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_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_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_as_continuous(self):
table = self.data
domain = table.domain
tr = AsContinuous()
dtr = []
for v in domain.variables:
vtr = apply_reinterpret(v, tr, table_column_data(table, v))
dtr.append(vtr)
ttable = table.transform(Domain(dtr))
assert_array_equal(
ttable.X,
np.array([
[np.nan, 2, 0.25, 180],
[np.nan, 1, 1.25, 360],
[np.nan, 0, 0.20, 720],
[np.nan, 0, 0.00, 000],
],
dtype=float))
def test_reinterpret(self):
var = String("T", ())
for tr in (AsContinuous(), AsCategorical(), AsTime()):
t = report_transform(var, [tr])
self.assertIn("→ (", t)
