def test_smolyak(self):
import numpy
f = lambda x: numpy.row_stack([
x[0,:] * x[1,:]**0.5,
x[1,:] * x[1,:] - x[0,:] * x[0,:]
])
bounds = numpy.row_stack([
[0.5,0.1],
[2,3]
])
from dolo.numeric.smolyak import SmolyakGrid
sg = SmolyakGrid(bounds,3)
values = f(sg.grid)
sg.fit_values(values)
theta_0 = sg.theta.copy()
def fobj(theta):
sg.theta = theta
return sg(sg.grid)
fobj(theta_0)
def test_smolyak_2(self):
import numpy
from dolo.numeric.smolyak import SmolyakGrid
d = 8
l = 4
bounds = numpy.row_stack([[-0.5]*6, [0.7]*6])
sg = SmolyakGrid(bounds,l)
f = lambda x: numpy.row_stack([
x[0,:] * x[1,:],
x[1,:] * x[1,:] - x[0,:] * x[0,:]
])
values = f(sg.grid)
import time
t = time.time()
for i in range(5):
sg.fit_values(sg.grid)
val = sg(sg.grid)
s = time.time()
print(s-t)
s0 = dr.S_bar
bounds = numpy.row_stack([-std,std])
bounds[:,0] += s0[0]
bounds[:,1] += s0[1]
print('bounds')
print bounds
P = eigs[1]
sg = SmolyakGrid( bounds, 5, P)
[y,x,parms] = model.read_calibration()
xinit = dr( sg.grid)
sg.fit_values(xinit)
from dolo.compiler.compiler_global import CModel, time_iteration, deterministic_residuals
gc = CModel(model)
res = deterministic_residuals(sg.grid, xinit, sg, gc.f, gc.g, dr.sigma, parms)
n_e = 5
epsilons = np.zeros((1,n_e))
weights = np.ones(n_e)/n_e
s0 = dr.S_bar
bounds = numpy.row_stack([-std, std])
bounds[:, 0] += s0[0]
bounds[:, 1] += s0[1]
print('bounds')
print bounds
P = eigs[1]
sg = SmolyakGrid(bounds, 5, P)
[y, x, parms] = model.read_calibration()
xinit = dr(sg.grid)
sg.fit_values(xinit)
from dolo.compiler.compiler_global import CModel, time_iteration, deterministic_residuals
gc = CModel(model)
res = deterministic_residuals(sg.grid, xinit, sg, gc.f, gc.g, dr.sigma, parms)
n_e = 5
epsilons = np.zeros((1, n_e))
weights = np.ones(n_e) / n_e
dr_smol = time_iteration(sg.grid,
sg,
xinit,
gc.f,
import numpy
from dolo.numeric.smolyak import SmolyakGrid
d = 8
l = 4
bounds = numpy.row_stack([[-0.5]*6, [0.7]*6])
sg = SmolyakGrid(bounds,l)
f = lambda x: numpy.row_stack([
x[0,:] * x[1,:],
x[1,:] * x[1,:] - x[0,:] * x[0,:]
])
values = f(sg.grid)
tt = numpy.repeat(sg.grid,40,axis=1)
print tt.shape
import time
t = time.time()
sg.fit_values(sg.grid)
for i in range(5):
val = sg(tt)
s = time.time()
print(s-t)
# unittest.main()
# tt = TestInterpolation()
# # tt.test_2d_interpolation()
# tt.test_smolyak_2()