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sample_data.py
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sample_data.py
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sample_data_1 = [44.3292, 51.4781, 51.0071, 52.12, 55.9599, 67.7005, 72.8356, 68.3542, 79.8374, 107.3469, 128.9711, 124.085, 136.6139, 133.3496, 135.8623, 130.303, 130.183, 165.3233, 195.6, 333.111, 253.0, 295.2597, 267.5147, 231.3646, 254.5056, 234.9146, 221.717, 225.3853, 210.2138, 254.9637,
239.6841, 240.5701, 229.6369, 225.4714, 226.3814, 240.11, 240.5509, 293.2052, 278.4499, 290.0301, 263.2201, 276.2822, 263.238, 254.5144, 258.5352, 269.7896, 261.4816, 262.935, 264.3023, 264.6513, 254.7976, 255.4646, 248.5236, 233.9466, 255.2105, 269.2234, 268.4263, 275.2991, 311.2962]
sample_data_2 = [264.44, 293.26, 293.36, 299.27, 301.56, 302.56, 304.0, 313.48, 313.8, 317.03, 322.58, 332.38, 332.59, 330.55, 323.43, 334.77, 337.91, 342.39, 356.18, 341.79, 354.32, 371.92, 390.96, 385.66, 410.76, 408.67, 414.05, 415.72, 401.8, 396.15, 431.27, 454.93, 448.74, 448.68, 499.06, 471.62, 503.19, 478.1, 494.5, 486.2, 479.7, 460.3, 463.9, 489.4, 483.7, 488.5, 497.7, 504.8, 496.1, 418.7, 415.0, 421.3, 401.4, 405.1, 416.3, 399.1, 414.3,
431.3, 424.3, 406.6, 410.7, 408.6, 364.1, 344.4, 379.0, 383.5, 355.0, 349.6, 344.0, 335.5, 333.0, 367.7, 387.5, 421.5, 427.1, 430.5, 426.3, 442.1, 434.9, 438.5, 419.2, 421.9, 404.1, 413.1, 444.2, 470.8, 472.7, 474.5,
465.8, 470.9, 484.9, 488.1, 501.3, 470.9, 479.3, 485.5, 475.8, 485.1, 478.1, 448.7]
sample_data_3 = [1.0539, 1.1711, 1.1856, 1.2077, 1.2327, 1.2284, 1.2551, 1.2799, 1.2875, 1.2856, 1.3108, 1.3193, 1.3142, 1.3083, 1.3696, 1.3765, 1.3859, 1.4025, 1.4727, 1.4255, 1.4745, 1.678, 1.7934, 1.8324, 2.1386,
2.1878, 2.1667, 2.0714, 1.9239, 2.1043, 2.4411, 2.4557, 2.4341, 2.7049, 2.9152, 2.7187, 2.739, 2.528, 2.946, 2.847, 2.851, 2.734, 2.767, 2.869, 2.96, 2.966, 2.83, 2.91, 2.833, 2.514, 2.47, 2.518, 2.383, 2.638, 2.581,
2.402, 2.396, 2.505, 2.417, 2.35, 2.371, 2.283, 2.079, 1.986, 2.257, 2.327, 2.277, 2.3, 2.207, 2.13, 2.037, 2.066, 2.115, 2.256, 2.247, 2.251, 2.191, 2.233, 2.209, 2.278, 2.237, 2.268, 2.189, 2.171, 2.118, 2.19, 2.172, 2.218, 2.179, 2.158, 2.128, 2.11, 2.19, 2.137, 2.156, 2.166, 2.12, 2.144, 2.137, 1.912, 1.987, 2.015, 1.955, 1.964, 1.949, 1.971, 2.063, 1.983, 1.982, 2.005, 2.021, 2.125, 2.27, 2.097, 2.079, 2.045, 2.05, 2.04, 2.017, 1.874, 1.876, 1.786, 1.863, 1.922, 1.835, 1.776, 1.751, 1.666, 1.675, 1.533, 1.543, 1.594, 1.601, 1.554, 1.548, 1.719, 1.556, 1.42, 1.378, 1.42, 1.378, 1.396, 1.289, 1.211, 1.354, 1.346, 1.223, 1.266, 1.311, 1.24,
1.218, 1.242, 1.243, 1.237, 1.28, 1.327, 1.475, 1.392, 1.452, 1.455, 1.516, 1.4, 1.332, 1.359, 1.308, 1.38, 1.377, 1.319, 1.309, 1.23, 1.28, 1.21, 1.181, 1.17, 1.123, 1.187, 1.312, 1.233, 1.292, 1.291, 1.41, 1.603, 1.458, 1.337, 1.259, 1.12, 1.071, 1.124, 1.065, 1.043, 1.077, 1.042, 1.048, 1.059, 1.035, 1.051, 1.096, 1.027, 1.061, 1.138, 1.125, 1.143, 1.199, 1.176, 1.195, 1.15, 1.079, 1.059, 1.042, 1.049, 1.107, 1.082, 1.02, 0.995, 0.996, 0.931, 0.856, 0.888, 0.866, 0.853, 0.898, 0.887, 0.856, 0.962, 0.963, 0.939, 0.903, 0.844, 0.864, 0.823, 0.793, 0.802, 0.849, 0.807, 0.788, 0.789, 0.786, 0.802, 0.8, 0.838, 0.835, 0.851, 0.903, 0.879, 0.917,
0.975, 1.108, 1.131, 1.096, 1.152, 1.184, 1.17, 1.191, 1.189, 1.141, 1.165, 1.155, 1.186, 1.212, 1.171, 1.052, 1.089, 1.024, 1.045, 1.027, 0.92, 0.955, 0.974, 0.933, 0.956, 0.951, 0.914, 0.937, 0.952, 0.937, 0.91, 0.906, 0.886, 0.886, 0.8974, 0.8259, 0.8401, 0.8432, 0.8048, 0.7556, 0.7895, 0.7809, 0.7711, 0.8985, 0.7884, 0.7832, 0.7604, 0.7403, 0.6019, 0.6286, 0.5187, 0.4733, 0.529, 0.5372, 0.5981, 0.5569, 0.5778, 0.5059, 0.5334,
0.5162, 0.5286, 0.5416, 0.5134, 0.5219, 0.5146, 0.4789, 0.4566, 0.4646, 0.482, 0.5698, 0.6268, 0.5516, 0.5871, 0.56, 0.5665, 0.5674, 0.6091, 0.6141, 0.6408, 0.6323, 0.5744, 0.554, 0.4904, 0.4644, 0.4831, 0.5348, 0.4762, 0.4872, 0.4549, 0.4848, 0.4915, 0.4813, 0.4594, 0.48, 0.4981, 0.4984, 0.4899, 0.4856, 0.4694, 0.4662, 0.4599, 0.4487, 0.4559, 0.4561, 0.4695, 0.4571, 0.4623, 0.4776, 0.4661, 0.478, 0.4624, 0.4347, 0.4171, 0.4383, 0.4416, 0.4421, 0.4578, 0.4478, 0.4904, 0.5152, 0.491, 0.4993, 0.4828, 0.517, 0.512, 0.4752, 0.4677, 0.5111, 0.513, 0.5218, 0.5263, 0.5144]
sample_data_4 = [1.0539, 1.1711, 1.1856, 1.2077, 1.2327, 1.2284, 1.2551, 1.2799, 1.2875, 1.2856, 1.3108, 1.3193, 1.3142, 1.3083, 1.3696, 1.3765, 1.3859, 1.4025, 1.4727, 1.4255, 1.4745, 1.678, 1.7934, 1.8324, 2.1386, 2.1878, 2.1667, 2.0714, 1.9239, 2.1043, 2.4411, 2.4557, 2.4341, 2.7049, 2.9152, 2.7187, 2.739, 2.528, 2.946, 2.847, 2.851, 2.734, 2.767, 2.869, 2.96, 2.966, 2.83, 2.91, 2.833, 2.514, 2.47, 2.518, 2.383, 2.638, 2.581, 2.402, 2.396, 2.505, 2.417, 2.35,
2.371, 2.283, 2.079, 1.986, 2.257, 2.327, 2.277, 2.3, 2.207, 2.13, 2.037, 2.066, 2.115, 2.256, 2.247, 2.251, 2.191, 2.233, 2.209, 2.278, 2.237, 2.268, 2.189, 2.171, 2.118, 2.19, 2.172, 2.218, 2.179, 2.158, 2.128, 2.11, 2.19, 2.137, 2.156, 2.166, 2.12]