def test_sparse_array_not_dense(self):
ctx = t.Ctx()
dom = t.Domain(ctx, t.Dim(ctx, domain=(1, 8), tile=2),
t.Dim(ctx, domain=(1, 8), tile=2))
att = t.Attr(ctx, "val", dtype='f8')
T = t.SparseArray(ctx, self.path("foo"), domain=dom, attrs=(att, ))
T.dump()
self.assertTrue(T.name == self.path("foo"))
self.assertTrue(T.sparse)
def test_simple_1d_sparse_vector(self):
ctx = t.Ctx()
dom = t.Domain(ctx, t.Dim(ctx, domain=(0, 3), tile=4, dtype=int))
att = t.Attr(ctx, dtype=int)
T = t.SparseArray(ctx, self.path("foo"), domain=dom, attrs=(att, ))
values = np.array([3, 4])
T[[1, 2]] = values
assert_array_equal(T[[1, 2]], values)
def test_sparse_unordered_fp_domain(self):
ctx = t.Ctx()
dom = t.Domain(
ctx, t.Dim(ctx, "x", domain=(0.0, 10.0), tile=2.0, dtype=float))
attr = t.Attr(ctx, dtype=float)
T = t.SparseArray(ctx, self.path("foo"), domain=dom, attrs=(attr, ))
values = np.array([3.3, 2.7])
T[[4.2, 2.5]] = values
assert_array_equal(T[[2.5, 4.2]], values[::-1])
def test_subarray(self):
ctx = t.Ctx()
dom = t.Domain(ctx,
t.Dim(ctx, "x", domain=(1, 10000), tile=100, dtype=int))
att = t.Attr(ctx, "", dtype=float)
T = t.SparseArray(ctx, self.path("foo"), domain=dom, attrs=(att, ))
self.assertIsNone(T.nonempty_domain())
T[[50, 60, 100]] = [1.0, 2.0, 3.0]
self.assertEqual(((50, 100), ), T.nonempty_domain())
# retrieve just valid coordinates in subarray T[40:60]
assert_array_equal(T[40:61]["coords"]["x"], [50, 60])
def test_multiple_attributes(self):
ctx = t.Ctx()
dom = t.Domain(ctx, t.Dim(ctx, domain=(1, 10), tile=10, dtype=int),
t.Dim(ctx, domain=(1, 10), tile=10, dtype=int))
attr_int = t.Attr(ctx, "ints", dtype=int)
attr_float = t.Attr(ctx, "floats", dtype="float")
T = t.SparseArray(ctx,
self.path("foo"),
domain=dom,
attrs=(
attr_int,
attr_float,
))
I = np.array([1, 1, 1, 2, 3, 3, 3, 4])
J = np.array([1, 2, 4, 3, 1, 6, 7, 5])
V_ints = np.array([0, 1, 2, 3, 4, 6, 7, 5])
V_floats = np.array([0.0, 1.0, 2.0, 3.0, 4.0, 6.0, 7.0, 5.0])
V = {"ints": V_ints, "floats": V_floats}
T[I, J] = V
R = T[I, J]
assert_array_equal(V["ints"], R["ints"])
assert_array_equal(V["floats"], R["floats"])
# check error attribute does not exist
# TODO: should this be an attribute error?
V["foo"] = V["ints"].astype(np.int8)
with self.assertRaises(t.TileDBError):
T[I, J] = V
# check error ncells length
V["ints"] = V["ints"][1:2].copy()
with self.assertRaises(AttributeError):
T[I, J] = V