def test_constructor():
from sklearn_xarray.utils import convert_to_ndarray
coord_1 = ["a"] * 51 + ["b"] * 49
coord_2 = list(range(10)) * 10
X_ds = xr.Dataset(
{"var_1": (["sample", "feature"], np.random.random((100, 10)))},
coords={
"sample": range(100),
"feature": range(10),
"coord_1": (["sample"], coord_1),
"coord_2": (["sample"], coord_2),
},
)
target = Target(transform_func=convert_to_ndarray)
target.assign_to(X_ds)
npt.assert_equal(target.values, np.array(X_ds.var_1))
target = Target(coord="coord_1", transformer=LabelBinarizer())(X_ds)
npt.assert_equal(target.values, LabelBinarizer().fit_transform(coord_1))
def test_constructor():
from sklearn_xarray.utils import convert_to_ndarray
coord_1 = ['a'] * 51 + ['b'] * 49
coord_2 = list(range(10)) * 10
X_ds = xr.Dataset(
{'var_1': (['sample', 'feature'], np.random.random((100, 10)))},
coords={
'sample': range(100),
'feature': range(10),
'coord_1': (['sample'], coord_1),
'coord_2': (['sample'], coord_2)
})
target = Target(transform_func=convert_to_ndarray)
target.assign_to(X_ds)
npt.assert_equal(target.values, np.array(X_ds.var_1))
target = Target(coord='coord_1', transformer=LabelBinarizer())(X_ds)
npt.assert_equal(target.values, LabelBinarizer().fit_transform(coord_1))
