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lin reg: only warn on superfluous predictors #361

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lin reg: only warn on superfluous predictors #361

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3 changes: 2 additions & 1 deletion mesmer/stats/_linear_regression.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import warnings
from typing import Mapping, Optional

import numpy as np
Expand Down Expand Up @@ -88,7 +89,7 @@ def predict(
if available_predictors - required_predictors:
superfluous = sorted(available_predictors - required_predictors)
superfluous = "', '".join(superfluous)
raise ValueError(f"Superfluous predictors: '{superfluous}'")
warnings.warn(f"Superfluous predictors: '{superfluous}'")

if "intercept" in exclude:
prediction = xr.zeros_like(params.intercept)
Expand Down
16 changes: 12 additions & 4 deletions tests/unit/test_linear_regression.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,17 +110,25 @@ def test_lr_predict_missing_superfluous():
)
lr.params = params

da = xr.DataArray([0, 1, 2], dims="time")

with pytest.raises(ValueError, match="Missing predictors: 'tas', 'tas2'"):
lr.predict({})

with pytest.raises(ValueError, match="Missing predictors: 'tas'"):
lr.predict({"tas2": None})

with pytest.raises(ValueError, match="Superfluous predictors: 'something else'"):
lr.predict({"tas": None, "tas2": None, "something else": None})
with pytest.warns(UserWarning, match="Superfluous predictors: 'something else'"):
result = lr.predict({"tas": da, "tas2": da, "something else": None})

expected = xr.DataArray([[5, 9, 13]], dims=("x", "time"))
xr.testing.assert_equal(result, expected)

with pytest.raises(ValueError, match="Superfluous predictors: 'bar', 'foo'"):
lr.predict({"tas": None, "tas2": None, "foo": None, "bar": None})
with pytest.warns(UserWarning, match="Superfluous predictors: 'bar', 'foo'"):
result = lr.predict({"tas": da, "tas2": da, "foo": None, "bar": None})

expected = xr.DataArray([[5, 9, 13]], dims=("x", "time"))
xr.testing.assert_equal(result, expected)


@pytest.mark.parametrize("as_2D", [True, False])
Expand Down