Function test_least_squares

xarray/tests/test_duck_array_ops.py:1094–1106

(use_dask, skipna)

@pytest.mark.parametrize("use_dask", [True, False])
@pytest.mark.parametrize("skipna", [True, False])
def test_least_squares(use_dask, skipna):
    if use_dask and (not has_dask or not has_scipy):
        pytest.skip("requires dask and scipy")
    lhs = np.array([[1, 2], [1, 2], [3, 2]])
    rhs = DataArray(np.array([3, 5, 7]), dims=("y",))

    if use_dask:
        rhs = rhs.chunk({"y": 1})

    coeffs, residuals = least_squares(lhs, rhs.data, skipna=skipna)

    np.testing.assert_allclose(coeffs, [1.5, 1.25])
    np.testing.assert_allclose(residuals, [2.0])


@requires_dask