Source code for gfun_57

[docs]def gfun_57(x): """Performance function for reliability problem 57. Parameters ---------- x : numpy.array of float(s) Values of independent variables: columns are the different parameters/random variables (x1, x2,...xn) and rows are different parameter/random variables sets for different calls. Returns ------- g_val_sys : numpy.array of float(s) Performance function value for the system. g_val_comp : numpy.array of float(s) Performance function value for each component. msg : str Accompanying diagnostic message, e.g. warning. """ import numpy as np # expected number of random variables/columns nrv_e = 2 g, g1, g2, g3 = float('nan'), float('nan'), float('nan'), float('nan') msg = 'Ok' x = np.array(x, dtype='f') n_dim = len(x.shape) if n_dim == 1: x = np.array(x)[np.newaxis] elif n_dim > 2: msg = 'Only available for 1D and 2D arrays.' return float('nan'), float('nan'), msg nrv_p = x.shape[1] if nrv_p != nrv_e: msg = f'The number of random variables (x, columns) is expected to be {nrv_e} but {nrv_p} is provided!' else: g1 = -x[:, 0] ** 2 + x[:, 1] ** 3 + 3 g2 = 2 - x[:, 0] - 8 * x[:, 1] g3 = (x[:, 0] + 3) ** 2 + (x[:, 1] + 3) ** 2 - 4 g = [min(max(g1[i], g2[i]), g3[i]) for i in range(len(g1))] gmax12 = np.amax(np.stack((g1, g2)), 0) g = np.amin(np.stack((gmax12, g3)), 0) g_val_sys = g g_val_comp = np.stack((g1, g2, g3)) return g_val_sys, g_val_comp, msg