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)