def test_bug_8278(self):
check_free_memory(8000)
use_solver(useUmfpack=True)
A, b = setup_bug_8278()
A = A.tocsc()
f = factorized(A)
x = f(b)
assert_array_almost_equal(A @ x, b)
def test_ilp64_bisplrep(self):
check_free_memory(28000) # VM size, doesn't actually use the pages
x = np.linspace(0, 1, 400)
y = np.linspace(0, 1, 400)
x, y = np.meshgrid(x, y)
z = np.zeros_like(x)
tck = bisplrep(x, y, z, kx=3, ky=3, s=0)
assert_allclose(bisplev(0.5, 0.5, tck), 0.0)
def setup_method(self):
assert self.n**2 > np.iinfo(np.int32).max
# check there's enough memory even if everything is run at the
# same time
try:
parallel_count = int(os.environ.get('PYTEST_XDIST_WORKER_COUNT', '1'))
except ValueError:
parallel_count = np.inf
check_free_memory(3000 * parallel_count)
def test_concatenate_int32_overflow(self):
""" test for indptr overflow when concatenating matrices """
check_free_memory(30000)
n = 33000
A = csr_matrix(np.ones((n, n), dtype=bool))
B = A.copy()
C = construct._compressed_sparse_stack((A, B), 0)
assert_(np.all(np.equal(np.diff(C.indptr), n)))
assert_equal(C.indices.dtype, np.int64)
assert_equal(C.indptr.dtype, np.int64)
def test_concatenate_int32_overflow(self):
""" test for indptr overflow when concatenating matrices """
check_free_memory(30000)
n = 33000
A = csr_matrix(np.ones((n, n), dtype=bool))
B = A.copy()
C = construct._compressed_sparse_stack((A,B), 0)
assert_(np.all(np.equal(np.diff(C.indptr), n)))
assert_equal(C.indices.dtype, np.int64)
assert_equal(C.indptr.dtype, np.int64)
def test_csr_matmat_int64_overflow():
n = 3037000500
assert n**2 > np.iinfo(np.int64).max
# the test would take crazy amounts of memory
check_free_memory(n * (8*2 + 1) * 3 / 1e6)
# int64 overflow
data = np.ones((n,), dtype=np.int8)
indptr = np.arange(n+1, dtype=np.int64)
indices = np.zeros(n, dtype=np.int64)
a = csr_matrix((data, indices, indptr))
b = a.T
assert_raises(RuntimeError, a.dot, b)
def test_nnz_overflow():
# Regression test for gh-7230 / gh-7871, checking that coo_todense
# with nnz > int32max doesn't overflow.
nnz = np.iinfo(np.int32).max + 1
# Ensure ~20 GB of RAM is free to run this test.
check_free_memory((4 + 4 + 1) * nnz / 1e6 + 0.5)
# Use nnz duplicate entries to keep the dense version small.
row = np.zeros(nnz, dtype=np.int32)
col = np.zeros(nnz, dtype=np.int32)
data = np.zeros(nnz, dtype=np.int8)
data[-1] = 4
s = coo_matrix((data, (row, col)), shape=(1, 1), copy=False)
# Sums nnz duplicates to produce a 1x1 array containing 4.
d = s.toarray()
assert_allclose(d, [[4]])
def test_bug_8278(self):
check_free_memory(8000)
use_solver(useUmfpack=True)
A, b = setup_bug_8278()
x = spsolve(A, b)
assert_array_almost_equal(A @ x, b)
