def test_corr_poly_1(self):
"""
Source: "General formulation of HDMR component functions with
independent and correlated variables", Rabitz/Li, J Math Chem 2011.
Two identical copies of the polynomial taken and added together (on
distinct sets of variables) to increase dimensionality to make this
a more interesting example.
"""
mu = np.array([1.0, 2.0, 3.0, 1.0, 2.0, 3.0])
cov = np.array([
[1.0, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.5, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 1.0, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.5, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 1.0]
])
sample_fn = model_validation.multi_gaussian_sampler(mu, cov)
test_fn = test_functions.gen_corr_poly_1(mu)
m = functools.partial(self.modeler, ord_cap=3, deg_cap=4)
print "Cross-validation relative L2 errors", model_validation.modeler_function_l2_errors(
m, 200, sample_fn, test_fn
)
import model_validation
logging.basicConfig()
mu = np.array([1.0, 2.0, 3.0, 1.0, 2.0, 3.0])
cov = np.array(
[
[1.0, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.5, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 1.0, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.5, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 1.0]
]
)
sample_fn = model_validation.multi_gaussian_sampler(mu, cov)
test_poly = test_functions.gen_corr_poly_1(mu)
n_list = [140]
sample_divisions = 12
out_file = proj_utils.OUT_DIR / 'corr_conv.csv'
def main():
with open(out_file, 'w') as f:
writer = csv.writer(f)
modeler = functools.partial(
cs_hdmr.cs_hdmr_modeler,
ord_cap=2,
deg_cap=5
)
import logging
import cProfile
import proj_utils
import csv
import tests.test_functions as test_functions
import numpy as np
import model_validation
logging.basicConfig()
mu = np.array([1.0, 2.0, 3.0, 1.0, 2.0, 3.0])
cov = np.array([[1.0, 1.0, 0.0, 0.0, 0.0, 0.0], [0.5, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 1.0, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.5, 1.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0,
1.0]])
sample_fn = model_validation.multi_gaussian_sampler(mu, cov)
test_poly = test_functions.gen_corr_poly_1(mu)
n_list = [140]
sample_divisions = 12
out_file = proj_utils.OUT_DIR / 'corr_conv.csv'
def main():
with open(out_file, 'w') as f:
writer = csv.writer(f)
modeler = functools.partial(cs_hdmr.cs_hdmr_modeler,
ord_cap=2,
deg_cap=5)
