Testing of the lo package
"""
import nose
from numpy.testing import *
import numpy as np
import linear_operators as lo
from linear_operators.iterative import utils
n = 128
k = n - 1
nk = 3
# collection of linear operators to test
I = lo.identity((n, n))
D = lo.diag(1. + np.arange(n))
C = lo.convolve((n,), kernel=1. + np.arange(nk))
lo_list = [I, D, C.T * C]
# collection of vectors
ones16 = np.ones(n)
def check_cond(A):
Adec = utils.eigendecomposition(A, k=k, which='BE')
assert_almost_equal(Adec.cond(), np.linalg.cond(A.todense()))
def test_cond():
for A in lo_list:
yield check_cond, A
def check_logdet(A):
Testing of the lo package
"""
import nose
from numpy.testing import *
import numpy as np
import linear_operators as lo
from linear_operators.iterative import utils
n = 128
k = n - 1
nk = 3
# collection of linear operators to test
I = lo.identity((n, n))
D = lo.diag(1. + np.arange(n))
C = lo.convolve((n, ), kernel=1. + np.arange(nk))
lo_list = [I, D, C.T * C]
# collection of vectors
ones16 = np.ones(n)
def check_cond(A):
Adec = utils.eigendecomposition(A, k=k, which='BE')
assert_almost_equal(Adec.cond(), np.linalg.cond(A.todense()))
def test_cond():
for A in lo_list:
yield check_cond, A
#!/usr/bin/env python
"""
Testing of the lo.iterative module
"""
import nose
from numpy.testing import *
import numpy as np
import linear_operators as lo
from linear_operators import iterative
# collection of linear operators to test
mat16 = lo.aslinearoperator(np.random.rand(16, 16))
id16 = lo.identity((16, 16))
diag16 = lo.diag(np.random.rand(16))
conv16 = lo.convolve(16, np.random.rand(4), mode="same")
lo_list = [mat16, id16, diag16, conv16]
# collection of vectors
ones16 = np.ones(16)
zeros16 = np.zeros(16)
rand16 = np.random.rand(16)
v_list = [ones16, zeros16, rand16]
# collection of methods
methods = [
iterative.acg,
]
"""
Testing of the lo.iterative module
"""
import nose
from numpy.testing import *
import numpy as np
import linear_operators as lo
from linear_operators import iterative
# collection of linear operators to test
mat16 = lo.aslinearoperator(np.random.rand(16, 16))
id16 = lo.identity((16, 16))
diag16 = lo.diag(np.random.rand(16))
conv16 = lo.convolve(16, np.random.rand(4), mode="same")
lo_list = [mat16, id16, diag16, conv16]
# collection of vectors
ones16 = np.ones(16)
zeros16 = np.zeros(16)
rand16 = np.random.rand(16)
v_list = [ones16, zeros16, rand16 ]
# collection of methods
methods = [iterative.acg, ]
# tests
def check_inv(method, A, x):
y = A * x