n_p1 = 360 / inc # number of phi1 samples for FZ n_P = (90 / inc) + 1 # number of Phi samples for FZ n_p2 = 60 / inc # number of phi2 samples for FZ n_tot = n_max**3 # total number of orientations # create file for pre-database outputs f_nhp = h5py.File('var_extract_%s.hdf5' % str(tnum).zfill(2), 'w') a = 0.0050 # start for en range b = 0.0085 # end for en range N = 10 # number of nodes en_inc = 0.0001 # en increment envec = np.arange(0.0001, 0.0100, en_inc) ai = np.int64(np.round(a / en_inc)) - 1 # index for start of en range bi = np.int64(np.round(b / en_inc)) - 1 # index for end of en range sample_indx = lagr.chebyshev_nodes(a, b, ai, en_inc, N) + ai xnode = envec[sample_indx] # en values for nodes of lagrange interpolation print xnode var_set = f_nhp.create_dataset("var_set", (n_max, n_max, n_max, N)) # Read Simulation info from "sim" file filename = 'sim_Ti64_tensor_%s.txt' % str(tnum).zfill(2) f = open(filename, "r") linelist = f.readlines() stmax = linelist[1].split()[4:7] test_no = np.zeros([n_tot], dtype='int8')
n_P = (90 / inc) + 1 # number of Phi samples for FZ n_p2 = 60 / inc # number of phi2 samples for FZ n_en_guess = 10 # desired number of en samples # n_eul is the number of orientations in the sampled db input set n_eul = n_p1 * n_P * n_p2 # here we determine the sampling for en based on the roots of the # chebyshev polynomial a = 0.0050 # start for en range b = 0.0085 # end for en range en_inc = 0.0001 # en increment et_norm = np.linspace(.0001, .0100, 100) ai = np.int64(np.round(a / en_inc)) - 1 # index for start of en range bi = np.int64(np.round(b / en_inc)) - 1 # index for end of en range sample_indx = lagr.chebyshev_nodes(a, b, ai, en_inc, n_en_guess) n_en = sample_indx.size # xnode: en values for nodes of lagrange interpolation xnode = et_norm[sample_indx + ai] print xnode nvec = np.array([n_th, n_p1, n_P, n_p2, n_en]) print "nvec: %s" % str(nvec) # create file for pre-database outputs f_nhp = h5py.File('var_extract_%s.hdf5' % str(tnum).zfill(2), 'w') var_set = f_nhp.create_dataset("var_set", (n_eul * n_en, 6)) # Read Simulation info from "sim" file filename = 'sim_Ti64_tensor_%s.txt' % str(tnum).zfill(2)