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import warnings
from numpy import array, finfo
from numpy.testing import *
from scipy.linalg import norm, inv
from scipy.sparse import spdiags, SparseEfficiencyWarning
from scipy.sparse.linalg.dsolve import spsolve, use_solver
warnings.simplefilter('ignore',SparseEfficiencyWarning)
#TODO add more comprehensive tests
use_solver( useUmfpack = False )
class TestLinsolve(TestCase):
## this crashes SuperLU
#def test_singular(self):
# A = csc_matrix( (5,5), dtype='d' )
# b = array([1, 2, 3, 4, 5],dtype='d')
# x = spsolve(A,b)
def test_twodiags(self):
A = spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]], [0, 1], 5, 5)
b = array([1, 2, 3, 4, 5])
# condition number of A
cond_A = norm(A.todense(),2) * norm(inv(A.todense()),2)
for t in ['f','d','F','D']:
eps = finfo(t).eps #floating point epsilon
b = b.astype(t)
for format in ['csc','csr']:
Asp = A.astype(t).asformat(format)
x = spsolve(Asp,b)
assert( norm(b - Asp*x) < 10 * cond_A * eps )
if __name__ == "__main__":
run_module_suite()
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