238,0,1,2.251,0,0,3.294,10.288,0,2,9.947,43.5,0,2.9304,1.28,0,0.984,1.951,2,0,0,0,1.117,2.333,4.782,0,0,0,2,0.0,1,0,0,-0.007,0,3.671,0,0,0,0
 707,1.528,8.362,0,3,2.29,0,0,3.404,10.337,0,1,10.009,40.9,0,3.2685,1.22,0,1.018,1.945,3,0,0,0,1.123,2.75,4.869,1,0,2,6,0.0,1,0,0,0.004,0,3.743,0,0,0,0
 708,0.75,9.007,0,6,2.532,0,0,3.788,44.736,0,0,10.813,55.6,0,2.4524,1.225,0,1.103,1.508,4,0,0,0,1.093,3.271,5.156,0,4,0,16,-3.296,6,0,0,0.0,0,3.986,0,0,0,0
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 710,1.563,9.005,0,4,2.355,0,0,4.037,24.332,0,1,10.658,44.2,0,2.2282,1.243,0,1.003,4.684,3,0,0,0,1.116,2.406,5.074,0,2,0,13,-1.025,2,0,0,0.0,0,3.798,0,0,0,0
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--- a/pycache/run.cpython-38.pyc
+++ b/pycache/run.cpython-38.pyc
--- a/cachedir/joblib/run/estimatorFeatureSelection/0237a2e70a1357c0d76691519bd22c74/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0237a2e70a1357c0d76691519bd22c74/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/05d9463b5e19dc233c8c347d61a0c1ef/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/05d9463b5e19dc233c8c347d61a0c1ef/metadata.json
@ -0,0 +1 @@
 {"duration": 14.059135913848877, "input_args": {"Data": "     F7  F10  F7+F10  |F7-F10|  F7xF10  F7/F10  F10/F7\n0     0    0       0         0       0     0.0     0.0\n1     6    6      12         0      36     1.0     1.0\n2     0    0       0         0       0     0.0     0.0\n3     0    0       0         0       0     0.0     0.0\n4     0    0       0         0       0     0.0     0.0\n..   ..  ...     ...       ...     ...     ...     ...\n832   0    0       0         0       0     0.0     0.0\n833   2    2       4         0       4     1.0     1.0\n834   0    0       0         0       0     0.0     0.0\n835   0    0       0         0       0     0.0     0.0\n836   0    0       0         0       0     0.0     0.0\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/06c8a11330f7f20823ddaebbd7b7dbe0/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/06c8a11330f7f20823ddaebbd7b7dbe0/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/08e88f1ed04ac3f4129750cdad1f165b/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/08e88f1ed04ac3f4129750cdad1f165b/metadata.json
@ -0,0 +1 @@
 {"duration": 37.06569814682007, "input_args": {"Data": "        F1     F2  F3  F4     F5_em1  F6  F7    F8_l1p      F9  F10  F11     F12   F13  F14     F15    F16  F17    F18     F19  F20  F21  F22  F23    F24    F25       F26_p4  F27  F28  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0   8.611882   3   0  1.535145   0.000    0    1   9.902  46.7    1  3.1934  1.359    0  1.034   1.476    3    3    0    0  1.100  2.483   541.987500    0    0    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0   7.971026   0   6  1.509839   0.000    6    0  10.054  35.1    0  1.8929  1.209    0  0.974   4.130    0    0    0    0  1.139  1.744   433.132851    0    0    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  10.290933   0   0  1.467644  21.884    0    0  10.226  42.1    0  2.3934  1.204    0  1.027   1.027    0    0    0    2  1.120  2.773   616.048483    0    0    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  13.731676  23   0  1.730770   9.855    0    1  12.353  31.6    0  7.7233  0.906    0  1.291   5.094    0    0    0    0  1.348  5.741  1591.360175    1    0    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  13.879732  27   0  1.756995   9.894    0    1  12.519  31.8    0  7.9184  0.906    0  1.292   5.891    0    0    0    0  1.350  5.742  1605.516747    1    0    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..        ...  ..  ..       ...     ...  ...  ...     ...   ...  ...     ...    ...  ...    ...     ...  ...  ...  ...  ...    ...    ...          ...  ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1   7.465508   0   0  1.383791   0.000    0    0   9.311  43.8    0  3.0778  1.253    0  0.991   1.481    1    0    0    0  1.117  2.146   409.698121    0    0    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1   8.225764   0   2  1.412206   0.000    2    0   9.668  38.9    0  3.2726  1.230    0  0.998   1.358    2    0    0    0  1.132  2.315   523.361201    2    0    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  11.170318   0   0  1.557091  24.203    0    0  10.681  58.3    0  2.3715  1.312    0  1.008   1.262    4    0    0    0  1.087  2.500   795.020055    0    0    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6   9.601548   0   0  1.648851  11.747    0    1  10.735  32.4    0  1.9452  1.166    0  0.992  10.593    0    0    0    0  1.140  2.300   613.579107    3    0    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6   9.601548   0   0  1.634521  11.724    0    1  10.694  31.4    0  1.9472  1.153    0  0.993   9.639    0    0    0    0  1.143  2.321   613.579107    3    0    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/09084dadb994c1eb1d41ac9654c18ff2/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/09084dadb994c1eb1d41ac9654c18ff2/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/0c20f602c8c8ef7b079e1c3304ce9b34/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0c20f602c8c8ef7b079e1c3304ce9b34/metadata.json
@ -0,0 +1 @@
 {"duration": 46.452970027923584, "input_args": {"Data": "        F1     F2  F3  F4     F5_em1  F6  F7    F8_l1p      F9  F10  F11       F12_p3   F13  F14     F15    F16  F17    F18     F19  F20  F21  F22  F23    F24    F25       F26_p4  F27  F28  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0   8.611882   3   0  1.535145   0.000    0    1   970.887179  46.7    1  3.1934  1.359    0  1.034   1.476    3    3    0    0  1.100  2.483   541.987500    0    0    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0   7.971026   0   6  1.509839   0.000    6    0  1016.287637  35.1    0  1.8929  1.209    0  0.974   4.130    0    0    0    0  1.139  1.744   433.132851    0    0    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  10.290933   0   0  1.467644  21.884    0    0  1069.343823  42.1    0  2.3934  1.204    0  1.027   1.027    0    0    0    2  1.120  2.773   616.048483    0    0    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  13.731676  23   0  1.730770   9.855    0    1  1885.025911  31.6    0  7.7233  0.906    0  1.291   5.094    0    0    0    0  1.348  5.741  1591.360175    1    0    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  13.879732  27   0  1.756995   9.894    0    1  1962.044794  31.8    0  7.9184  0.906    0  1.292   5.891    0    0    0    0  1.350  5.742  1605.516747    1    0    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..        ...  ..  ..       ...     ...  ...  ...          ...   ...  ...     ...    ...  ...    ...     ...  ...  ...  ...  ...    ...    ...          ...  ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1   7.465508   0   0  1.383791   0.000    0    0   807.214547  43.8    0  3.0778  1.253    0  0.991   1.481    1    0    0    0  1.117  2.146   409.698121    0    0    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1   8.225764   0   2  1.412206   0.000    2    0   903.670126  38.9    0  3.2726  1.230    0  0.998   1.358    2    0    0    0  1.132  2.315   523.361201    2    0    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  11.170318   0   0  1.557091  24.203    0    0  1218.528651  58.3    0  2.3715  1.312    0  1.008   1.262    4    0    0    0  1.087  2.500   795.020055    0    0    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6   9.601548   0   0  1.648851  11.747    0    1  1237.103815  32.4    0  1.9452  1.166    0  0.992  10.593    0    0    0    0  1.140  2.300   613.579107    3    0    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6   9.601548   0   0  1.634521  11.724    0    1  1222.983335  31.4    0  1.9472  1.153    0  0.993   9.639    0    0    0    0  1.143  2.321   613.579107    3    0    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/0cf26a0ace4cf44623ed9e0f324ad28c/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0cf26a0ace4cf44623ed9e0f324ad28c/metadata.json
@ -0,0 +1 @@
 {"duration": 39.2252459526062, "input_args": {"Data": "        F1     F2  F3  F4     F5  F6  F7     F8_l2      F9  F10  F11     F12   F13  ...  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0  2.263   3   0  1.864731   0.000    0    1   9.902  46.7  ...    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0  2.194   0   6  1.818032   0.000    6    0  10.054  35.1  ...    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  2.424   0   0  1.739416  21.884    0    0  10.226  42.1  ...    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  2.690  23   0  2.215679   9.855    0    1  12.353  31.6  ...    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  2.700  27   0  2.261531   9.894    0    1  12.519  31.8  ...    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..    ...  ..  ..       ...     ...  ...  ...     ...   ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1  2.136   0   0  1.580145   0.000    0    0   9.311  43.8  ...    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1  2.222   0   2  1.634593   0.000    2    0   9.668  38.9  ...    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  2.499   0   0  1.904966  24.203    0    0  10.681  58.3  ...    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6  2.361   0   0  2.070733  11.747    0    1  10.735  32.4  ...    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6  2.361   0   0  2.045093  11.724    0    1  10.694  31.4  ...    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/0d5467cfcb3692caa554061d986834a1/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0d5467cfcb3692caa554061d986834a1/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/0e09d698e192a513a0e48318923cfe0d/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0e09d698e192a513a0e48318923cfe0d/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/0e6aa1ae1ffd78d7c9c405c11cb17ed9/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0e6aa1ae1ffd78d7c9c405c11cb17ed9/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/0f8f7f0b0182403045b700a7e1ae9528/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/0f8f7f0b0182403045b700a7e1ae9528/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/14ebb2205f65f2d37f60c52fbdf8fd76/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/14ebb2205f65f2d37f60c52fbdf8fd76/metadata.json
@ -0,0 +1 @@
 {"duration": 16.30320119857788, "input_args": {"Data": "        F8_l2     F12  F8_l2+F12  |F8_l2-F12|  F8_l2xF12  F8_l2/F12  F12/F8_l2\n0    1.864731   9.902  11.766731     8.037269  18.464566   0.188319   5.310150\n1    1.818032  10.054  11.872032     8.235968  18.278499   0.180827   5.530154\n2    1.739416  10.226  11.965416     8.486584  17.787269   0.170097   5.878984\n3    2.215679  12.353  14.568679    10.137321  27.370278   0.179364   5.575267\n4    2.261531  12.519  14.780531    10.257469  28.312104   0.180648   5.535631\n..        ...     ...        ...          ...        ...        ...        ...\n832  1.580145   9.311  10.891145     7.730855  14.712735   0.169707   5.892495\n833  1.634593   9.668  11.302593     8.033407  15.803248   0.169073   5.914621\n834  1.904966  10.681  12.585966     8.776034  20.346939   0.178351   5.606925\n835  2.070733  10.735  12.805733     8.664267  22.229316   0.192895   5.184155\n836  2.045093  10.694  12.739093     8.648907  21.870229   0.191237   5.229101\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/19f73053d9c815e84da2c40a02f76932/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/19f73053d9c815e84da2c40a02f76932/metadata.json
@ -0,0 +1 @@
 {"duration": 14.528310060501099, "input_args": {"Data": "        F2     F8_l2   F2+F8_l2  |F2-F8_l2|   F2xF8_l2  F2/F8_l2  F8_l2/F2\n0    9.085  1.864731  10.949731    7.220269  16.941080  4.872017  0.205254\n1    8.179  1.818032   9.997032    6.360968  14.869688  4.498820  0.222281\n2    8.297  1.739416  10.036416    6.557584  14.431935  4.769992  0.209644\n3    9.673  2.215679  11.888679    7.457321  21.432259  4.365705  0.229058\n4    9.825  2.261531  12.086531    7.563469  22.219540  4.344402  0.230181\n..     ...       ...        ...         ...        ...       ...       ...\n832  7.878  1.580145   9.458145    6.297855  12.448386  4.985617  0.200577\n833  8.046  1.634593   9.680593    6.411407  13.151937  4.922325  0.203156\n834  8.901  1.904966  10.805966    6.996034  16.956100  4.672525  0.214017\n835  8.778  2.070733  10.848733    6.707267  18.176892  4.239079  0.235900\n836  8.680  2.045093  10.725093    6.634907  17.751411  4.244305  0.235610\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/1dece5a6ac641a158f55f38c2f19bc3a/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/1dece5a6ac641a158f55f38c2f19bc3a/metadata.json
@ -1 +0,0 @@
 {"duration": 10.279210090637207, "input_args": {"Data": "        F1_l2   F2   F3   F4  F1_l2+F4\n0    1.321928  3.3  6.3  6.0  7.321928\n1    0.925999  2.7  5.8  5.1  6.025999\n2    1.070389  3.0  7.1  5.9  6.970389\n3    0.847997  2.9  6.3  5.6  6.447997\n4    1.137504  3.0  6.5  5.8  6.937504\n..        ...  ...  ...  ...       ...\n145 -1.736966  3.0  4.8  1.4 -0.336966\n146 -2.321928  3.8  5.1  1.6 -0.721928\n147 -2.321928  3.2  4.6  1.4 -0.921928\n148 -2.321928  3.7  5.3  1.5 -0.821928\n149 -2.321928  3.3  5.0  1.4 -0.921928\n\n[150 rows x 5 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              objective='multi:softprob', probability=True, random_state=42,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n              subsample=0.9972633684544026, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/1edf0aab1322bad6d8bc1faf9d99ec87/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/1edf0aab1322bad6d8bc1faf9d99ec87/metadata.json
@ -1 +0,0 @@
 {"duration": 13.386974096298218, "input_args": {"Data": "         F1_l2  F6_b  F1_l2+F6_b  |F1_l2-F6_b|  F1_l2xF6_b  F1_l2/F6_b  F6_b/F1_l2\n0    -0.621488     1    0.378512      1.621488   -0.621488   -0.621488   -1.609041\n1    -0.785875     1    0.214125      1.785875   -0.785875   -0.785875   -1.272467\n2    -1.836501    11    9.163499     12.836501  -20.201514   -0.166955   -5.989650\n3    -1.395929     6    4.604071      7.395929   -8.375572   -0.232655   -4.298214\n4    -0.943416     3    2.056584      3.943416   -2.830249   -0.314472   -3.179932\n...        ...   ...         ...           ...         ...         ...         ...\n1594 -0.736966     2    1.263034      2.736966   -1.473931   -0.368483   -2.713831\n1595 -0.862496     2    1.137504      2.862496   -1.724993   -0.431248   -2.318850\n1596 -0.971431     3    2.028569      3.971431   -2.914293   -0.323810   -3.088228\n1597 -0.632629     3    2.367371      3.632629   -1.897887   -0.210876   -4.742116\n1598 -1.689660     9    7.310340     10.689660  -15.206939   -0.187740   -5.326516\n\n[1599 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.9223705789444759,\n              eta=0.08487346516301046, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.0848734677, max_delta_step=0, max_depth=7,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=76, n_jobs=12, num_parallel_tree=1,\n              objective='multi:softprob', probability=True, random_state=42,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n              subsample=0.8912139968434072, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/2221b5c353b2aca71982e3930c6a849e/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/2221b5c353b2aca71982e3930c6a849e/metadata.json
@ -0,0 +1 @@
 {"duration": 36.06182813644409, "input_args": {"Data": "        F1     F2  F3  F4      F5_p4  F6  F7    F8_l1p      F9  F10  F11     F12   F13  F14     F15    F16  F17    F18     F19  F20  F21  F22  F23    F24    F25       F26_p4  F27  F28  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0  26.226372   3   0  1.535145   0.000    0    1   9.902  46.7    1  3.1934  1.359    0  1.034   1.476    3    3    0    0  1.100  2.483   541.987500    0    0    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0  23.171092   0   6  1.509839   0.000    6    0  10.054  35.1    0  1.8929  1.209    0  0.974   4.130    0    0    0    0  1.139  1.744   433.132851    0    0    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  34.524744   0   0  1.467644  21.884    0    0  10.226  42.1    0  2.3934  1.204    0  1.027   1.027    0    0    0    2  1.120  2.773   616.048483    0    0    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  52.361143  23   0  1.730770   9.855    0    1  12.353  31.6    0  7.7233  0.906    0  1.291   5.094    0    0    0    0  1.348  5.741  1591.360175    1    0    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  53.144100  27   0  1.756995   9.894    0    1  12.519  31.8    0  7.9184  0.906    0  1.292   5.891    0    0    0    0  1.350  5.742  1605.516747    1    0    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..        ...  ..  ..       ...     ...  ...  ...     ...   ...  ...     ...    ...  ...    ...     ...  ...  ...  ...  ...    ...    ...          ...  ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1  20.816370   0   0  1.383791   0.000    0    0   9.311  43.8    0  3.0778  1.253    0  0.991   1.481    1    0    0    0  1.117  2.146   409.698121    0    0    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1  24.376773   0   2  1.412206   0.000    2    0   9.668  38.9    0  3.2726  1.230    0  0.998   1.358    2    0    0    0  1.132  2.315   523.361201    2    0    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  39.000037   0   0  1.557091  24.203    0    0  10.681  58.3    0  2.3715  1.312    0  1.008   1.262    4    0    0    0  1.087  2.500   795.020055    0    0    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6  31.073055   0   0  1.648851  11.747    0    1  10.735  32.4    0  1.9452  1.166    0  0.992  10.593    0    0    0    0  1.140  2.300   613.579107    3    0    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6  31.073055   0   0  1.634521  11.724    0    1  10.694  31.4    0  1.9472  1.153    0  0.993   9.639    0    0    0    0  1.143  2.321   613.579107    3    0    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/23bdef957a8c99991197f093001eec87/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/23bdef957a8c99991197f093001eec87/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/294e8763914741a79b0838898ece3368/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/294e8763914741a79b0838898ece3368/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/2956fe3fc2ead99c0e75e9a3188d9e47/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/2956fe3fc2ead99c0e75e9a3188d9e47/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/2ba580f7ff5e5310897b12f768a7c058/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/2ba580f7ff5e5310897b12f768a7c058/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/2bc58d6b58235a4f804147e27bb7ba82/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/2bc58d6b58235a4f804147e27bb7ba82/metadata.json
@ -0,0 +1 @@
 {"duration": 28.126965045928955, "input_args": {"Data": "        F1     F2  F3  F4     F5    F6_l1p  F7     F8_l2      F9  F10  F11     F12  ...  F30    F31  F32  F33  F34    F35  F36   F37_l10  F38  F39_l10  F40  F41\n0    1.185  9.085   0   0  2.263  1.386294   0  1.864731   0.000    0    1   9.902  ...    0  0.000    1    0    0  0.014    0  0.607884    0  0.00000    0    0\n1    0.000  8.179   2   0  2.194  0.000000   6  1.818032   0.000    6    0  10.054  ...    0  0.000    2    0    0  0.000    0  0.542701    0  0.60206    0    0\n2    0.762  8.297   0   3  2.424  0.000000   0  1.739416  21.884    0    0  10.226  ...    8 -0.686    3    0    0  0.004    0  0.567379    0  0.00000    0    0\n3    1.747  9.673   0   2  2.690  3.178054   0  2.215679   9.855    0    1  12.353  ...    2 -4.617    0    0   11  0.000    0  0.601299    0  0.00000    0    1\n4    1.824  9.825   0   2  2.700  3.332205   0  2.261531   9.894    0    1  12.519  ...    2 -4.724    0    0   13  0.000    0  0.602603    0  0.00000    0    1\n..     ...    ...  ..  ..    ...       ...  ..       ...     ...  ...  ...     ...  ...  ...    ...  ...  ...  ...    ...  ...       ...  ...      ...  ...  ...\n832  1.125  7.878   0   1  2.136  0.000000   0  1.580145   0.000    0    0   9.311  ...    2  0.000    1    0    0  0.045    0  0.553033    0  0.00000    0    0\n833  1.187  8.046   1   1  2.222  0.000000   2  1.634593   0.000    2    0   9.668  ...    2  0.000    1    0    0 -0.025    0  0.564192    0  0.30103    0    0\n834  0.625  8.901   0   2  2.499  0.000000   0  1.904966  24.203    0    0  10.681  ...    8 -0.128    6    0    0  0.000    0  0.595717    0  0.00000    0    0\n835  3.866  8.778   0   6  2.361  0.000000   0  2.070733  11.747    0    1  10.735  ...    9 -0.347    1    0    0  0.000    0  0.543696    0  0.00000    0    0\n836  3.706  8.680   0   6  2.361  0.000000   0  2.045093  11.724    0    1  10.694  ...    9 -0.338    1    0    0  0.000    0  0.543696    0  0.00000    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/2cec3ede420aa45b1efd7f743dbf8e01/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/2cec3ede420aa45b1efd7f743dbf8e01/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/2dd4af227f7f5e75e7a30a786dc19aac/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/2dd4af227f7f5e75e7a30a786dc19aac/metadata.json
@ -0,0 +1 @@
 {"duration": 21.14425778388977, "input_args": {"Data": "        F5     F12  F5+F12  |F5-F12|     F5xF12    F5/F12    F12/F5\n0    2.263   9.902  12.165     7.639  22.408226  0.228540  4.375608\n1    2.194  10.054  12.248     7.860  22.058476  0.218222  4.582498\n2    2.424  10.226  12.650     7.802  24.787824  0.237043  4.218647\n3    2.690  12.353  15.043     9.663  33.229570  0.217761  4.592193\n4    2.700  12.519  15.219     9.819  33.801300  0.215672  4.636667\n..     ...     ...     ...       ...        ...       ...       ...\n832  2.136   9.311  11.447     7.175  19.888296  0.229406  4.359082\n833  2.222   9.668  11.890     7.446  21.482296  0.229830  4.351035\n834  2.499  10.681  13.180     8.182  26.691819  0.233967  4.274110\n835  2.361  10.735  13.096     8.374  25.345335  0.219935  4.546802\n836  2.361  10.694  13.055     8.333  25.248534  0.220778  4.529437\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/35b06c1585296cbe5dbde2720b41dc63/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/35b06c1585296cbe5dbde2720b41dc63/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/3ccec7a626a2fb858a5cc1c2b2f25282/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/3ccec7a626a2fb858a5cc1c2b2f25282/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/3d6891067cef4ae3f8881a8e07adda34/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/3d6891067cef4ae3f8881a8e07adda34/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/3e9ed49e5b059ae812700e00d4534a3f/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/3e9ed49e5b059ae812700e00d4534a3f/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/402017027ba3a50afc90fd835298d6b6/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/402017027ba3a50afc90fd835298d6b6/metadata.json
@ -1 +0,0 @@
 {"duration": 23.081444025039673, "input_args": {"Data": "        F5     F26_p2  F5+F26_p2  |F5-F26_p2|   F5xF26_p2  F5/F26_p2  F26_p2/F5\n0    2.263  23.280625  25.543625    21.017625   52.684054   0.097205  10.287506\n1    2.194  20.811844  23.005844    18.617844   45.661186   0.105421   9.485799\n2    2.424  24.820324  27.244324    22.396324   60.164465   0.097662  10.239408\n3    2.690  39.891856  42.581856    37.201856  107.309093   0.067432  14.829686\n4    2.700  40.068900  42.768900    37.368900  108.186030   0.067384  14.840333\n..     ...        ...        ...          ...         ...        ...        ...\n832  2.136  20.241001  22.377001    18.105001   43.234778   0.105528   9.476124\n833  2.222  22.877089  25.099089    20.655089   50.832892   0.097128  10.295720\n834  2.499  28.196100  30.695100    25.697100   70.462054   0.088629  11.282953\n835  2.361  24.770529  27.131529    22.409529   58.483219   0.095315  10.491541\n836  2.361  24.770529  27.131529    22.409529   58.483219   0.095315  10.491541\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/41dab28469e4379ce8ff25d934657637/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/41dab28469e4379ce8ff25d934657637/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/44719fe531ecc273e584e52cb7589cb9/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/44719fe531ecc273e584e52cb7589cb9/metadata.json
@ -0,0 +1 @@
 {"duration": 37.37262415885925, "input_args": {"Data": "        F1     F2  F3  F4     F5  F6  F7     F8_l2      F9  F10  F11     F12   F13  F14     F15    F16  F17    F18     F19  F20   F21_l1p  F22  F23    F24    F25       F26_p4  F27  F28  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0  2.263   3   0  1.864731   0.000    0    1   9.902  46.7    1  3.1934  1.359    0  1.034   1.476    3  1.386294    0    0  1.100  2.483   541.987500    0    0    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0  2.194   0   6  1.818032   0.000    6    0  10.054  35.1    0  1.8929  1.209    0  0.974   4.130    0  0.000000    0    0  1.139  1.744   433.132851    0    0    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  2.424   0   0  1.739416  21.884    0    0  10.226  42.1    0  2.3934  1.204    0  1.027   1.027    0  0.000000    0    2  1.120  2.773   616.048483    0    0    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  2.690  23   0  2.215679   9.855    0    1  12.353  31.6    0  7.7233  0.906    0  1.291   5.094    0  0.000000    0    0  1.348  5.741  1591.360175    1    0    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  2.700  27   0  2.261531   9.894    0    1  12.519  31.8    0  7.9184  0.906    0  1.292   5.891    0  0.000000    0    0  1.350  5.742  1605.516747    1    0    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..    ...  ..  ..       ...     ...  ...  ...     ...   ...  ...     ...    ...  ...    ...     ...  ...       ...  ...  ...    ...    ...          ...  ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1  2.136   0   0  1.580145   0.000    0    0   9.311  43.8    0  3.0778  1.253    0  0.991   1.481    1  0.000000    0    0  1.117  2.146   409.698121    0    0    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1  2.222   0   2  1.634593   0.000    2    0   9.668  38.9    0  3.2726  1.230    0  0.998   1.358    2  0.000000    0    0  1.132  2.315   523.361201    2    0    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  2.499   0   0  1.904966  24.203    0    0  10.681  58.3    0  2.3715  1.312    0  1.008   1.262    4  0.000000    0    0  1.087  2.500   795.020055    0    0    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6  2.361   0   0  2.070733  11.747    0    1  10.735  32.4    0  1.9452  1.166    0  0.992  10.593    0  0.000000    0    0  1.140  2.300   613.579107    3    0    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6  2.361   0   0  2.045093  11.724    0    1  10.694  31.4    0  1.9472  1.153    0  0.993   9.639    0  0.000000    0    0  1.143  2.321   613.579107    3    0    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/44ec384289903c56f725fa4c7080f4f9/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/44ec384289903c56f725fa4c7080f4f9/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/485f52ed4cb0c38642671ad4188376a9/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/485f52ed4cb0c38642671ad4188376a9/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/498aaebdf7e953577636fb0a77d1e9f5/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/498aaebdf7e953577636fb0a77d1e9f5/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/4b9aa4234cd17658680e9705e0dfc853/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/4b9aa4234cd17658680e9705e0dfc853/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/4ba274c6e70c70db814318f28218b0fb/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/4ba274c6e70c70db814318f28218b0fb/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/4d4f2677947733cf5690e46ac2809a1f/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/4d4f2677947733cf5690e46ac2809a1f/metadata.json
@ -0,0 +1 @@
 {"duration": 31.682257890701294, "input_args": {"Data": "        F5_em1      F12_p2       F26_p4  F5_em1+F12_p2  F12_p2+F26_p4  F5_em1+F26_p4  F5_em1+F12_p2+F26_p4  ...  F26_p4/F5_em1  F5_em1/F12_p2/F26_p4  F5_em1/F26_p4/F12_p2  F12_p2/F26_p4/F5_em1  F12_p2/F5_em1/F26_p4  F26_p4/F5_em1/F12_p2  F26_p4/F12_p2/F5_em1\n0     8.611882   98.049604   541.987500     106.661486     640.037104     550.599382            648.648986  ...      62.934853              0.000162              0.000162              0.021007              0.021007              0.641867              0.641867\n1     7.971026  101.082916   433.132851     109.053942     534.215767     441.103876            542.186792  ...      54.338410              0.000182              0.000182              0.029278              0.029278              0.537563              0.537563\n2    10.290933  104.571076   616.048483     114.862009     720.619559     626.339416            730.910492  ...      59.863230              0.000160              0.000160              0.016495              0.016495              0.572465              0.572465\n3    13.731676  152.596609  1591.360175     166.328285    1743.956784    1605.091851           1757.688460  ...     115.889727              0.000057              0.000057              0.006983              0.006983              0.759452              0.759452\n4    13.879732  156.725361  1605.516747     170.605093    1762.242108    1619.396479           1776.121840  ...     115.673471              0.000055              0.000055              0.007033              0.007033              0.738065              0.738065\n..         ...         ...          ...            ...            ...            ...                   ...  ...            ...                   ...                   ...                   ...                   ...                   ...                   ...\n832   7.465508   86.694721   409.698121      94.160229     496.392842     417.163629            503.858350  ...      54.878802              0.000210              0.000210              0.028345              0.028345              0.633012              0.633012\n833   8.225764   93.470224   523.361201     101.695988     616.831425     531.586965            625.057189  ...      63.624632              0.000168              0.000168              0.021712              0.021712              0.680694              0.680694\n834  11.170318  114.083761   795.020055     125.254079     909.103816     806.190373            920.274134  ...      71.172556              0.000123              0.000123              0.012846              0.012846              0.623862              0.623862\n835   9.601548  115.240225   613.579107     124.841773     728.819332     623.180655            738.420880  ...      63.904188              0.000136              0.000136              0.019561              0.019561              0.554530              0.554530\n836   9.601548  114.361636   613.579107     123.963184     727.940743     623.180655            737.542291  ...      63.904188              0.000137              0.000137              0.019412              0.019412              0.558790              0.558790\n\n[837 rows x 27 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/4e5e0ad1742a47076aecdf47f8cce30d/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/4e5e0ad1742a47076aecdf47f8cce30d/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/51d22e80197033bfba7c393a5135e6a3/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/51d22e80197033bfba7c393a5135e6a3/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/520fc41c95deafe327fa32fd24b968c6/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/520fc41c95deafe327fa32fd24b968c6/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/5325ae9ab4d892e28c2fd6154fcfbcb9/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5325ae9ab4d892e28c2fd6154fcfbcb9/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/5338659cb0c734abf279561337879b33/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5338659cb0c734abf279561337879b33/metadata.json
@ -0,0 +1 @@
 {"duration": 10.513028860092163, "input_args": {"Data": "        F2    F37_l2  F2+F37_l2  |F2-F37_l2|  F2xF37_l2  F2/F37_l2  F37_l2/F2\n0    9.085  2.019346  11.104346     7.065654  18.345759   4.498981   0.222273\n1    8.179  1.802814   9.981814     6.376186  14.745212   4.536797   0.220420\n2    8.297  1.884793  10.181793     6.412207  15.638130   4.402074   0.227166\n3    9.673  1.997473  11.670473     7.675527  19.321557   4.842618   0.206500\n4    9.825  2.001802  11.826802     7.823198  19.667707   4.908077   0.203746\n..     ...       ...        ...          ...        ...        ...        ...\n832  7.878  1.837136   9.715136     6.040864  14.472957   4.288197   0.233198\n833  8.046  1.874207   9.920207     6.171793  15.079868   4.293016   0.232936\n834  8.901  1.978928  10.879928     6.922072  17.614436   4.497890   0.222326\n835  8.778  1.806118  10.584118     6.971882  15.854102   4.860148   0.205755\n836  8.680  1.806118  10.486118     6.873882  15.677102   4.805888   0.208078\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/5619edf6be3516c79ed02031bef792cc/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5619edf6be3516c79ed02031bef792cc/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/5635ceb7546a57c7b1f509770402b4d9/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5635ceb7546a57c7b1f509770402b4d9/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/5750f70183ad143b12ee3d9f5100c9a4/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5750f70183ad143b12ee3d9f5100c9a4/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/5ae633be555c108d6dbaf783d5b7febf/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5ae633be555c108d6dbaf783d5b7febf/output.pkl
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--- a/cachedir/joblib/run/estimatorFeatureSelection/5c6d9ec9ebd0c96ad37bcece2a7b1ab1/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5c6d9ec9ebd0c96ad37bcece2a7b1ab1/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/5e75c467e81d002fe3d1b9d0b67d946c/output.pkl
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--- a/cachedir/joblib/run/estimatorFeatureSelection/5fa740243b273457bc3baef8701c08b7/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/5fa740243b273457bc3baef8701c08b7/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/610bb029753a23a56fb410e68151c6c1/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/610bb029753a23a56fb410e68151c6c1/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/64cbff1b01949bb0ce657830f9e570ab/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/64cbff1b01949bb0ce657830f9e570ab/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/6773274ba885294c36e936cd0b3de42c/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6773274ba885294c36e936cd0b3de42c/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/678837c1e9d3a64ed577088ed10f6b7b/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/696aa511b71ded760fcddc1a66f612dd/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/696aa511b71ded760fcddc1a66f612dd/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/6a00ae0dc0a73430ffc1bb4fb54c4f00/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6a00ae0dc0a73430ffc1bb4fb54c4f00/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/6a8b4f44c93cb574e128ff83bfc2bcbe/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6a8b4f44c93cb574e128ff83bfc2bcbe/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/6c7221458a9d947f06a9502fc98332dd/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6c7221458a9d947f06a9502fc98332dd/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/6cb9aa4d3e4f65304fcd4f4b64757ac2/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6cb9aa4d3e4f65304fcd4f4b64757ac2/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/6cf213f12622de3190590ff357a547c7/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6cf213f12622de3190590ff357a547c7/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/6d2be047daf51bdd2730a3af563cfed8/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6d2be047daf51bdd2730a3af563cfed8/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/6e02e84047b19fc8eff9a063b06e8edd/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/6e02e84047b19fc8eff9a063b06e8edd/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/7102203dd1359b6f1157285dc780242a/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/7102203dd1359b6f1157285dc780242a/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/72a6b348a0dd22fb660d39f82b6736d8/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/72a6b348a0dd22fb660d39f82b6736d8/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/72ac4adfa3e5cbdd57bcba63418bbace/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/72ac4adfa3e5cbdd57bcba63418bbace/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/74bc362a63daf52533adca063a624313/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/74bc362a63daf52533adca063a624313/metadata.json
@ -1 +0,0 @@
 {"duration": 26.64803910255432, "input_args": {"Data": "      F1   F2  F3    F4_p4  F5   F6  F7  F8   F9  F10  F11  F12  F13  F14  F15  F16  F17   F18\n0    184  162  48  3111696  70  197  10   6  176   72   95  159   16  178   20  187   83   379\n1    158  149  41  4100625  72  199   9   9  170   57   91  143   14  141   19  189   84   330\n2    127  144  41  4477456  63  207   9   6  160   63   93  143   10  159   19  199   82   309\n3    164  137  43  5308416  67  202   9   3  162   65   90  146    3  157   18  193   66   281\n4    112  122  34  8503056  64  208   7   2  141   61   86  127   14  140   17  200   62   223\n..   ...  ...  ..      ...  ..  ...  ..  ..  ...  ...  ...  ...  ...  ...  ...  ...  ...   ...\n841  173  150  43  4100625  83  183   7   4  172   55   85  146   15  123   19  180   66   326\n842  186  151  45  4100625  88  185  22   1  186   69   81  147   10  154   19  180   68   335\n843  119  151  37  3418801  65  208   7   0  167   66   97  129   16  173   19  201   70   346\n844  172  162  47  2560000  68  205   7   9  179   70  100  153    6  185   20  200   70   406\n845  255  265  58   456976  85  183   6   4  285   51  111  174    8  183   29  181  105  1018\n\n[846 rows x 18 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.9223705789444759,\n              eta=0.08487346516301046, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.0848734677, max_delta_step=0, max_depth=7,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=76, n_jobs=12, num_parallel_tree=1,\n              objective='multi:softprob', probability=True, random_state=42,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n              subsample=0.8912139968434072, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/751c583899c82c3dd976754417920520/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/751c583899c82c3dd976754417920520/output.pkl
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+++ b/cachedir/joblib/run/estimatorFeatureSelection/758edac5fdf9a29fc85fa1a3b2a9c409/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/760b2cbd0988b06f70ccd37910f3033b/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/760b2cbd0988b06f70ccd37910f3033b/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/76bcf55a91df8fc3fc34773609714dee/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/76bcf55a91df8fc3fc34773609714dee/metadata.json
@ -1 +0,0 @@
 {"duration": 36.848369121551514, "input_args": {"Data": "        F5     F12     F26_p2  F5+F12  F12+F26_p2  F5+F26_p2  F5+F12+F26_p2  |F5-F12|  |F12-F26_p2|  |F5-F26_p2|  ...  F12/F26_p2  F26_p2/F12  F5/F26_p2  F26_p2/F5  F5/F12/F26_p2  F5/F26_p2/F12  F12/F26_p2/F5  F12/F5/F26_p2  F26_p2/F5/F12  F26_p2/F12/F5\n0    2.263   9.902  23.280625  12.165   33.182625  25.543625      35.445625     7.639     13.378625    21.017625  ...    0.425332    2.351103   0.097205  10.287506       0.009817       0.009817       0.187951       0.187951       1.038932       1.038932\n1    2.194  10.054  20.811844  12.248   30.865844  23.005844      33.059844     7.860     10.757844    18.617844  ...    0.483090    2.070006   0.105421   9.485799       0.010485       0.010485       0.220187       0.220187       0.943485       0.943485\n2    2.424  10.226  24.820324  12.650   35.046324  27.244324      37.470324     7.802     14.594324    22.396324  ...    0.412001    2.427178   0.097662  10.239408       0.009550       0.009550       0.169967       0.169967       1.001311       1.001311\n3    2.690  12.353  39.891856  15.043   52.244856  42.581856      54.934856     9.663     27.538856    37.201856  ...    0.309662    3.229325   0.067432  14.829686       0.005459       0.005459       0.115116       0.115116       1.200493       1.200493\n4    2.700  12.519  40.068900  15.219   52.587900  42.768900      55.287900     9.819     27.549900    37.368900  ...    0.312437    3.200647   0.067384  14.840333       0.005383       0.005383       0.115717       0.115717       1.185425       1.185425\n..     ...     ...        ...     ...         ...        ...            ...       ...           ...          ...  ...         ...         ...        ...        ...            ...            ...            ...            ...            ...            ...\n832  2.136   9.311  20.241001  11.447   29.552001  22.377001      31.688001     7.175     10.930001    18.105001  ...    0.460007    2.173880   0.105528   9.476124       0.011334       0.011334       0.215359       0.215359       1.017734       1.017734\n833  2.222   9.668  22.877089  11.890   32.545089  25.099089      34.767089     7.446     13.209089    20.655089  ...    0.422606    2.366269   0.097128  10.295720       0.010046       0.010046       0.190192       0.190192       1.064928       1.064928\n834  2.499  10.681  28.196100  13.180   38.877100  30.695100      41.376100     8.182     17.515100    25.697100  ...    0.378811    2.639837   0.088629  11.282953       0.008298       0.008298       0.151585       0.151585       1.056357       1.056357\n835  2.361  10.735  24.770529  13.096   35.505529  27.131529      37.866529     8.374     14.035529    22.409529  ...    0.433378    2.307455   0.095315  10.491541       0.008879       0.008879       0.183557       0.183557       0.977321       0.977321\n836  2.361  10.694  24.770529  13.055   35.464529  27.131529      37.825529     8.333     14.076529    22.409529  ...    0.431723    2.316302   0.095315  10.491541       0.008913       0.008913       0.182856       0.182856       0.981068       0.981068\n\n[837 rows x 27 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/7b6afa134d7be07aeaaf83d85cdce228/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/7b6afa134d7be07aeaaf83d85cdce228/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/7dd418660b962dbd9a2af1431c0496af/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/7dd418660b962dbd9a2af1431c0496af/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/7e5ca030c1668579fbf1c3bfe24d631c/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/7e5ca030c1668579fbf1c3bfe24d631c/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/843d286a97b9fd43f2e2f89ab586b877/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/843d286a97b9fd43f2e2f89ab586b877/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/8535477c687736c77a69b62894907190/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/8535477c687736c77a69b62894907190/metadata.json
@ -1 +0,0 @@
 {"duration": 39.3106529712677, "input_args": {"Data": "        F1     F2  F3  F4     F5  F6  F7     F8      F9  F10  F11     F12   F13  F14     F15    F16  F17    F18     F19  F20  F21  F22  F23    F24    F25     F26_p2  F27  F28  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0  2.263   3   0  3.642   0.000    0    1   9.902  46.7    1  3.1934  1.359    0  1.034   1.476    3    3    0    0  1.100  2.483  23.280625    0    0    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0  2.194   0   6  3.526   0.000    6    0  10.054  35.1    0  1.8929  1.209    0  0.974   4.130    0    0    0    0  1.139  1.744  20.811844    0    0    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  2.424   0   0  3.339  21.884    0    0  10.226  42.1    0  2.3934  1.204    0  1.027   1.027    0    0    0    2  1.120  2.773  24.820324    0    0    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  2.690  23   0  4.645   9.855    0    1  12.353  31.6    0  7.7233  0.906    0  1.291   5.094    0    0    0    0  1.348  5.741  39.891856    1    0    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  2.700  27   0  4.795   9.894    0    1  12.519  31.8    0  7.9184  0.906    0  1.292   5.891    0    0    0    0  1.350  5.742  40.068900    1    0    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..    ...  ..  ..    ...     ...  ...  ...     ...   ...  ...     ...    ...  ...    ...     ...  ...  ...  ...  ...    ...    ...        ...  ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1  2.136   0   0  2.990   0.000    0    0   9.311  43.8    0  3.0778  1.253    0  0.991   1.481    1    0    0    0  1.117  2.146  20.241001    0    0    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1  2.222   0   2  3.105   0.000    2    0   9.668  38.9    0  3.2726  1.230    0  0.998   1.358    2    0    0    0  1.132  2.315  22.877089    2    0    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  2.499   0   0  3.745  24.203    0    0  10.681  58.3    0  2.3715  1.312    0  1.008   1.262    4    0    0    0  1.087  2.500  28.196100    0    0    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6  2.361   0   0  4.201  11.747    0    1  10.735  32.4    0  1.9452  1.166    0  0.992  10.593    0    0    0    0  1.140  2.300  24.770529    3    0    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6  2.361   0   0  4.127  11.724    0    1  10.694  31.4    0  1.9472  1.153    0  0.993   9.639    0    0    0    0  1.143  2.321  24.770529    3    0    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/87b94a4add2e9fd3dab5c7c46aeff563/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/87b94a4add2e9fd3dab5c7c46aeff563/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/87f281cc6a3026fff16744d27118fd89/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/87f281cc6a3026fff16744d27118fd89/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/88fbae4bab966681cad801c198a11b79/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/88fbae4bab966681cad801c198a11b79/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/89fab13156b31d2cf6dd9570330f8375/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/89fab13156b31d2cf6dd9570330f8375/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/89fab13156b31d2cf6dd9570330f8375/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/89fab13156b31d2cf6dd9570330f8375/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/8ad216fec9ad2391d9945cc264fb06fd/output.pkl
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--- a/cachedir/joblib/run/estimatorFeatureSelection/8e45819f1848604688aba5256fd282de/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/8e45819f1848604688aba5256fd282de/output.pkl
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+++ b/cachedir/joblib/run/estimatorFeatureSelection/8fdd9e0baf085ecc8cc8cbaf48a2b77a/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/918a327121a85ee1502fabcb8cdec070/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/918a327121a85ee1502fabcb8cdec070/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/9542eca72d45a0e534a347c646cab7d0/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/9542eca72d45a0e534a347c646cab7d0/metadata.json
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--- a/cachedir/joblib/run/estimatorFeatureSelection/9818da1e86d86943193ed95685c94b84/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/9818da1e86d86943193ed95685c94b84/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/99a2ef44d6ed0bf80fcac97f871cae22/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/99a2ef44d6ed0bf80fcac97f871cae22/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/9bb8074ec6b631e352538287bdfa0b0a/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/9bb8074ec6b631e352538287bdfa0b0a/metadata.json
@ -1 +0,0 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/9beda7f5ef0ad90c3703144998e1712b/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/9beda7f5ef0ad90c3703144998e1712b/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/9faa7354574f71cf9a41c1b450ab6d43/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/9faa7354574f71cf9a41c1b450ab6d43/metadata.json
@ -0,0 +1 @@
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--- a/cachedir/joblib/run/estimatorFeatureSelection/a6d10c8e16c56485298823ed0cf48c75/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/a6d10c8e16c56485298823ed0cf48c75/output.pkl
--- a/cachedir/joblib/run/estimatorFeatureSelection/aa888e12434b582daa8216da815a7193/metadata.json
+++ b/cachedir/joblib/run/estimatorFeatureSelection/aa888e12434b582daa8216da815a7193/metadata.json
@ -0,0 +1 @@
 {"duration": 39.08091402053833, "input_args": {"Data": "        F1     F2  F3  F4     F5_em1  F6  F7     F8      F9  F10  F11     F12   F13  F14     F15    F16  F17    F18     F19  F20  F21  F22  F23    F24    F25    F26  F27  F28  F29  F30    F31  F32  F33  F34    F35  F36    F37  F38  F39  F40  F41\n0    1.185  9.085   0   0   8.611882   3   0  3.642   0.000    0    1   9.902  46.7    1  3.1934  1.359    0  1.034   1.476    3    3    0    0  1.100  2.483  4.825    0    0    2    0  0.000    1    0    0  0.014    0  4.054    0    0    0    0\n1    0.000  8.179   2   0   7.971026   0   6  3.526   0.000    6    0  10.054  35.1    0  1.8929  1.209    0  0.974   4.130    0    0    0    0  1.139  1.744  4.562    0    0    0    0  0.000    2    0    0  0.000    0  3.489    0    4    0    0\n2    0.762  8.297   0   3  10.290933   0   0  3.339  21.884    0    0  10.226  42.1    0  2.3934  1.204    0  1.027   1.027    0    0    0    2  1.120  2.773  4.982    0    0    0    8 -0.686    3    0    0  0.004    0  3.693    0    0    0    0\n3    1.747  9.673   0   2  13.731676  23   0  4.645   9.855    0    1  12.353  31.6    0  7.7233  0.906    0  1.291   5.094    0    0    0    0  1.348  5.741  6.316    1    0    0    2 -4.617    0    0   11  0.000    0  3.993    0    0    0    1\n4    1.824  9.825   0   2  13.879732  27   0  4.795   9.894    0    1  12.519  31.8    0  7.9184  0.906    0  1.292   5.891    0    0    0    0  1.350  5.742  6.330    1    0    0    2 -4.724    0    0   13  0.000    0  4.005    0    0    0    1\n..     ...    ...  ..  ..        ...  ..  ..    ...     ...  ...  ...     ...   ...  ...     ...    ...  ...    ...     ...  ...  ...  ...  ...    ...    ...    ...  ...  ...  ...  ...    ...  ...  ...  ...    ...  ...    ...  ...  ...  ...  ...\n832  1.125  7.878   0   1   7.465508   0   0  2.990   0.000    0    0   9.311  43.8    0  3.0778  1.253    0  0.991   1.481    1    0    0    0  1.117  2.146  4.499    0    0    1    2  0.000    1    0    0  0.045    0  3.573    0    0    0    0\n833  1.187  8.046   1   1   8.225764   0   2  3.105   0.000    2    0   9.668  38.9    0  3.2726  1.230    0  0.998   1.358    2    0    0    0  1.132  2.315  4.783    2    0    2    2  0.000    1    0    0 -0.025    0  3.666    0    2    0    0\n834  0.625  8.901   0   2  11.170318   0   0  3.745  24.203    0    0  10.681  58.3    0  2.3715  1.312    0  1.008   1.262    4    0    0    0  1.087  2.500  5.310    0    0    0    8 -0.128    6    0    0  0.000    0  3.942    0    0    0    0\n835  3.866  8.778   0   6   9.601548   0   0  4.201  11.747    0    1  10.735  32.4    0  1.9452  1.166    0  0.992  10.593    0    0    0    0  1.140  2.300  4.977    3    0    0    9 -0.347    1    0    0  0.000    0  3.497    0    0    0    0\n836  3.706  8.680   0   6   9.601548   0   0  4.127  11.724    0    1  10.694  31.4    0  1.9472  1.153    0  0.993   9.639    0    0    0    0  1.143  2.321  4.977    3    0    0    9 -0.338    1    0    0  0.000    0  3.497    0    0    0    0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8702434039276976,\n              eta=0.2593099998788648, gamma=0, gpu_id=-1,\n              importance_type='gain', interaction_constraints='',\n              learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n              min_child_weight=1, missing=nan, monotone_constraints='()',\n              n_estimators=188, n_jobs=12, num_parallel_tree=1,\n              probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n              scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n              tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}
--- a/cachedir/joblib/run/estimatorFeatureSelection/aba65e314193f69c27783462e6869e73/output.pkl
+++ b/cachedir/joblib/run/estimatorFeatureSelection/aba65e314193f69c27783462e6869e73/output.pkl
--- a/Show More
+++ b/Show More
		`@ -0,0 +1 @@`
							{"duration": 14.059135913848877, "input_args": {"Data": " F7 F10 F7+F10 \|F7-F10\| F7xF10 F7/F10 F10/F7\n0 0 0 0 0 0 0.0 0.0\n1 6 6 12 0 36 1.0 1.0\n2 0 0 0 0 0 0.0 0.0\n3 0 0 0 0 0 0.0 0.0\n4 0 0 0 0 0 0.0 0.0\n.. .. ... ... ... ... ... ...\n832 0 0 0 0 0 0.0 0.0\n833 2 2 4 0 4 1.0 1.0\n834 0 0 0 0 0 0.0 0.0\n835 0 0 0 0 0 0.0 0.0\n836 0 0 0 0 0 0.0 0.0\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -0,0 +1 @@`
							{"duration": 39.00056982040405, "input_args": {"Data": " F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24 F25 F26_p4 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 F37 F38 F39 F40 F41\n0 1.185 9.085 0 0 2.263 3 0 3.642 0.000 0 1 9.902 46.7 1 3.1934 1.359 0 1.034 1.476 3 3 0 0 1.100 2.483 541.987500 0 0 2 0 0.000 1 0 0 0.014 0 4.054 0 0 0 0\n1 0.000 8.179 2 0 2.194 0 6 3.526 0.000 6 0 10.054 35.1 0 1.8929 1.209 0 0.974 4.130 0 0 0 0 1.139 1.744 433.132851 0 0 0 0 0.000 2 0 0 0.000 0 3.489 0 4 0 0\n2 0.762 8.297 0 3 2.424 0 0 3.339 21.884 0 0 10.226 42.1 0 2.3934 1.204 0 1.027 1.027 0 0 0 2 1.120 2.773 616.048483 0 0 0 8 -0.686 3 0 0 0.004 0 3.693 0 0 0 0\n3 1.747 9.673 0 2 2.690 23 0 4.645 9.855 0 1 12.353 31.6 0 7.7233 0.906 0 1.291 5.094 0 0 0 0 1.348 5.741 1591.360175 1 0 0 2 -4.617 0 0 11 0.000 0 3.993 0 0 0 1\n4 1.824 9.825 0 2 2.700 27 0 4.795 9.894 0 1 12.519 31.8 0 7.9184 0.906 0 1.292 5.891 0 0 0 0 1.350 5.742 1605.516747 1 0 0 2 -4.724 0 0 13 0.000 0 4.005 0 0 0 1\n.. ... ... .. .. ... .. .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n832 1.125 7.878 0 1 2.136 0 0 2.990 0.000 0 0 9.311 43.8 0 3.0778 1.253 0 0.991 1.481 1 0 0 0 1.117 2.146 409.698121 0 0 1 2 0.000 1 0 0 0.045 0 3.573 0 0 0 0\n833 1.187 8.046 1 1 2.222 0 2 3.105 0.000 2 0 9.668 38.9 0 3.2726 1.230 0 0.998 1.358 2 0 0 0 1.132 2.315 523.361201 2 0 2 2 0.000 1 0 0 -0.025 0 3.666 0 2 0 0\n834 0.625 8.901 0 2 2.499 0 0 3.745 24.203 0 0 10.681 58.3 0 2.3715 1.312 0 1.008 1.262 4 0 0 0 1.087 2.500 795.020055 0 0 0 8 -0.128 6 0 0 0.000 0 3.942 0 0 0 0\n835 3.866 8.778 0 6 2.361 0 0 4.201 11.747 0 1 10.735 32.4 0 1.9452 1.166 0 0.992 10.593 0 0 0 0 1.140 2.300 613.579107 3 0 0 9 -0.347 1 0 0 0.000 0 3.497 0 0 0 0\n836 3.706 8.680 0 6 2.361 0 0 4.127 11.724 0 1 10.694 31.4 0 1.9472 1.153 0 0.993 9.639 0 0 0 0 1.143 2.321 613.579107 3 0 0 9 -0.338 1 0 0 0.000 0 3.497 0 0 0 0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -0,0 +1 @@`
							{"duration": 37.06569814682007, "input_args": {"Data": " F1 F2 F3 F4 F5_em1 F6 F7 F8_l1p F9 F10 F11 F12 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24 F25 F26_p4 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 F37 F38 F39 F40 F41\n0 1.185 9.085 0 0 8.611882 3 0 1.535145 0.000 0 1 9.902 46.7 1 3.1934 1.359 0 1.034 1.476 3 3 0 0 1.100 2.483 541.987500 0 0 2 0 0.000 1 0 0 0.014 0 4.054 0 0 0 0\n1 0.000 8.179 2 0 7.971026 0 6 1.509839 0.000 6 0 10.054 35.1 0 1.8929 1.209 0 0.974 4.130 0 0 0 0 1.139 1.744 433.132851 0 0 0 0 0.000 2 0 0 0.000 0 3.489 0 4 0 0\n2 0.762 8.297 0 3 10.290933 0 0 1.467644 21.884 0 0 10.226 42.1 0 2.3934 1.204 0 1.027 1.027 0 0 0 2 1.120 2.773 616.048483 0 0 0 8 -0.686 3 0 0 0.004 0 3.693 0 0 0 0\n3 1.747 9.673 0 2 13.731676 23 0 1.730770 9.855 0 1 12.353 31.6 0 7.7233 0.906 0 1.291 5.094 0 0 0 0 1.348 5.741 1591.360175 1 0 0 2 -4.617 0 0 11 0.000 0 3.993 0 0 0 1\n4 1.824 9.825 0 2 13.879732 27 0 1.756995 9.894 0 1 12.519 31.8 0 7.9184 0.906 0 1.292 5.891 0 0 0 0 1.350 5.742 1605.516747 1 0 0 2 -4.724 0 0 13 0.000 0 4.005 0 0 0 1\n.. ... ... .. .. ... .. .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n832 1.125 7.878 0 1 7.465508 0 0 1.383791 0.000 0 0 9.311 43.8 0 3.0778 1.253 0 0.991 1.481 1 0 0 0 1.117 2.146 409.698121 0 0 1 2 0.000 1 0 0 0.045 0 3.573 0 0 0 0\n833 1.187 8.046 1 1 8.225764 0 2 1.412206 0.000 2 0 9.668 38.9 0 3.2726 1.230 0 0.998 1.358 2 0 0 0 1.132 2.315 523.361201 2 0 2 2 0.000 1 0 0 -0.025 0 3.666 0 2 0 0\n834 0.625 8.901 0 2 11.170318 0 0 1.557091 24.203 0 0 10.681 58.3 0 2.3715 1.312 0 1.008 1.262 4 0 0 0 1.087 2.500 795.020055 0 0 0 8 -0.128 6 0 0 0.000 0 3.942 0 0 0 0\n835 3.866 8.778 0 6 9.601548 0 0 1.648851 11.747 0 1 10.735 32.4 0 1.9452 1.166 0 0.992 10.593 0 0 0 0 1.140 2.300 613.579107 3 0 0 9 -0.347 1 0 0 0.000 0 3.497 0 0 0 0\n836 3.706 8.680 0 6 9.601548 0 0 1.634521 11.724 0 1 10.694 31.4 0 1.9472 1.153 0 0.993 9.639 0 0 0 0 1.143 2.321 613.579107 3 0 0 9 -0.338 1 0 0 0.000 0 3.497 0 0 0 0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -0,0 +1 @@`
							{"duration": 46.452970027923584, "input_args": {"Data": " F1 F2 F3 F4 F5_em1 F6 F7 F8_l1p F9 F10 F11 F12_p3 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24 F25 F26_p4 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 F37 F38 F39 F40 F41\n0 1.185 9.085 0 0 8.611882 3 0 1.535145 0.000 0 1 970.887179 46.7 1 3.1934 1.359 0 1.034 1.476 3 3 0 0 1.100 2.483 541.987500 0 0 2 0 0.000 1 0 0 0.014 0 4.054 0 0 0 0\n1 0.000 8.179 2 0 7.971026 0 6 1.509839 0.000 6 0 1016.287637 35.1 0 1.8929 1.209 0 0.974 4.130 0 0 0 0 1.139 1.744 433.132851 0 0 0 0 0.000 2 0 0 0.000 0 3.489 0 4 0 0\n2 0.762 8.297 0 3 10.290933 0 0 1.467644 21.884 0 0 1069.343823 42.1 0 2.3934 1.204 0 1.027 1.027 0 0 0 2 1.120 2.773 616.048483 0 0 0 8 -0.686 3 0 0 0.004 0 3.693 0 0 0 0\n3 1.747 9.673 0 2 13.731676 23 0 1.730770 9.855 0 1 1885.025911 31.6 0 7.7233 0.906 0 1.291 5.094 0 0 0 0 1.348 5.741 1591.360175 1 0 0 2 -4.617 0 0 11 0.000 0 3.993 0 0 0 1\n4 1.824 9.825 0 2 13.879732 27 0 1.756995 9.894 0 1 1962.044794 31.8 0 7.9184 0.906 0 1.292 5.891 0 0 0 0 1.350 5.742 1605.516747 1 0 0 2 -4.724 0 0 13 0.000 0 4.005 0 0 0 1\n.. ... ... .. .. ... .. .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n832 1.125 7.878 0 1 7.465508 0 0 1.383791 0.000 0 0 807.214547 43.8 0 3.0778 1.253 0 0.991 1.481 1 0 0 0 1.117 2.146 409.698121 0 0 1 2 0.000 1 0 0 0.045 0 3.573 0 0 0 0\n833 1.187 8.046 1 1 8.225764 0 2 1.412206 0.000 2 0 903.670126 38.9 0 3.2726 1.230 0 0.998 1.358 2 0 0 0 1.132 2.315 523.361201 2 0 2 2 0.000 1 0 0 -0.025 0 3.666 0 2 0 0\n834 0.625 8.901 0 2 11.170318 0 0 1.557091 24.203 0 0 1218.528651 58.3 0 2.3715 1.312 0 1.008 1.262 4 0 0 0 1.087 2.500 795.020055 0 0 0 8 -0.128 6 0 0 0.000 0 3.942 0 0 0 0\n835 3.866 8.778 0 6 9.601548 0 0 1.648851 11.747 0 1 1237.103815 32.4 0 1.9452 1.166 0 0.992 10.593 0 0 0 0 1.140 2.300 613.579107 3 0 0 9 -0.347 1 0 0 0.000 0 3.497 0 0 0 0\n836 3.706 8.680 0 6 9.601548 0 0 1.634521 11.724 0 1 1222.983335 31.4 0 1.9472 1.153 0 0.993 9.639 0 0 0 0 1.143 2.321 613.579107 3 0 0 9 -0.338 1 0 0 0.000 0 3.497 0 0 0 0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -0,0 +1 @@`
							{"duration": 39.2252459526062, "input_args": {"Data": " F1 F2 F3 F4 F5 F6 F7 F8_l2 F9 F10 F11 F12 F13 ... F29 F30 F31 F32 F33 F34 F35 F36 F37 F38 F39 F40 F41\n0 1.185 9.085 0 0 2.263 3 0 1.864731 0.000 0 1 9.902 46.7 ... 2 0 0.000 1 0 0 0.014 0 4.054 0 0 0 0\n1 0.000 8.179 2 0 2.194 0 6 1.818032 0.000 6 0 10.054 35.1 ... 0 0 0.000 2 0 0 0.000 0 3.489 0 4 0 0\n2 0.762 8.297 0 3 2.424 0 0 1.739416 21.884 0 0 10.226 42.1 ... 0 8 -0.686 3 0 0 0.004 0 3.693 0 0 0 0\n3 1.747 9.673 0 2 2.690 23 0 2.215679 9.855 0 1 12.353 31.6 ... 0 2 -4.617 0 0 11 0.000 0 3.993 0 0 0 1\n4 1.824 9.825 0 2 2.700 27 0 2.261531 9.894 0 1 12.519 31.8 ... 0 2 -4.724 0 0 13 0.000 0 4.005 0 0 0 1\n.. ... ... .. .. ... .. .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n832 1.125 7.878 0 1 2.136 0 0 1.580145 0.000 0 0 9.311 43.8 ... 1 2 0.000 1 0 0 0.045 0 3.573 0 0 0 0\n833 1.187 8.046 1 1 2.222 0 2 1.634593 0.000 2 0 9.668 38.9 ... 2 2 0.000 1 0 0 -0.025 0 3.666 0 2 0 0\n834 0.625 8.901 0 2 2.499 0 0 1.904966 24.203 0 0 10.681 58.3 ... 0 8 -0.128 6 0 0 0.000 0 3.942 0 0 0 0\n835 3.866 8.778 0 6 2.361 0 0 2.070733 11.747 0 1 10.735 32.4 ... 0 9 -0.347 1 0 0 0.000 0 3.497 0 0 0 0\n836 3.706 8.680 0 6 2.361 0 0 2.045093 11.724 0 1 10.694 31.4 ... 0 9 -0.338 1 0 0 0.000 0 3.497 0 0 0 0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -0,0 +1 @@`
							{"duration": 16.30320119857788, "input_args": {"Data": " F8_l2 F12 F8_l2+F12 \|F8_l2-F12\| F8_l2xF12 F8_l2/F12 F12/F8_l2\n0 1.864731 9.902 11.766731 8.037269 18.464566 0.188319 5.310150\n1 1.818032 10.054 11.872032 8.235968 18.278499 0.180827 5.530154\n2 1.739416 10.226 11.965416 8.486584 17.787269 0.170097 5.878984\n3 2.215679 12.353 14.568679 10.137321 27.370278 0.179364 5.575267\n4 2.261531 12.519 14.780531 10.257469 28.312104 0.180648 5.535631\n.. ... ... ... ... ... ... ...\n832 1.580145 9.311 10.891145 7.730855 14.712735 0.169707 5.892495\n833 1.634593 9.668 11.302593 8.033407 15.803248 0.169073 5.914621\n834 1.904966 10.681 12.585966 8.776034 20.346939 0.178351 5.606925\n835 2.070733 10.735 12.805733 8.664267 22.229316 0.192895 5.184155\n836 2.045093 10.694 12.739093 8.648907 21.870229 0.191237 5.229101\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -0,0 +1 @@`
							{"duration": 14.528310060501099, "input_args": {"Data": " F2 F8_l2 F2+F8_l2 \|F2-F8_l2\| F2xF8_l2 F2/F8_l2 F8_l2/F2\n0 9.085 1.864731 10.949731 7.220269 16.941080 4.872017 0.205254\n1 8.179 1.818032 9.997032 6.360968 14.869688 4.498820 0.222281\n2 8.297 1.739416 10.036416 6.557584 14.431935 4.769992 0.209644\n3 9.673 2.215679 11.888679 7.457321 21.432259 4.365705 0.229058\n4 9.825 2.261531 12.086531 7.563469 22.219540 4.344402 0.230181\n.. ... ... ... ... ... ... ...\n832 7.878 1.580145 9.458145 6.297855 12.448386 4.985617 0.200577\n833 8.046 1.634593 9.680593 6.411407 13.151937 4.922325 0.203156\n834 8.901 1.904966 10.805966 6.996034 16.956100 4.672525 0.214017\n835 8.778 2.070733 10.848733 6.707267 18.176892 4.239079 0.235900\n836 8.680 2.045093 10.725093 6.634907 17.751411 4.244305 0.235610\n\n[837 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}
		`@ -1 +0,0 @@`
			{"duration": 10.279210090637207, "input_args": {"Data": " F1_l2 F2 F3 F4 F1_l2+F4\n0 1.321928 3.3 6.3 6.0 7.321928\n1 0.925999 2.7 5.8 5.1 6.025999\n2 1.070389 3.0 7.1 5.9 6.970389\n3 0.847997 2.9 6.3 5.6 6.447997\n4 1.137504 3.0 6.5 5.8 6.937504\n.. ... ... ... ... ...\n145 -1.736966 3.0 4.8 1.4 -0.336966\n146 -2.321928 3.8 5.1 1.6 -0.721928\n147 -2.321928 3.2 4.6 1.4 -0.921928\n148 -2.321928 3.7 5.3 1.5 -0.821928\n149 -2.321928 3.3 5.0 1.4 -0.921928\n\n[150 rows x 5 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n objective='multi:softprob', probability=True, random_state=42,\n reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n subsample=0.9972633684544026, tree_method='exact',\n use_label_encoder=False, validate_parameters=1, ...)"}}
		`@ -1 +0,0 @@`
			{"duration": 13.386974096298218, "input_args": {"Data": " F1_l2 F6_b F1_l2+F6_b \|F1_l2-F6_b\| F1_l2xF6_b F1_l2/F6_b F6_b/F1_l2\n0 -0.621488 1 0.378512 1.621488 -0.621488 -0.621488 -1.609041\n1 -0.785875 1 0.214125 1.785875 -0.785875 -0.785875 -1.272467\n2 -1.836501 11 9.163499 12.836501 -20.201514 -0.166955 -5.989650\n3 -1.395929 6 4.604071 7.395929 -8.375572 -0.232655 -4.298214\n4 -0.943416 3 2.056584 3.943416 -2.830249 -0.314472 -3.179932\n... ... ... ... ... ... ... ...\n1594 -0.736966 2 1.263034 2.736966 -1.473931 -0.368483 -2.713831\n1595 -0.862496 2 1.137504 2.862496 -1.724993 -0.431248 -2.318850\n1596 -0.971431 3 2.028569 3.971431 -2.914293 -0.323810 -3.088228\n1597 -0.632629 3 2.367371 3.632629 -1.897887 -0.210876 -4.742116\n1598 -1.689660 9 7.310340 10.689660 -15.206939 -0.187740 -5.326516\n\n[1599 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.9223705789444759,\n eta=0.08487346516301046, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.0848734677, max_delta_step=0, max_depth=7,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=76, n_jobs=12, num_parallel_tree=1,\n objective='multi:softprob', probability=True, random_state=42,\n reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n subsample=0.8912139968434072, tree_method='exact',\n use_label_encoder=False, validate_parameters=1, ...)"}}
		`@ -0,0 +1 @@`
							{"duration": 36.06182813644409, "input_args": {"Data": " F1 F2 F3 F4 F5_p4 F6 F7 F8_l1p F9 F10 F11 F12 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24 F25 F26_p4 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 F37 F38 F39 F40 F41\n0 1.185 9.085 0 0 26.226372 3 0 1.535145 0.000 0 1 9.902 46.7 1 3.1934 1.359 0 1.034 1.476 3 3 0 0 1.100 2.483 541.987500 0 0 2 0 0.000 1 0 0 0.014 0 4.054 0 0 0 0\n1 0.000 8.179 2 0 23.171092 0 6 1.509839 0.000 6 0 10.054 35.1 0 1.8929 1.209 0 0.974 4.130 0 0 0 0 1.139 1.744 433.132851 0 0 0 0 0.000 2 0 0 0.000 0 3.489 0 4 0 0\n2 0.762 8.297 0 3 34.524744 0 0 1.467644 21.884 0 0 10.226 42.1 0 2.3934 1.204 0 1.027 1.027 0 0 0 2 1.120 2.773 616.048483 0 0 0 8 -0.686 3 0 0 0.004 0 3.693 0 0 0 0\n3 1.747 9.673 0 2 52.361143 23 0 1.730770 9.855 0 1 12.353 31.6 0 7.7233 0.906 0 1.291 5.094 0 0 0 0 1.348 5.741 1591.360175 1 0 0 2 -4.617 0 0 11 0.000 0 3.993 0 0 0 1\n4 1.824 9.825 0 2 53.144100 27 0 1.756995 9.894 0 1 12.519 31.8 0 7.9184 0.906 0 1.292 5.891 0 0 0 0 1.350 5.742 1605.516747 1 0 0 2 -4.724 0 0 13 0.000 0 4.005 0 0 0 1\n.. ... ... .. .. ... .. .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n832 1.125 7.878 0 1 20.816370 0 0 1.383791 0.000 0 0 9.311 43.8 0 3.0778 1.253 0 0.991 1.481 1 0 0 0 1.117 2.146 409.698121 0 0 1 2 0.000 1 0 0 0.045 0 3.573 0 0 0 0\n833 1.187 8.046 1 1 24.376773 0 2 1.412206 0.000 2 0 9.668 38.9 0 3.2726 1.230 0 0.998 1.358 2 0 0 0 1.132 2.315 523.361201 2 0 2 2 0.000 1 0 0 -0.025 0 3.666 0 2 0 0\n834 0.625 8.901 0 2 39.000037 0 0 1.557091 24.203 0 0 10.681 58.3 0 2.3715 1.312 0 1.008 1.262 4 0 0 0 1.087 2.500 795.020055 0 0 0 8 -0.128 6 0 0 0.000 0 3.942 0 0 0 0\n835 3.866 8.778 0 6 31.073055 0 0 1.648851 11.747 0 1 10.735 32.4 0 1.9452 1.166 0 0.992 10.593 0 0 0 0 1.140 2.300 613.579107 3 0 0 9 -0.347 1 0 0 0.000 0 3.497 0 0 0 0\n836 3.706 8.680 0 6 31.073055 0 0 1.634521 11.724 0 1 10.694 31.4 0 1.9472 1.153 0 0.993 9.639 0 0 0 0 1.143 2.321 613.579107 3 0 0 9 -0.338 1 0 0 0.000 0 3.497 0 0 0 0\n\n[837 rows x 41 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.8702434039276976,\n eta=0.2593099998788648, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.259310007, max_delta_step=0, max_depth=6,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=188, n_jobs=12, num_parallel_tree=1,\n probability=True, random_state=42, reg_alpha=0, reg_lambda=1,\n scale_pos_weight=1, silent=True, subsample=0.9972633684544026,\n tree_method='exact', use_label_encoder=False,\n validate_parameters=1, verbosity=0)"}}