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Anton Nesterov 2024-10-02 18:11:01 +02:00
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@ -0,0 +1,768 @@
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1,139,46,19,83,28.7,0.654,22,0
3,116,0,0,0,23.5,0.187,23,0
3,99,62,19,74,21.8,0.279,26,0
5,0,80,32,0,41.0,0.346,37,1
4,92,80,0,0,42.2,0.237,29,0
4,137,84,0,0,31.2,0.252,30,0
3,61,82,28,0,34.4,0.243,46,0
1,90,62,12,43,27.2,0.580,24,0
3,90,78,0,0,42.7,0.559,21,0
9,165,88,0,0,30.4,0.302,49,1
1,125,50,40,167,33.3,0.962,28,1
13,129,0,30,0,39.9,0.569,44,1
12,88,74,40,54,35.3,0.378,48,0
1,196,76,36,249,36.5,0.875,29,1
5,189,64,33,325,31.2,0.583,29,1
5,158,70,0,0,29.8,0.207,63,0
5,103,108,37,0,39.2,0.305,65,0
4,146,78,0,0,38.5,0.520,67,1
4,147,74,25,293,34.9,0.385,30,0
5,99,54,28,83,34.0,0.499,30,0
6,124,72,0,0,27.6,0.368,29,1
0,101,64,17,0,21.0,0.252,21,0
3,81,86,16,66,27.5,0.306,22,0
1,133,102,28,140,32.8,0.234,45,1
3,173,82,48,465,38.4,2.137,25,1
0,118,64,23,89,0.0,1.731,21,0
0,84,64,22,66,35.8,0.545,21,0
2,105,58,40,94,34.9,0.225,25,0
2,122,52,43,158,36.2,0.816,28,0
12,140,82,43,325,39.2,0.528,58,1
0,98,82,15,84,25.2,0.299,22,0
1,87,60,37,75,37.2,0.509,22,0
4,156,75,0,0,48.3,0.238,32,1
0,93,100,39,72,43.4,1.021,35,0
1,107,72,30,82,30.8,0.821,24,0
0,105,68,22,0,20.0,0.236,22,0
1,109,60,8,182,25.4,0.947,21,0
1,90,62,18,59,25.1,1.268,25,0
1,125,70,24,110,24.3,0.221,25,0
1,119,54,13,50,22.3,0.205,24,0
5,116,74,29,0,32.3,0.660,35,1
8,105,100,36,0,43.3,0.239,45,1
5,144,82,26,285,32.0,0.452,58,1
3,100,68,23,81,31.6,0.949,28,0
1,100,66,29,196,32.0,0.444,42,0
5,166,76,0,0,45.7,0.340,27,1
1,131,64,14,415,23.7,0.389,21,0
4,116,72,12,87,22.1,0.463,37,0
4,158,78,0,0,32.9,0.803,31,1
2,127,58,24,275,27.7,1.600,25,0
3,96,56,34,115,24.7,0.944,39,0
0,131,66,40,0,34.3,0.196,22,1
3,82,70,0,0,21.1,0.389,25,0
3,193,70,31,0,34.9,0.241,25,1
4,95,64,0,0,32.0,0.161,31,1
6,137,61,0,0,24.2,0.151,55,0
5,136,84,41,88,35.0,0.286,35,1
9,72,78,25,0,31.6,0.280,38,0
5,168,64,0,0,32.9,0.135,41,1
2,123,48,32,165,42.1,0.520,26,0
4,115,72,0,0,28.9,0.376,46,1
0,101,62,0,0,21.9,0.336,25,0
8,197,74,0,0,25.9,1.191,39,1
1,172,68,49,579,42.4,0.702,28,1
6,102,90,39,0,35.7,0.674,28,0
1,112,72,30,176,34.4,0.528,25,0
1,143,84,23,310,42.4,1.076,22,0
1,143,74,22,61,26.2,0.256,21,0
0,138,60,35,167,34.6,0.534,21,1
3,173,84,33,474,35.7,0.258,22,1
1,97,68,21,0,27.2,1.095,22,0
4,144,82,32,0,38.5,0.554,37,1
1,83,68,0,0,18.2,0.624,27,0
3,129,64,29,115,26.4,0.219,28,1
1,119,88,41,170,45.3,0.507,26,0
2,94,68,18,76,26.0,0.561,21,0
0,102,64,46,78,40.6,0.496,21,0
2,115,64,22,0,30.8,0.421,21,0
8,151,78,32,210,42.9,0.516,36,1
4,184,78,39,277,37.0,0.264,31,1
0,94,0,0,0,0.0,0.256,25,0
1,181,64,30,180,34.1,0.328,38,1
0,135,94,46,145,40.6,0.284,26,0
1,95,82,25,180,35.0,0.233,43,1
2,99,0,0,0,22.2,0.108,23,0
3,89,74,16,85,30.4,0.551,38,0
1,80,74,11,60,30.0,0.527,22,0
2,139,75,0,0,25.6,0.167,29,0
1,90,68,8,0,24.5,1.138,36,0
0,141,0,0,0,42.4,0.205,29,1
12,140,85,33,0,37.4,0.244,41,0
5,147,75,0,0,29.9,0.434,28,0
1,97,70,15,0,18.2,0.147,21,0
6,107,88,0,0,36.8,0.727,31,0
0,189,104,25,0,34.3,0.435,41,1
2,83,66,23,50,32.2,0.497,22,0
4,117,64,27,120,33.2,0.230,24,0
8,108,70,0,0,30.5,0.955,33,1
4,117,62,12,0,29.7,0.380,30,1
0,180,78,63,14,59.4,2.420,25,1
1,100,72,12,70,25.3,0.658,28,0
0,95,80,45,92,36.5,0.330,26,0
0,104,64,37,64,33.6,0.510,22,1
0,120,74,18,63,30.5,0.285,26,0
1,82,64,13,95,21.2,0.415,23,0
2,134,70,0,0,28.9,0.542,23,1
0,91,68,32,210,39.9,0.381,25,0
2,119,0,0,0,19.6,0.832,72,0
2,100,54,28,105,37.8,0.498,24,0
14,175,62,30,0,33.6,0.212,38,1
1,135,54,0,0,26.7,0.687,62,0
5,86,68,28,71,30.2,0.364,24,0
10,148,84,48,237,37.6,1.001,51,1
9,134,74,33,60,25.9,0.460,81,0
9,120,72,22,56,20.8,0.733,48,0
1,71,62,0,0,21.8,0.416,26,0
8,74,70,40,49,35.3,0.705,39,0
5,88,78,30,0,27.6,0.258,37,0
10,115,98,0,0,24.0,1.022,34,0
0,124,56,13,105,21.8,0.452,21,0
0,74,52,10,36,27.8,0.269,22,0
0,97,64,36,100,36.8,0.600,25,0
8,120,0,0,0,30.0,0.183,38,1
6,154,78,41,140,46.1,0.571,27,0
1,144,82,40,0,41.3,0.607,28,0
0,137,70,38,0,33.2,0.170,22,0
0,119,66,27,0,38.8,0.259,22,0
7,136,90,0,0,29.9,0.210,50,0
4,114,64,0,0,28.9,0.126,24,0
0,137,84,27,0,27.3,0.231,59,0
2,105,80,45,191,33.7,0.711,29,1
7,114,76,17,110,23.8,0.466,31,0
8,126,74,38,75,25.9,0.162,39,0
4,132,86,31,0,28.0,0.419,63,0
3,158,70,30,328,35.5,0.344,35,1
0,123,88,37,0,35.2,0.197,29,0
4,85,58,22,49,27.8,0.306,28,0
0,84,82,31,125,38.2,0.233,23,0
0,145,0,0,0,44.2,0.630,31,1
0,135,68,42,250,42.3,0.365,24,1
1,139,62,41,480,40.7,0.536,21,0
0,173,78,32,265,46.5,1.159,58,0
4,99,72,17,0,25.6,0.294,28,0
8,194,80,0,0,26.1,0.551,67,0
2,83,65,28,66,36.8,0.629,24,0
2,89,90,30,0,33.5,0.292,42,0
4,99,68,38,0,32.8,0.145,33,0
4,125,70,18,122,28.9,1.144,45,1
3,80,0,0,0,0.0,0.174,22,0
6,166,74,0,0,26.6,0.304,66,0
5,110,68,0,0,26.0,0.292,30,0
2,81,72,15,76,30.1,0.547,25,0
7,195,70,33,145,25.1,0.163,55,1
6,154,74,32,193,29.3,0.839,39,0
2,117,90,19,71,25.2,0.313,21,0
3,84,72,32,0,37.2,0.267,28,0
6,0,68,41,0,39.0,0.727,41,1
7,94,64,25,79,33.3,0.738,41,0
3,96,78,39,0,37.3,0.238,40,0
10,75,82,0,0,33.3,0.263,38,0
0,180,90,26,90,36.5,0.314,35,1
1,130,60,23,170,28.6,0.692,21,0
2,84,50,23,76,30.4,0.968,21,0
8,120,78,0,0,25.0,0.409,64,0
12,84,72,31,0,29.7,0.297,46,1
0,139,62,17,210,22.1,0.207,21,0
9,91,68,0,0,24.2,0.200,58,0
2,91,62,0,0,27.3,0.525,22,0
3,99,54,19,86,25.6,0.154,24,0
3,163,70,18,105,31.6,0.268,28,1
9,145,88,34,165,30.3,0.771,53,1
7,125,86,0,0,37.6,0.304,51,0
13,76,60,0,0,32.8,0.180,41,0
6,129,90,7,326,19.6,0.582,60,0
2,68,70,32,66,25.0,0.187,25,0
3,124,80,33,130,33.2,0.305,26,0
6,114,0,0,0,0.0,0.189,26,0
9,130,70,0,0,34.2,0.652,45,1
3,125,58,0,0,31.6,0.151,24,0
3,87,60,18,0,21.8,0.444,21,0
1,97,64,19,82,18.2,0.299,21,0
3,116,74,15,105,26.3,0.107,24,0
0,117,66,31,188,30.8,0.493,22,0
0,111,65,0,0,24.6,0.660,31,0
2,122,60,18,106,29.8,0.717,22,0
0,107,76,0,0,45.3,0.686,24,0
1,86,66,52,65,41.3,0.917,29,0
6,91,0,0,0,29.8,0.501,31,0
1,77,56,30,56,33.3,1.251,24,0
4,132,0,0,0,32.9,0.302,23,1
0,105,90,0,0,29.6,0.197,46,0
0,57,60,0,0,21.7,0.735,67,0
0,127,80,37,210,36.3,0.804,23,0
3,129,92,49,155,36.4,0.968,32,1
8,100,74,40,215,39.4,0.661,43,1
3,128,72,25,190,32.4,0.549,27,1
10,90,85,32,0,34.9,0.825,56,1
4,84,90,23,56,39.5,0.159,25,0
1,88,78,29,76,32.0,0.365,29,0
8,186,90,35,225,34.5,0.423,37,1
5,187,76,27,207,43.6,1.034,53,1
4,131,68,21,166,33.1,0.160,28,0
1,164,82,43,67,32.8,0.341,50,0
4,189,110,31,0,28.5,0.680,37,0
1,116,70,28,0,27.4,0.204,21,0
3,84,68,30,106,31.9,0.591,25,0
6,114,88,0,0,27.8,0.247,66,0
1,88,62,24,44,29.9,0.422,23,0
1,84,64,23,115,36.9,0.471,28,0
7,124,70,33,215,25.5,0.161,37,0
1,97,70,40,0,38.1,0.218,30,0
8,110,76,0,0,27.8,0.237,58,0
11,103,68,40,0,46.2,0.126,42,0
11,85,74,0,0,30.1,0.300,35,0
6,125,76,0,0,33.8,0.121,54,1
0,198,66,32,274,41.3,0.502,28,1
1,87,68,34,77,37.6,0.401,24,0
6,99,60,19,54,26.9,0.497,32,0
0,91,80,0,0,32.4,0.601,27,0
2,95,54,14,88,26.1,0.748,22,0
1,99,72,30,18,38.6,0.412,21,0
6,92,62,32,126,32.0,0.085,46,0
4,154,72,29,126,31.3,0.338,37,0
0,121,66,30,165,34.3,0.203,33,1
3,78,70,0,0,32.5,0.270,39,0
2,130,96,0,0,22.6,0.268,21,0
3,111,58,31,44,29.5,0.430,22,0
2,98,60,17,120,34.7,0.198,22,0
1,143,86,30,330,30.1,0.892,23,0
1,119,44,47,63,35.5,0.280,25,0
6,108,44,20,130,24.0,0.813,35,0
2,118,80,0,0,42.9,0.693,21,1
10,133,68,0,0,27.0,0.245,36,0
2,197,70,99,0,34.7,0.575,62,1
0,151,90,46,0,42.1,0.371,21,1
6,109,60,27,0,25.0,0.206,27,0
12,121,78,17,0,26.5,0.259,62,0
8,100,76,0,0,38.7,0.190,42,0
8,124,76,24,600,28.7,0.687,52,1
1,93,56,11,0,22.5,0.417,22,0
8,143,66,0,0,34.9,0.129,41,1
6,103,66,0,0,24.3,0.249,29,0
3,176,86,27,156,33.3,1.154,52,1
0,73,0,0,0,21.1,0.342,25,0
11,111,84,40,0,46.8,0.925,45,1
2,112,78,50,140,39.4,0.175,24,0
3,132,80,0,0,34.4,0.402,44,1
2,82,52,22,115,28.5,1.699,25,0
6,123,72,45,230,33.6,0.733,34,0
0,188,82,14,185,32.0,0.682,22,1
0,67,76,0,0,45.3,0.194,46,0
1,89,24,19,25,27.8,0.559,21,0
1,173,74,0,0,36.8,0.088,38,1
1,109,38,18,120,23.1,0.407,26,0
1,108,88,19,0,27.1,0.400,24,0
6,96,0,0,0,23.7,0.190,28,0
1,124,74,36,0,27.8,0.100,30,0
7,150,78,29,126,35.2,0.692,54,1
4,183,0,0,0,28.4,0.212,36,1
1,124,60,32,0,35.8,0.514,21,0
1,181,78,42,293,40.0,1.258,22,1
1,92,62,25,41,19.5,0.482,25,0
0,152,82,39,272,41.5,0.270,27,0
1,111,62,13,182,24.0,0.138,23,0
3,106,54,21,158,30.9,0.292,24,0
3,174,58,22,194,32.9,0.593,36,1
7,168,88,42,321,38.2,0.787,40,1
6,105,80,28,0,32.5,0.878,26,0
11,138,74,26,144,36.1,0.557,50,1
3,106,72,0,0,25.8,0.207,27,0
6,117,96,0,0,28.7,0.157,30,0
2,68,62,13,15,20.1,0.257,23,0
9,112,82,24,0,28.2,1.282,50,1
0,119,0,0,0,32.4,0.141,24,1
2,112,86,42,160,38.4,0.246,28,0
2,92,76,20,0,24.2,1.698,28,0
6,183,94,0,0,40.8,1.461,45,0
0,94,70,27,115,43.5,0.347,21,0
2,108,64,0,0,30.8,0.158,21,0
4,90,88,47,54,37.7,0.362,29,0
0,125,68,0,0,24.7,0.206,21,0
0,132,78,0,0,32.4,0.393,21,0
5,128,80,0,0,34.6,0.144,45,0
4,94,65,22,0,24.7,0.148,21,0
7,114,64,0,0,27.4,0.732,34,1
0,102,78,40,90,34.5,0.238,24,0
2,111,60,0,0,26.2,0.343,23,0
1,128,82,17,183,27.5,0.115,22,0
10,92,62,0,0,25.9,0.167,31,0
13,104,72,0,0,31.2,0.465,38,1
5,104,74,0,0,28.8,0.153,48,0
2,94,76,18,66,31.6,0.649,23,0
7,97,76,32,91,40.9,0.871,32,1
1,100,74,12,46,19.5,0.149,28,0
0,102,86,17,105,29.3,0.695,27,0
4,128,70,0,0,34.3,0.303,24,0
6,147,80,0,0,29.5,0.178,50,1
4,90,0,0,0,28.0,0.610,31,0
3,103,72,30,152,27.6,0.730,27,0
2,157,74,35,440,39.4,0.134,30,0
1,167,74,17,144,23.4,0.447,33,1
0,179,50,36,159,37.8,0.455,22,1
11,136,84,35,130,28.3,0.260,42,1
0,107,60,25,0,26.4,0.133,23,0
1,91,54,25,100,25.2,0.234,23,0
1,117,60,23,106,33.8,0.466,27,0
5,123,74,40,77,34.1,0.269,28,0
2,120,54,0,0,26.8,0.455,27,0
1,106,70,28,135,34.2,0.142,22,0
2,155,52,27,540,38.7,0.240,25,1
2,101,58,35,90,21.8,0.155,22,0
1,120,80,48,200,38.9,1.162,41,0
11,127,106,0,0,39.0,0.190,51,0
3,80,82,31,70,34.2,1.292,27,1
10,162,84,0,0,27.7,0.182,54,0
1,199,76,43,0,42.9,1.394,22,1
8,167,106,46,231,37.6,0.165,43,1
9,145,80,46,130,37.9,0.637,40,1
6,115,60,39,0,33.7,0.245,40,1
1,112,80,45,132,34.8,0.217,24,0
4,145,82,18,0,32.5,0.235,70,1
10,111,70,27,0,27.5,0.141,40,1
6,98,58,33,190,34.0,0.430,43,0
9,154,78,30,100,30.9,0.164,45,0
6,165,68,26,168,33.6,0.631,49,0
1,99,58,10,0,25.4,0.551,21,0
10,68,106,23,49,35.5,0.285,47,0
3,123,100,35,240,57.3,0.880,22,0
8,91,82,0,0,35.6,0.587,68,0
6,195,70,0,0,30.9,0.328,31,1
9,156,86,0,0,24.8,0.230,53,1
0,93,60,0,0,35.3,0.263,25,0
3,121,52,0,0,36.0,0.127,25,1
2,101,58,17,265,24.2,0.614,23,0
2,56,56,28,45,24.2,0.332,22,0
0,162,76,36,0,49.6,0.364,26,1
0,95,64,39,105,44.6,0.366,22,0
4,125,80,0,0,32.3,0.536,27,1
5,136,82,0,0,0.0,0.640,69,0
2,129,74,26,205,33.2,0.591,25,0
3,130,64,0,0,23.1,0.314,22,0
1,107,50,19,0,28.3,0.181,29,0
1,140,74,26,180,24.1,0.828,23,0
1,144,82,46,180,46.1,0.335,46,1
8,107,80,0,0,24.6,0.856,34,0
13,158,114,0,0,42.3,0.257,44,1
2,121,70,32,95,39.1,0.886,23,0
7,129,68,49,125,38.5,0.439,43,1
2,90,60,0,0,23.5,0.191,25,0
7,142,90,24,480,30.4,0.128,43,1
3,169,74,19,125,29.9,0.268,31,1
0,99,0,0,0,25.0,0.253,22,0
4,127,88,11,155,34.5,0.598,28,0
4,118,70,0,0,44.5,0.904,26,0
2,122,76,27,200,35.9,0.483,26,0
6,125,78,31,0,27.6,0.565,49,1
1,168,88,29,0,35.0,0.905,52,1
2,129,0,0,0,38.5,0.304,41,0
4,110,76,20,100,28.4,0.118,27,0
6,80,80,36,0,39.8,0.177,28,0
10,115,0,0,0,0.0,0.261,30,1
2,127,46,21,335,34.4,0.176,22,0
9,164,78,0,0,32.8,0.148,45,1
2,93,64,32,160,38.0,0.674,23,1
3,158,64,13,387,31.2,0.295,24,0
5,126,78,27,22,29.6,0.439,40,0
10,129,62,36,0,41.2,0.441,38,1
0,134,58,20,291,26.4,0.352,21,0
3,102,74,0,0,29.5,0.121,32,0
7,187,50,33,392,33.9,0.826,34,1
3,173,78,39,185,33.8,0.970,31,1
10,94,72,18,0,23.1,0.595,56,0
1,108,60,46,178,35.5,0.415,24,0
5,97,76,27,0,35.6,0.378,52,1
4,83,86,19,0,29.3,0.317,34,0
1,114,66,36,200,38.1,0.289,21,0
1,149,68,29,127,29.3,0.349,42,1
5,117,86,30,105,39.1,0.251,42,0
1,111,94,0,0,32.8,0.265,45,0
4,112,78,40,0,39.4,0.236,38,0
1,116,78,29,180,36.1,0.496,25,0
0,141,84,26,0,32.4,0.433,22,0
2,175,88,0,0,22.9,0.326,22,0
2,92,52,0,0,30.1,0.141,22,0
3,130,78,23,79,28.4,0.323,34,1
8,120,86,0,0,28.4,0.259,22,1
2,174,88,37,120,44.5,0.646,24,1
2,106,56,27,165,29.0,0.426,22,0
2,105,75,0,0,23.3,0.560,53,0
4,95,60,32,0,35.4,0.284,28,0
0,126,86,27,120,27.4,0.515,21,0
8,65,72,23,0,32.0,0.600,42,0
2,99,60,17,160,36.6,0.453,21,0
1,102,74,0,0,39.5,0.293,42,1
11,120,80,37,150,42.3,0.785,48,1
3,102,44,20,94,30.8,0.400,26,0
1,109,58,18,116,28.5,0.219,22,0
9,140,94,0,0,32.7,0.734,45,1
13,153,88,37,140,40.6,1.174,39,0
12,100,84,33,105,30.0,0.488,46,0
1,147,94,41,0,49.3,0.358,27,1
1,81,74,41,57,46.3,1.096,32,0
3,187,70,22,200,36.4,0.408,36,1
6,162,62,0,0,24.3,0.178,50,1
4,136,70,0,0,31.2,1.182,22,1
1,121,78,39,74,39.0,0.261,28,0
3,108,62,24,0,26.0,0.223,25,0
0,181,88,44,510,43.3,0.222,26,1
8,154,78,32,0,32.4,0.443,45,1
1,128,88,39,110,36.5,1.057,37,1
7,137,90,41,0,32.0,0.391,39,0
0,123,72,0,0,36.3,0.258,52,1
1,106,76,0,0,37.5,0.197,26,0
6,190,92,0,0,35.5,0.278,66,1
2,88,58,26,16,28.4,0.766,22,0
9,170,74,31,0,44.0,0.403,43,1
9,89,62,0,0,22.5,0.142,33,0
10,101,76,48,180,32.9,0.171,63,0
2,122,70,27,0,36.8,0.340,27,0
5,121,72,23,112,26.2,0.245,30,0
1,126,60,0,0,30.1,0.349,47,1
1,93,70,31,0,30.4,0.315,23,0
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406 2 123 48 32 165 42.1 0.520 26 0
407 4 115 72 0 0 28.9 0.376 46 1
408 0 101 62 0 0 21.9 0.336 25 0
409 8 197 74 0 0 25.9 1.191 39 1
410 1 172 68 49 579 42.4 0.702 28 1
411 6 102 90 39 0 35.7 0.674 28 0
412 1 112 72 30 176 34.4 0.528 25 0
413 1 143 84 23 310 42.4 1.076 22 0
414 1 143 74 22 61 26.2 0.256 21 0
415 0 138 60 35 167 34.6 0.534 21 1
416 3 173 84 33 474 35.7 0.258 22 1
417 1 97 68 21 0 27.2 1.095 22 0
418 4 144 82 32 0 38.5 0.554 37 1
419 1 83 68 0 0 18.2 0.624 27 0
420 3 129 64 29 115 26.4 0.219 28 1
421 1 119 88 41 170 45.3 0.507 26 0
422 2 94 68 18 76 26.0 0.561 21 0
423 0 102 64 46 78 40.6 0.496 21 0
424 2 115 64 22 0 30.8 0.421 21 0
425 8 151 78 32 210 42.9 0.516 36 1
426 4 184 78 39 277 37.0 0.264 31 1
427 0 94 0 0 0 0.0 0.256 25 0
428 1 181 64 30 180 34.1 0.328 38 1
429 0 135 94 46 145 40.6 0.284 26 0
430 1 95 82 25 180 35.0 0.233 43 1
431 2 99 0 0 0 22.2 0.108 23 0
432 3 89 74 16 85 30.4 0.551 38 0
433 1 80 74 11 60 30.0 0.527 22 0
434 2 139 75 0 0 25.6 0.167 29 0
435 1 90 68 8 0 24.5 1.138 36 0
436 0 141 0 0 0 42.4 0.205 29 1
437 12 140 85 33 0 37.4 0.244 41 0
438 5 147 75 0 0 29.9 0.434 28 0
439 1 97 70 15 0 18.2 0.147 21 0
440 6 107 88 0 0 36.8 0.727 31 0
441 0 189 104 25 0 34.3 0.435 41 1
442 2 83 66 23 50 32.2 0.497 22 0
443 4 117 64 27 120 33.2 0.230 24 0
444 8 108 70 0 0 30.5 0.955 33 1
445 4 117 62 12 0 29.7 0.380 30 1
446 0 180 78 63 14 59.4 2.420 25 1
447 1 100 72 12 70 25.3 0.658 28 0
448 0 95 80 45 92 36.5 0.330 26 0
449 0 104 64 37 64 33.6 0.510 22 1
450 0 120 74 18 63 30.5 0.285 26 0
451 1 82 64 13 95 21.2 0.415 23 0
452 2 134 70 0 0 28.9 0.542 23 1
453 0 91 68 32 210 39.9 0.381 25 0
454 2 119 0 0 0 19.6 0.832 72 0
455 2 100 54 28 105 37.8 0.498 24 0
456 14 175 62 30 0 33.6 0.212 38 1
457 1 135 54 0 0 26.7 0.687 62 0
458 5 86 68 28 71 30.2 0.364 24 0
459 10 148 84 48 237 37.6 1.001 51 1
460 9 134 74 33 60 25.9 0.460 81 0
461 9 120 72 22 56 20.8 0.733 48 0
462 1 71 62 0 0 21.8 0.416 26 0
463 8 74 70 40 49 35.3 0.705 39 0
464 5 88 78 30 0 27.6 0.258 37 0
465 10 115 98 0 0 24.0 1.022 34 0
466 0 124 56 13 105 21.8 0.452 21 0
467 0 74 52 10 36 27.8 0.269 22 0
468 0 97 64 36 100 36.8 0.600 25 0
469 8 120 0 0 0 30.0 0.183 38 1
470 6 154 78 41 140 46.1 0.571 27 0
471 1 144 82 40 0 41.3 0.607 28 0
472 0 137 70 38 0 33.2 0.170 22 0
473 0 119 66 27 0 38.8 0.259 22 0
474 7 136 90 0 0 29.9 0.210 50 0
475 4 114 64 0 0 28.9 0.126 24 0
476 0 137 84 27 0 27.3 0.231 59 0
477 2 105 80 45 191 33.7 0.711 29 1
478 7 114 76 17 110 23.8 0.466 31 0
479 8 126 74 38 75 25.9 0.162 39 0
480 4 132 86 31 0 28.0 0.419 63 0
481 3 158 70 30 328 35.5 0.344 35 1
482 0 123 88 37 0 35.2 0.197 29 0
483 4 85 58 22 49 27.8 0.306 28 0
484 0 84 82 31 125 38.2 0.233 23 0
485 0 145 0 0 0 44.2 0.630 31 1
486 0 135 68 42 250 42.3 0.365 24 1
487 1 139 62 41 480 40.7 0.536 21 0
488 0 173 78 32 265 46.5 1.159 58 0
489 4 99 72 17 0 25.6 0.294 28 0
490 8 194 80 0 0 26.1 0.551 67 0
491 2 83 65 28 66 36.8 0.629 24 0
492 2 89 90 30 0 33.5 0.292 42 0
493 4 99 68 38 0 32.8 0.145 33 0
494 4 125 70 18 122 28.9 1.144 45 1
495 3 80 0 0 0 0.0 0.174 22 0
496 6 166 74 0 0 26.6 0.304 66 0
497 5 110 68 0 0 26.0 0.292 30 0
498 2 81 72 15 76 30.1 0.547 25 0
499 7 195 70 33 145 25.1 0.163 55 1
500 6 154 74 32 193 29.3 0.839 39 0
501 2 117 90 19 71 25.2 0.313 21 0
502 3 84 72 32 0 37.2 0.267 28 0
503 6 0 68 41 0 39.0 0.727 41 1
504 7 94 64 25 79 33.3 0.738 41 0
505 3 96 78 39 0 37.3 0.238 40 0
506 10 75 82 0 0 33.3 0.263 38 0
507 0 180 90 26 90 36.5 0.314 35 1
508 1 130 60 23 170 28.6 0.692 21 0
509 2 84 50 23 76 30.4 0.968 21 0
510 8 120 78 0 0 25.0 0.409 64 0
511 12 84 72 31 0 29.7 0.297 46 1
512 0 139 62 17 210 22.1 0.207 21 0
513 9 91 68 0 0 24.2 0.200 58 0
514 2 91 62 0 0 27.3 0.525 22 0
515 3 99 54 19 86 25.6 0.154 24 0
516 3 163 70 18 105 31.6 0.268 28 1
517 9 145 88 34 165 30.3 0.771 53 1
518 7 125 86 0 0 37.6 0.304 51 0
519 13 76 60 0 0 32.8 0.180 41 0
520 6 129 90 7 326 19.6 0.582 60 0
521 2 68 70 32 66 25.0 0.187 25 0
522 3 124 80 33 130 33.2 0.305 26 0
523 6 114 0 0 0 0.0 0.189 26 0
524 9 130 70 0 0 34.2 0.652 45 1
525 3 125 58 0 0 31.6 0.151 24 0
526 3 87 60 18 0 21.8 0.444 21 0
527 1 97 64 19 82 18.2 0.299 21 0
528 3 116 74 15 105 26.3 0.107 24 0
529 0 117 66 31 188 30.8 0.493 22 0
530 0 111 65 0 0 24.6 0.660 31 0
531 2 122 60 18 106 29.8 0.717 22 0
532 0 107 76 0 0 45.3 0.686 24 0
533 1 86 66 52 65 41.3 0.917 29 0
534 6 91 0 0 0 29.8 0.501 31 0
535 1 77 56 30 56 33.3 1.251 24 0
536 4 132 0 0 0 32.9 0.302 23 1
537 0 105 90 0 0 29.6 0.197 46 0
538 0 57 60 0 0 21.7 0.735 67 0
539 0 127 80 37 210 36.3 0.804 23 0
540 3 129 92 49 155 36.4 0.968 32 1
541 8 100 74 40 215 39.4 0.661 43 1
542 3 128 72 25 190 32.4 0.549 27 1
543 10 90 85 32 0 34.9 0.825 56 1
544 4 84 90 23 56 39.5 0.159 25 0
545 1 88 78 29 76 32.0 0.365 29 0
546 8 186 90 35 225 34.5 0.423 37 1
547 5 187 76 27 207 43.6 1.034 53 1
548 4 131 68 21 166 33.1 0.160 28 0
549 1 164 82 43 67 32.8 0.341 50 0
550 4 189 110 31 0 28.5 0.680 37 0
551 1 116 70 28 0 27.4 0.204 21 0
552 3 84 68 30 106 31.9 0.591 25 0
553 6 114 88 0 0 27.8 0.247 66 0
554 1 88 62 24 44 29.9 0.422 23 0
555 1 84 64 23 115 36.9 0.471 28 0
556 7 124 70 33 215 25.5 0.161 37 0
557 1 97 70 40 0 38.1 0.218 30 0
558 8 110 76 0 0 27.8 0.237 58 0
559 11 103 68 40 0 46.2 0.126 42 0
560 11 85 74 0 0 30.1 0.300 35 0
561 6 125 76 0 0 33.8 0.121 54 1
562 0 198 66 32 274 41.3 0.502 28 1
563 1 87 68 34 77 37.6 0.401 24 0
564 6 99 60 19 54 26.9 0.497 32 0
565 0 91 80 0 0 32.4 0.601 27 0
566 2 95 54 14 88 26.1 0.748 22 0
567 1 99 72 30 18 38.6 0.412 21 0
568 6 92 62 32 126 32.0 0.085 46 0
569 4 154 72 29 126 31.3 0.338 37 0
570 0 121 66 30 165 34.3 0.203 33 1
571 3 78 70 0 0 32.5 0.270 39 0
572 2 130 96 0 0 22.6 0.268 21 0
573 3 111 58 31 44 29.5 0.430 22 0
574 2 98 60 17 120 34.7 0.198 22 0
575 1 143 86 30 330 30.1 0.892 23 0
576 1 119 44 47 63 35.5 0.280 25 0
577 6 108 44 20 130 24.0 0.813 35 0
578 2 118 80 0 0 42.9 0.693 21 1
579 10 133 68 0 0 27.0 0.245 36 0
580 2 197 70 99 0 34.7 0.575 62 1
581 0 151 90 46 0 42.1 0.371 21 1
582 6 109 60 27 0 25.0 0.206 27 0
583 12 121 78 17 0 26.5 0.259 62 0
584 8 100 76 0 0 38.7 0.190 42 0
585 8 124 76 24 600 28.7 0.687 52 1
586 1 93 56 11 0 22.5 0.417 22 0
587 8 143 66 0 0 34.9 0.129 41 1
588 6 103 66 0 0 24.3 0.249 29 0
589 3 176 86 27 156 33.3 1.154 52 1
590 0 73 0 0 0 21.1 0.342 25 0
591 11 111 84 40 0 46.8 0.925 45 1
592 2 112 78 50 140 39.4 0.175 24 0
593 3 132 80 0 0 34.4 0.402 44 1
594 2 82 52 22 115 28.5 1.699 25 0
595 6 123 72 45 230 33.6 0.733 34 0
596 0 188 82 14 185 32.0 0.682 22 1
597 0 67 76 0 0 45.3 0.194 46 0
598 1 89 24 19 25 27.8 0.559 21 0
599 1 173 74 0 0 36.8 0.088 38 1
600 1 109 38 18 120 23.1 0.407 26 0
601 1 108 88 19 0 27.1 0.400 24 0
602 6 96 0 0 0 23.7 0.190 28 0
603 1 124 74 36 0 27.8 0.100 30 0
604 7 150 78 29 126 35.2 0.692 54 1
605 4 183 0 0 0 28.4 0.212 36 1
606 1 124 60 32 0 35.8 0.514 21 0
607 1 181 78 42 293 40.0 1.258 22 1
608 1 92 62 25 41 19.5 0.482 25 0
609 0 152 82 39 272 41.5 0.270 27 0
610 1 111 62 13 182 24.0 0.138 23 0
611 3 106 54 21 158 30.9 0.292 24 0
612 3 174 58 22 194 32.9 0.593 36 1
613 7 168 88 42 321 38.2 0.787 40 1
614 6 105 80 28 0 32.5 0.878 26 0
615 11 138 74 26 144 36.1 0.557 50 1
616 3 106 72 0 0 25.8 0.207 27 0
617 6 117 96 0 0 28.7 0.157 30 0
618 2 68 62 13 15 20.1 0.257 23 0
619 9 112 82 24 0 28.2 1.282 50 1
620 0 119 0 0 0 32.4 0.141 24 1
621 2 112 86 42 160 38.4 0.246 28 0
622 2 92 76 20 0 24.2 1.698 28 0
623 6 183 94 0 0 40.8 1.461 45 0
624 0 94 70 27 115 43.5 0.347 21 0
625 2 108 64 0 0 30.8 0.158 21 0
626 4 90 88 47 54 37.7 0.362 29 0
627 0 125 68 0 0 24.7 0.206 21 0
628 0 132 78 0 0 32.4 0.393 21 0
629 5 128 80 0 0 34.6 0.144 45 0
630 4 94 65 22 0 24.7 0.148 21 0
631 7 114 64 0 0 27.4 0.732 34 1
632 0 102 78 40 90 34.5 0.238 24 0
633 2 111 60 0 0 26.2 0.343 23 0
634 1 128 82 17 183 27.5 0.115 22 0
635 10 92 62 0 0 25.9 0.167 31 0
636 13 104 72 0 0 31.2 0.465 38 1
637 5 104 74 0 0 28.8 0.153 48 0
638 2 94 76 18 66 31.6 0.649 23 0
639 7 97 76 32 91 40.9 0.871 32 1
640 1 100 74 12 46 19.5 0.149 28 0
641 0 102 86 17 105 29.3 0.695 27 0
642 4 128 70 0 0 34.3 0.303 24 0
643 6 147 80 0 0 29.5 0.178 50 1
644 4 90 0 0 0 28.0 0.610 31 0
645 3 103 72 30 152 27.6 0.730 27 0
646 2 157 74 35 440 39.4 0.134 30 0
647 1 167 74 17 144 23.4 0.447 33 1
648 0 179 50 36 159 37.8 0.455 22 1
649 11 136 84 35 130 28.3 0.260 42 1
650 0 107 60 25 0 26.4 0.133 23 0
651 1 91 54 25 100 25.2 0.234 23 0
652 1 117 60 23 106 33.8 0.466 27 0
653 5 123 74 40 77 34.1 0.269 28 0
654 2 120 54 0 0 26.8 0.455 27 0
655 1 106 70 28 135 34.2 0.142 22 0
656 2 155 52 27 540 38.7 0.240 25 1
657 2 101 58 35 90 21.8 0.155 22 0
658 1 120 80 48 200 38.9 1.162 41 0
659 11 127 106 0 0 39.0 0.190 51 0
660 3 80 82 31 70 34.2 1.292 27 1
661 10 162 84 0 0 27.7 0.182 54 0
662 1 199 76 43 0 42.9 1.394 22 1
663 8 167 106 46 231 37.6 0.165 43 1
664 9 145 80 46 130 37.9 0.637 40 1
665 6 115 60 39 0 33.7 0.245 40 1
666 1 112 80 45 132 34.8 0.217 24 0
667 4 145 82 18 0 32.5 0.235 70 1
668 10 111 70 27 0 27.5 0.141 40 1
669 6 98 58 33 190 34.0 0.430 43 0
670 9 154 78 30 100 30.9 0.164 45 0
671 6 165 68 26 168 33.6 0.631 49 0
672 1 99 58 10 0 25.4 0.551 21 0
673 10 68 106 23 49 35.5 0.285 47 0
674 3 123 100 35 240 57.3 0.880 22 0
675 8 91 82 0 0 35.6 0.587 68 0
676 6 195 70 0 0 30.9 0.328 31 1
677 9 156 86 0 0 24.8 0.230 53 1
678 0 93 60 0 0 35.3 0.263 25 0
679 3 121 52 0 0 36.0 0.127 25 1
680 2 101 58 17 265 24.2 0.614 23 0
681 2 56 56 28 45 24.2 0.332 22 0
682 0 162 76 36 0 49.6 0.364 26 1
683 0 95 64 39 105 44.6 0.366 22 0
684 4 125 80 0 0 32.3 0.536 27 1
685 5 136 82 0 0 0.0 0.640 69 0
686 2 129 74 26 205 33.2 0.591 25 0
687 3 130 64 0 0 23.1 0.314 22 0
688 1 107 50 19 0 28.3 0.181 29 0
689 1 140 74 26 180 24.1 0.828 23 0
690 1 144 82 46 180 46.1 0.335 46 1
691 8 107 80 0 0 24.6 0.856 34 0
692 13 158 114 0 0 42.3 0.257 44 1
693 2 121 70 32 95 39.1 0.886 23 0
694 7 129 68 49 125 38.5 0.439 43 1
695 2 90 60 0 0 23.5 0.191 25 0
696 7 142 90 24 480 30.4 0.128 43 1
697 3 169 74 19 125 29.9 0.268 31 1
698 0 99 0 0 0 25.0 0.253 22 0
699 4 127 88 11 155 34.5 0.598 28 0
700 4 118 70 0 0 44.5 0.904 26 0
701 2 122 76 27 200 35.9 0.483 26 0
702 6 125 78 31 0 27.6 0.565 49 1
703 1 168 88 29 0 35.0 0.905 52 1
704 2 129 0 0 0 38.5 0.304 41 0
705 4 110 76 20 100 28.4 0.118 27 0
706 6 80 80 36 0 39.8 0.177 28 0
707 10 115 0 0 0 0.0 0.261 30 1
708 2 127 46 21 335 34.4 0.176 22 0
709 9 164 78 0 0 32.8 0.148 45 1
710 2 93 64 32 160 38.0 0.674 23 1
711 3 158 64 13 387 31.2 0.295 24 0
712 5 126 78 27 22 29.6 0.439 40 0
713 10 129 62 36 0 41.2 0.441 38 1
714 0 134 58 20 291 26.4 0.352 21 0
715 3 102 74 0 0 29.5 0.121 32 0
716 7 187 50 33 392 33.9 0.826 34 1
717 3 173 78 39 185 33.8 0.970 31 1
718 10 94 72 18 0 23.1 0.595 56 0
719 1 108 60 46 178 35.5 0.415 24 0
720 5 97 76 27 0 35.6 0.378 52 1
721 4 83 86 19 0 29.3 0.317 34 0
722 1 114 66 36 200 38.1 0.289 21 0
723 1 149 68 29 127 29.3 0.349 42 1
724 5 117 86 30 105 39.1 0.251 42 0
725 1 111 94 0 0 32.8 0.265 45 0
726 4 112 78 40 0 39.4 0.236 38 0
727 1 116 78 29 180 36.1 0.496 25 0
728 0 141 84 26 0 32.4 0.433 22 0
729 2 175 88 0 0 22.9 0.326 22 0
730 2 92 52 0 0 30.1 0.141 22 0
731 3 130 78 23 79 28.4 0.323 34 1
732 8 120 86 0 0 28.4 0.259 22 1
733 2 174 88 37 120 44.5 0.646 24 1
734 2 106 56 27 165 29.0 0.426 22 0
735 2 105 75 0 0 23.3 0.560 53 0
736 4 95 60 32 0 35.4 0.284 28 0
737 0 126 86 27 120 27.4 0.515 21 0
738 8 65 72 23 0 32.0 0.600 42 0
739 2 99 60 17 160 36.6 0.453 21 0
740 1 102 74 0 0 39.5 0.293 42 1
741 11 120 80 37 150 42.3 0.785 48 1
742 3 102 44 20 94 30.8 0.400 26 0
743 1 109 58 18 116 28.5 0.219 22 0
744 9 140 94 0 0 32.7 0.734 45 1
745 13 153 88 37 140 40.6 1.174 39 0
746 12 100 84 33 105 30.0 0.488 46 0
747 1 147 94 41 0 49.3 0.358 27 1
748 1 81 74 41 57 46.3 1.096 32 0
749 3 187 70 22 200 36.4 0.408 36 1
750 6 162 62 0 0 24.3 0.178 50 1
751 4 136 70 0 0 31.2 1.182 22 1
752 1 121 78 39 74 39.0 0.261 28 0
753 3 108 62 24 0 26.0 0.223 25 0
754 0 181 88 44 510 43.3 0.222 26 1
755 8 154 78 32 0 32.4 0.443 45 1
756 1 128 88 39 110 36.5 1.057 37 1
757 7 137 90 41 0 32.0 0.391 39 0
758 0 123 72 0 0 36.3 0.258 52 1
759 1 106 76 0 0 37.5 0.197 26 0
760 6 190 92 0 0 35.5 0.278 66 1
761 2 88 58 26 16 28.4 0.766 22 0
762 9 170 74 31 0 44.0 0.403 43 1
763 9 89 62 0 0 22.5 0.142 33 0
764 10 101 76 48 180 32.9 0.171 63 0
765 2 122 70 27 0 36.8 0.340 27 0
766 5 121 72 23 112 26.2 0.245 30 0
767 1 126 60 0 0 30.1 0.349 47 1
768 1 93 70 31 0 30.4 0.315 23 0

5
regr/main.go
View file

@ -10,11 +10,12 @@ import (
)
func InitRegrExports(this js.Value, args []js.Value) interface{} {
exports := args[0]
exports := js.Global().Get("Object").New()
exports.Set("Linear", js.FuncOf(src.NewLinearRegressionJS))
exports.Set("ElasticNet", js.FuncOf(src.NewElasticNetJS))
exports.Set("Lasso", js.FuncOf(src.NewLassoJS))
return nil
exports.Set("R2Score", js.FuncOf(src.R2ScoreJS))
return exports
}
func main() {

4
regr/mod.ts
View file

@ -12,9 +12,7 @@ const wasm = wasmMmodule.instance;
go.run(wasm);
const _exports = {} as Record<string, (...args: unknown[]) => unknown>;
// @ts-ignore: no types
__InitRegrExports(_exports);
const _exports = __InitRegrExports(_exports) as Record<string, (...args: unknown[]) => unknown>;
export default _exports;

38
regr/src/CDescent.go
View file

@ -41,7 +41,6 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
RNorm, wNorm, ANorm, nn, tmpfactor := 0., 0., 0., 0., 0.
XtA = mat.NewDense(NFeatures, NTasks, nil)
// # norm_cols_X = (np.asarray(X) ** 2).sum(axis=0)
normColsX := make([]float64, NFeatures)
Xmat := X.RawMatrix()
for jX := 0; jX < Xmat.Rows*Xmat.Stride; jX = jX + Xmat.Stride {
@ -49,18 +48,13 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
normColsX[i] += v * v
}
}
// # R = Y - np.dot(X, W.T)
R.Mul(X, w)
R.Sub(Y, R)
// # tol = tol * linalg.norm(Y, ord='fro') ** 2
Y2.MulElem(Y, Y)
tol *= mat.Sum(Y2)
for nIter = 0; nIter < maxIter; nIter++ {
wmax, dwmax = 0., 0.
for fIter = 0; fIter < NFeatures; fIter++ {
if random {
if rng != nil {
@ -74,23 +68,13 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
if normColsX[ii] == 0. {
continue
}
// # w_ii = W[:, ii] # Store previous value
wii.CopyVec(w.RowView(ii)) // store previous value
// if np.sum(w_ii ** 2) != 0.0: # can do better
if mat.Norm(wii, 2) != 0. {
// # R += X[:,ii] *wii # rank 1 update
xw.Mul(X.ColView(ii), wii.T())
R.Add(R, xw)
}
// # tmp = np.dot(X[:, ii][None, :], R).ravel()
tmp.MulVec(R.T(), X.ColView(ii))
// # nn = sqrt(np.sum(tmp ** 2))
nn = mat.Norm(tmp, 2)
// # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
if l1reg < nn {
tmpfactor = math.Max(1.-l1reg/nn, 0) / (normColsX[ii] + l2reg)
@ -98,16 +82,10 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
tmpfactor = 0.
}
w.RowView(ii).(*mat.VecDense).ScaleVec(tmpfactor, tmp)
// # if np.sum(W[:, ii] ** 2) != 0.0: # can do better
if mat.Norm(w.RowView(ii), 2) != 0. {
// # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
// # Update residual : rank 1 update
xw.Mul(X.ColView(ii), w.RowView(ii).T())
R.Sub(R, xw)
}
// # update the maximum absolute coefficient update
dwii = 0.
for o := 0; o < NTasks; o++ {
v := math.Abs(w.At(ii, o) - wii.AtVec(o))
@ -136,11 +114,6 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
}
if wmax == 0. || dwmax/wmax < dwtol || nIter == maxIter-1 {
// # the biggest coordinate update of this iteration was smaller
// # than the tolerance: check the duality gap as ultimate
// # stopping criterion
// # XtA = np.dot(X.T, R) - l2_reg * W.T
XtA.Mul(X.T(), R)
XtAmat := XtA.RawMatrix()
Wmat := w.RawMatrix()
@ -149,8 +122,6 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
XtAmat.Data[jXtA+i] -= l2reg * Wmat.Data[jW+i]
}
}
// # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
dualNormXtA = 0.
for ii := 0; ii < NFeatures; ii++ {
XtAaxis1norm = mat.Norm(XtA.RowView(ii), 2)
@ -158,8 +129,6 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
dualNormXtA = XtAaxis1norm
}
}
// # R_norm = linalg.norm(R, ord='fro')
// # w_norm = linalg.norm(W, ord='fro')
RNorm = mat.Norm(R, 2)
wNorm = mat.Norm(w, 2)
if dualNormXtA > l1reg {
@ -170,19 +139,12 @@ func CoordinateDescent(w *mat.Dense, l1reg, l2reg float64, X *mat.Dense, Y *mat.
cons = 1.
gap = RNorm * RNorm
}
// # ry_sum = np.sum(R * y)
RY.MulElem(R, Y)
// # l21_norm = np.sqrt(np.sum(W ** 2, axis=0)).sum()
l21norm = 0.
for ii = 0; ii < NFeatures; ii++ {
l21norm += mat.Norm(w.RowView(ii), 2)
}
gap += l1reg*l21norm - cons*mat.Sum(RY) + .5*l2reg*(1.+cons*cons)*(wNorm*wNorm)
// fmt.Printf("X\n%4f\nR:\n%4f\nW:\n%.4f\nXtA:\n%4f\n", mat.Formatted(X), mat.Formatted(R), mat.Formatted(w), mat.Formatted(XtA))
// fmt.Println("dwmax", dwmax, "wmax", wmax, "dwtol", dwtol)
// fmt.Println(nIter, gap, "l1reg", l1reg, "l2reg", l2reg, "l21norm", l21norm, "sumRY", cons*mat.Sum(RY), "dualNormXtA", dualNormXtA, "RNorm", RNorm, "gap", gap)
if gap < tol {
// return if we have reached the desired tolerance
break

7
regr/src/LinearRegression.go
View file

@ -61,3 +61,10 @@ func NewLinearRegressionJS(this js.Value, args []js.Value) interface{} {
}))
return obj
}
func R2ScoreJS(this js.Value, args []js.Value) interface{} {
X := JSFloatArray2D(args[0])
Y := JSFloatArray2D(args[1])
reg := new(LinearRegression)
return reg.Score(X, Y)
}

79
regr/src/LogisticRegression.go Normal file
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@ -0,0 +1,79 @@
package src
import (
"math"
"gonum.org/v1/gonum/mat"
)
type LogisticRegression struct {
Epochs int
Weights *mat.Dense
Bias float64
Losses []float64
}
func sigmoidFunction(x float64) float64 {
if x < 0 {
return 1. - 1./(1.+math.Exp(x))
}
return 1. / (1. + math.Exp(-x))
}
func (regr *LogisticRegression) backprop(x, y mat.Matrix) float64 {
_, c := x.Dims()
ry, cy := y.Dims()
regr.Bias = 0.1
regr.Weights = mat.NewDense(cy, c, nil)
coef := &mat.Dense{}
coef.Mul(regr.Weights, x.T())
coef.Apply(func(i, j int, v float64) float64 {
return sigmoidFunction(v + regr.Bias)
}, coef)
diff := &mat.Dense{}
diff.Sub(y.T(), coef)
w := &mat.Dense{}
w.Mul(diff, x)
regr.Weights = w
regr.Bias -= 0.1 * (mat.Sum(diff) / float64(c))
// Loss
yZeroLoss := &mat.Dense{}
yZeroLoss.Apply(func(i, j int, v float64) float64 {
return v * math.Log1p(coef.At(i, j)+1e-9)
}, y.T())
yOneLoss := &mat.Dense{}
yOneLoss.Apply(func(i, j int, v float64) float64 {
return (1. - v) * math.Log1p(1.-coef.At(i, j)+1e-9)
}, y.T())
sum := &mat.Dense{}
sum.Add(yZeroLoss, yOneLoss)
return mat.Sum(sum) / float64(ry+cy)
}
func (regr *LogisticRegression) Fit(X, Y mat.Matrix, epochs int) error {
for i := 0; i < epochs; i++ {
loss := regr.backprop(X, Y)
regr.Losses = append(regr.Losses, loss)
}
return nil
}
func (regr *LogisticRegression) Predict(X mat.Matrix) mat.Matrix {
coef := &mat.Dense{}
coef.Mul(X, regr.Weights.T())
coef.Apply(func(i, j int, v float64) float64 {
p := sigmoidFunction(v + regr.Bias)
if p > .5 {
return 1.
}
return 0.
}, coef)
return coef
}

21
regr/src/LogisticRegression_test.go Normal file
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@ -0,0 +1,21 @@
package src
import (
"fmt"
"testing"
)
func TestLogisticRegression(t *testing.T) {
X := [][]float64{{10.1, 10.1, 10.1}, {2.1, 2.1, 2.1}, {10.2, 10.2, 10.2}, {2.2, 2.2, 2.2}}
Y := [][]float64{{0}, {1}, {0}, {1}}
XDense := Array2DToDense(X)
YDense := Array2DToDense(Y)
epochs := 10
regr := &LogisticRegression{}
err := regr.Fit(XDense, YDense, epochs)
if err != nil {
t.Error(err)
}
fmt.Println(regr.Weights, regr.Bias, regr.Losses)
fmt.Println(YDense, regr.Predict(XDense))
}

34
regr/src/utils.go
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@ -1,11 +1,6 @@
//go:build js && wasm
// +build js,wasm
package src
import (
"syscall/js"
"gonum.org/v1/gonum/mat"
)
@ -16,32 +11,3 @@ func Array2DToDense(X [][]float64) *mat.Dense {
}
return dense
}
func JSFloatArray(arg js.Value) []float64 {
arr := make([]float64, arg.Length())
for i := 0; i < len(arr); i++ {
arr[i] = arg.Index(i).Float()
}
return arr
}
func JSFloatArray2D(arg js.Value) [][]float64 {
arr := make([][]float64, arg.Length())
for i := 0; i < len(arr); i++ {
arr[i] = make([]float64, arg.Index(i).Length())
}
for i := 0; i < len(arr); i++ {
for j := 0; j < arg.Index(i).Length(); j++ {
arr[i][j] = arg.Index(i).Index(j).Float()
}
}
return arr
}
func ToJSArray[T any](arr []T) []interface{} {
jsArr := make([]interface{}, len(arr))
for i, v := range arr {
jsArr[i] = v
}
return jsArr
}

37
regr/src/utils_js.go Normal file
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@ -0,0 +1,37 @@
//go:build js && wasm
// +build js,wasm
package src
import (
"syscall/js"
)
func JSFloatArray(arg js.Value) []float64 {
arr := make([]float64, arg.Length())
for i := 0; i < len(arr); i++ {
arr[i] = arg.Index(i).Float()
}
return arr
}
func JSFloatArray2D(arg js.Value) [][]float64 {
arr := make([][]float64, arg.Length())
for i := 0; i < len(arr); i++ {
arr[i] = make([]float64, arg.Index(i).Length())
}
for i := 0; i < len(arr); i++ {
for j := 0; j < arg.Index(i).Length(); j++ {
arr[i][j] = arg.Index(i).Index(j).Float()
}
}
return arr
}
func ToJSArray[T any](arr []T) []interface{} {
jsArr := make([]interface{}, len(arr))
for i, v := range arr {
jsArr[i] = v
}
return jsArr
}