import numpy as np m_values = np.array([1, 2, 4, 8, 16]) b_values = np.array([2, 4, 8, 10, 12]) rank_values = np.array([1, 10, 100, 1000, 10000, 100000, 1000000]) # data point for each triplet (m, b, rank) data_points = np.array([ [ [ 0.0000, 0.0000, 0.0002, 0.0030, 0.0351, 0.3546, 1.0000 ], [ 0.0000, 0.0000, 0.0003, 0.0118, 0.1238, 0.7991, 1.0000 ], [ 0.0000, 0.0005, 0.0039, 0.0423, 0.4085, 0.8569, 1.0000 ], [ 0.0001, 0.0013, 0.0130, 0.1354, 0.6193, 0.9307, 1.0000 ], [ 0.0008, 0.0043, 0.0462, 0.4074, 0.6656, 0.9661, 1.0000 ], [ 0.0013, 0.0170, 0.1551, 0.4910, 0.7592, 0.9849, 1.0000 ] ], [ [ 0.0000, 0.0001, 0.0008, 0.0075, 0.0714, 0.5460, 1.0000 ], [ 0.0000, 0.0003, 0.0064, 0.0637, 0.3915, 0.8876, 1.0000 ], [ 0.0012, 0.0048, 0.0441, 0.2679, 0.6637, 0.9549, 1.0000 ], [ 0.0031, 0.0262, 0.1613, 0.4424, 0.7946, 0.9858, 1.0000 ], [ 0.0132, 0.0863, 0.2694, 0.5927, 0.8843, 0.9958, 1.0000 ], [ 0.0420, 0.1546, 0.3935, 0.7007, 0.9443, 0.9991, 1.0000 ], ], [ [ 0.0001, 0.0002, 0.0038, 0.0305, 0.1924, 0.7969, 1.0000 ], [ 0.0010, 0.0106, 0.0655, 0.2685, 0.6568, 0.9589, 1.0000 ], [ 0.0132, 0.0616, 0.2150, 0.5178, 0.8542, 0.9924, 1.0000 ], [ 0.0373, 0.1378, 0.3770, 0.7154, 0.9491, 0.9988, 1.0000 ], [ 0.0742, 0.2388, 0.5402, 0.8475, 0.9810, 0.9998, 1.0000 ], [ 0.1238, 0.3437, 0.6913, 0.9301, 0.9954, 1.0000, 1.0000 ], ], [ [ 0.0008, 0.0051, 0.0334, 0.1503, 0.4698, 0.9143, 1.0000 ], [ 0.0199, 0.0847, 0.2534, 0.5666, 0.8818, 0.9939, 1.0000 ], [ 0.0749, 0.2259, 0.5120, 0.8242, 0.9777, 0.9998, 1.0000 ], [ 0.1371, 0.3906, 0.7382, 0.9533, 0.9978, 1.0000, 1.0000 ], [ 0.2126, 0.5637, 0.8833, 0.9905, 1.0000, 1.0000, 1.0000 ], [ 0.2916, 0.7062, 0.9579, 0.9984, 1.0000, 1.0000, 1.0000 ], ], [ [ 0.0123, 0.0515, 0.1638, 0.4244, 0.7794, 0.9851, 1.0000 ], [ 0.0886, 0.2809, 0.5858, 0.8701, 0.9875, 0.9997, 1.0000 ], [ 0.2098, 0.5433, 0.8722, 0.9858, 0.9998, 1.0000, 1.0000 ], [ 0.3402, 0.7615, 0.9701, 0.9995, 1.0000, 1.0000, 1.0000 ], [ 0.4506, 0.8898, 0.9965, 1.0000, 1.0000, 1.0000, 1.0000 ], [ 0.5539, 0.9527, 0.9996, 1.0000, 1.0000, 1.0000, 1.0000 ], ]])