def test_padecases_dtype_sparse_float(self):
# float32 and complex64 lead to errors in spsolve/UMFpack
dtype = np.float64
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=SparseEfficiencyWarning)
for scale in [1e-2, 1e-1, 5e-1, 1, 10]:
a = scale * speye(3, 3, dtype=dtype, format='csc')
e = exp(scale) * eye(3, dtype=dtype)
exact_onenorm = _expm(a, use_exact_onenorm=True).toarray()
inexact_onenorm = _expm(a, use_exact_onenorm=False).toarray()
assert_array_almost_equal_nulp(exact_onenorm, e, nulp=100)
assert_array_almost_equal_nulp(inexact_onenorm, e, nulp=100)
def test_padecases_dtype_sparse_float(self):
# float32 and complex64 lead to errors in spsolve/UMFpack
dtype = np.float64
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=SparseEfficiencyWarning)
for scale in [1e-2, 1e-1, 5e-1, 1, 10]:
a = scale * speye(3, 3, dtype=dtype, format='csc')
e = exp(scale) * eye(3, dtype=dtype)
exact_onenorm = _expm(a, use_exact_onenorm=True).toarray()
inexact_onenorm = _expm(a, use_exact_onenorm=False).toarray()
assert_array_almost_equal_nulp(exact_onenorm, e, nulp=100)
assert_array_almost_equal_nulp(inexact_onenorm, e, nulp=100)
def test_padecases_dtype_sparse_float(self):
# float32 and complex64 lead to errors in spsolve/UMFpack
dtype = np.float64
for scale in [1e-2, 1e-1, 5e-1, 1, 10]:
a = scale * speye(3, 3, dtype=dtype, format='csc')
e = exp(scale) * eye(3, dtype=dtype)
with suppress_warnings() as sup:
sup.filter(SparseEfficiencyWarning,
"Changing the sparsity structure of a csc_matrix is expensive.")
exact_onenorm = _expm(a, use_exact_onenorm=True).toarray()
inexact_onenorm = _expm(a, use_exact_onenorm=False).toarray()
assert_array_almost_equal_nulp(exact_onenorm, e, nulp=100)
assert_array_almost_equal_nulp(inexact_onenorm, e, nulp=100)
def test_padecases_dtype_sparse_float(self):
# float32 and complex64 lead to errors in spsolve/UMFpack
dtype = np.float64
for scale in [1e-2, 1e-1, 5e-1, 1, 10]:
a = scale * speye(3, 3, dtype=dtype, format='csc')
e = exp(scale) * eye(3, dtype=dtype)
with suppress_warnings() as sup:
sup.filter(SparseEfficiencyWarning,
"Changing the sparsity structure of a csc_matrix is expensive.")
exact_onenorm = _expm(a, use_exact_onenorm=True).toarray()
inexact_onenorm = _expm(a, use_exact_onenorm=False).toarray()
assert_array_almost_equal_nulp(exact_onenorm, e, nulp=100)
assert_array_almost_equal_nulp(inexact_onenorm, e, nulp=100)
def matrix_exp(A, use_exact_onenorm):
k = 5
import scipy.sparse.linalg.matfuncs as mf
return mf._expm(k*A, use_exact_onenorm)**(1/k)