|
| 1 | +import numpy as np |
| 2 | + |
| 3 | +""" |
| 4 | +{'p_gauss_1': array([ 0.07349721, -0.60647022, 1.97806105, -3.22994084, 2.72007585, |
| 5 | + -0.92812989]), |
| 6 | + 'p_gauss_2': array([ 0.08434813, -0.69694429, 2.28047526, -3.73821453, 3.15612997, |
| 7 | + -0.99158461]), |
| 8 | + 'p_q': array([ 0.05712779, -0.47050592, 1.56888875, -2.75649024, 2.71900493, |
| 9 | + -0.28637106]), |
| 10 | + 'p_std': array([ 0.08344418, -0.68630504, 2.21084202, -3.50529186, 2.77854093, |
| 11 | + 0.08576048])} |
| 12 | +""" |
| 13 | + |
| 14 | + |
| 15 | +def eval_xi_1(n): |
| 16 | + """ convert to MAD """ |
| 17 | + p = np.array([0.07349721, -0.60647022, 1.97806105, -3.22994084, 2.72007585, -0.92812989]) |
| 18 | + return 10. ** np.polyval(p, np.log10(n)) |
| 19 | + |
| 20 | + |
| 21 | +def eval_xi_2(n): |
| 22 | + """ convert to MAD """ |
| 23 | + p = np.array([0.08434813, -0.69694429, 2.28047526, -3.73821453, 3.15612997, -0.99158461]) |
| 24 | + return 10. ** np.polyval(p, np.log10(n)) |
| 25 | + |
| 26 | + |
| 27 | +def eval_zeta_q(n): |
| 28 | + """ convert to std """ |
| 29 | + p = np.array([0.05712779, -0.47050592, 1.56888875, -2.75649024, 2.71900493, -0.28637106]) |
| 30 | + return np.polyval(p, np.log10(n)) |
| 31 | + |
| 32 | + |
| 33 | +def eval_zeta_std(n): |
| 34 | + """ convert to std """ |
| 35 | + p = np.array([0.08344418, -0.68630504, 2.21084202, -3.50529186, 2.77854093, 0.08576048]) |
| 36 | + return np.polyval(p, np.log10(n)) |
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