def test_compound_transform(self):
table = self.data_str
domain = table.domain
v1 = domain.metas[0]
v1.attributes["a"] = "a"
tv1 = apply_transform(v1, table, [AsContinuous(), Rename("Z1")])
tv2 = apply_transform(
v1, table,
[AsContinuous(),
Rename("Z2"),
Annotate((("a", "b"), ))])
self.assertIsInstance(tv1, ContinuousVariable)
self.assertEqual(tv1.name, "Z1")
self.assertEqual(tv1.attributes, {"a": "a"})
self.assertIsInstance(tv2, ContinuousVariable)
self.assertEqual(tv2.name, "Z2")
self.assertEqual(tv2.attributes, {"a": "b"})
tdomain = Domain([], metas=[tv1, tv2])
ttable = table.transform(tdomain)
assert_array_nanequal(
ttable.metas, np.array([
[0.1, 0.1],
[1.0, 1.0],
], dtype=object))
def test_init_inst(self):
domain = self.create_domain(
["x", DiscreteVariable("g", values="MF")],
[DiscreteVariable("y", values="ABC")],
self.metas,
)
vals = [42, "M", "B", "X", 43, "Foo"]
inst = Instance(domain, vals)
inst2 = Instance(domain, inst)
assert_array_equal(inst2._x, np.array([42, 0]))
self.assertEqual(inst2._y[0], 1)
assert_array_equal(inst2._metas, np.array([0, 43, "Foo"],
dtype=object))
domain2 = self.create_domain(
["z", domain[1], self.metas[1]],
domain.class_vars,
[self.metas[0], "w", domain[0]],
)
inst2 = Instance(domain2, inst)
assert_array_nanequal(inst2._x, np.array([Unknown, 0, 43]))
self.assertEqual(inst2._y[0], 1)
assert_array_nanequal(inst2._metas,
np.array([0, Unknown, 42], dtype=object))
def test_reinterpret_string(self):
table = self.data_str
domain = table.domain
tvars = []
for v in domain.metas:
for i, tr in enumerate(
[AsContinuous(),
AsCategorical(),
AsTime(),
AsString()]):
vtr = apply_reinterpret(v, tr, table_column_data(
table, v)).renamed(f"{v.name}_{i}")
if isinstance(tr, AsTime):
strp = StrpTime("Detect automatically", None, 1, 1)
vtr = apply_transform_var(vtr, [strp])
tvars.append(vtr)
tdomain = Domain([], metas=tvars)
ttable = table.transform(tdomain)
assert_array_nanequal(
ttable.metas,
np.array([
[0.1, 0., np.nan, "0.1", 2010., 0., 1262304000., "2010"],
[1.0, 1., np.nan, "1.0", 2020., 1., 1577836800., "2020"],
],
dtype=object))
def test_init_xym_no_data(self):
domain = self.mock_domain(with_classes=True, with_metas=True)
inst = Instance(domain)
self.assertIsInstance(inst, Instance)
self.assertIs(inst.domain, domain)
self.assertEqual(inst._x.shape, (len(self.attributes), ))
self.assertEqual(inst._y.shape, (len(self.class_vars), ))
self.assertEqual(inst._metas.shape, (3, ))
self.assertTrue(all(isnan(x) for x in inst._x))
self.assertTrue(all(isnan(x) for x in inst._y))
assert_array_nanequal(inst._metas,
np.array([var.Unknown for var in domain.metas],
dtype=object))
def test_reinterpret_string(self):
table = self.data_str
domain = table.domain
tvars = []
for v in domain.metas:
for tr in [AsContinuous(), AsCategorical(), AsTime(), AsString()]:
tr = apply_reinterpret(v, tr, table_column_data(table, v))
tvars.append(tr)
tdomain = Domain([], metas=tvars)
ttable = table.transform(tdomain)
assert_array_nanequal(
ttable.metas,
np.array([
[0.1, 0., np.nan, "0.1", 2010., 0., 1262304000., "2010"],
[1.0, 1., np.nan, "1.0", 2020., 1., 1577836800., "2020"],
],
dtype=object))
def test_init_inst(self):
domain = self.create_domain(["x", DiscreteVariable("g", values="MF")],
[DiscreteVariable("y", values="ABC")],
self.metas)
vals = [42, "M", "B", "X", 43, "Foo"]
inst = Instance(domain, vals)
inst2 = Instance(domain, inst)
assert_array_equal(inst2._x, np.array([42, 0]))
self.assertEqual(inst2._y[0], 1)
assert_array_equal(inst2._metas, np.array([0, 43, "Foo"], dtype=object))
domain2 = self.create_domain(["z", domain[1], self.metas[1]],
domain.class_vars,
[self.metas[0], "w", domain[0]])
inst2 = Instance(domain2, inst)
assert_array_nanequal(inst2._x, np.array([Unknown, 0, 43]))
self.assertEqual(inst2._y[0], 1)
assert_array_nanequal(inst2._metas, np.array([0, Unknown, 42],
dtype=object))
