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y_opt.py
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import numpy as np
# optimal solution of MaxDD minimization for n=150
y_opt = np.array([1.34161288e-02, 2.24428676e-03, -5.53379612e-02, 4.21569521e-03
, 2.30809430e-02, -2.30247266e-03, -2.26890356e-02, -5.45670908e-02
, 5.07349527e-02, -1.49720361e-02, 3.74759760e-02, -2.94385500e-02
, 1.16154810e-04, 2.53942959e-02, 3.98846104e-03, -4.22589413e-03
, 4.24454400e-03, 7.41069736e-03, -4.18158542e-03, -1.91603143e-02
, -1.04218576e-03, -5.52308711e-03, 4.36291474e-03, -4.89492477e-03
, -6.65680071e-04, 1.32701682e-03, -6.84300882e-03, -3.86600841e-01
, -1.38254309e-02, -2.49779938e-03, -1.15487217e-02, 7.81151130e-03
, -3.40690298e-01, 9.30244440e-04, 1.18630518e-02, 2.80428169e-03
, 9.71962627e-03, -1.66021734e-02, 5.73835299e-03, 1.81783174e-02
, -2.81796350e-03, 2.68447260e-02, -2.41092132e-03, -2.11453791e-03
, -5.83164891e-03, 1.39517343e-02, -3.56273524e-02, -1.03400731e-02
, 1.38662335e-03, 4.09820097e-02, 1.59877095e-03, 6.92036955e-03
, 8.14253271e-03, 7.80342610e-03, -1.62180247e-02, -2.41472553e-03
, -1.62932652e-02, -1.76342313e-02, 1.91609045e-02, -3.24964785e-03
, 2.22673359e-03, -5.76697002e-03, 2.76180303e-02, -3.19222351e-03
, -3.22831140e-02, 2.61504113e-02, 1.40592220e-02, -8.40204703e-03
, 1.00457704e-02, 1.20530089e-02, -1.05410542e-02, 1.98483418e-02
, -1.15261941e-02, -1.34086138e-02, 1.25424445e-02, -3.91483477e-03
, -4.17770047e-03, 4.83079670e-03, 5.25056145e-02, -1.60983805e-03
, 1.78834230e-02, -1.90497817e-03, -1.70837850e-02, -2.84676255e-02
, -2.75845463e-02, 9.82067743e-03, -1.41731518e-02, -1.69059446e-02
, 1.98828885e-02, 8.79244510e-03, -2.06212831e-02, -4.27323357e-02
, 9.16182684e-03, 7.14102320e-03, -4.68048700e-03, 5.54146759e-03
, 2.23483122e-03, -9.49900883e-03, -4.10077225e-03, -2.12669201e-02
, -3.77906817e-03, -4.19307510e-03, -4.73192680e-03, 1.01058857e-02
, -1.00602760e-02, 1.46678771e-02, -1.15736997e-02, 1.25684073e-02
, 4.92420227e-03, -1.21493968e-02, 1.28904194e-02, -2.84720091e-03
, 6.47263781e-04, -1.90314981e-01, -5.72913534e-03, 1.93041987e-04
, 1.08134588e-02, 3.01496733e-03, 5.67658090e-04, -2.12530892e-03
, 9.94350312e-03, -2.17847309e-03, 1.34505467e-03, 6.10298394e-03
, 4.57530782e-03, -1.06975044e-03, -1.82672678e-02, 1.46565045e-02
, 3.40635038e-04, -1.47524617e-03, 1.36757624e-01, -1.31739278e-01
, -1.52964252e-02, -2.94137438e-04, -6.98861940e-03, 3.46241966e-03
, 1.08969003e-03, -4.77825290e-04, 4.80830050e-02, -4.58291832e-02
, 4.29248145e-03, 4.94979616e-03, 7.20481598e-04, -4.04322777e-03
, 1.27472477e-03, -9.22105803e-04, -5.94748520e-03, 3.30417337e-02
, 8.20031888e-04, -3.85274133e-02])