x = np.linspace(-20.1, 20.5, 100),
Lr = np.linspace(0.1, 20.0, 50)
),
theta_vars = dict(tau = RV('uniform', 0.7, 1.0),
l = RV('uniform', 5.0, 10.0),
D_f = 26e-3,
E_f = 72e3,
theta = 0.0,
xi = RV('weibull_min', scale = 0.017, shape = 8, n_int = 10),
phi = 1.0,
Ll = 50.0,
# Lr = 1.0
),
n_int = 5)
e_arr = make_ogrid(s.evar_lst)
n_e_arr = [ e / np.max(np.fabs(e)) for e in e_arr ]
max_mu_q = np.max(np.fabs(s.mu_q_arr))
n_mu_q_arr = s.mu_q_arr / max_mu_q
n_std_q_arr = np.sqrt(s.var_q_arr) / max_mu_q
#===========================================================================
# Prepare plotting
#===========================================================================
tdir = tempfile.mkdtemp()
n_img = n_mu_q_arr.shape[0]
fnames = [os.path.join(tdir, 'x%02d.jpg' % i) for i in range(n_img) ]
f = m.figure(1, size = (1000, 500), fgcolor = (0, 0, 0),
bgcolor = (1., 1., 1.))
# This software is provided without warranty under the terms of the BSD
# license included in the Spirrid top directory "licence.txt" and may be
# redistributed only under the conditions described in the aforementioned
# license.
#
# Thanks for using Simvisage open source!
#
#-------------------------------------------------------------------------------
from spirrid import make_ogrid
import numpy as np
evar_names = ['a', 'b', 'c']
evar_lst = [np.arange(1, 5, 1), np.arange(5, 10, 1), np.arange(10, 15, 1)]
e_ogrid = make_ogrid(evar_lst)
def f(a, b, c,):
return a * b * c
def mu_q(*e):
eargs = dict(zip(evar_names, e))
res = f(**eargs)
return res
otypes = [ float for i in range(len(evar_lst))]
mu_q_vec = np.vectorize(mu_q, otypes=[float])
print mu_q_vec(*e_ogrid)