Method test_curvefit_ignore_errors

xarray/tests/test_dataarray.py:5059–5097

(self, use_dask: bool)

    @requires_scipy
    @pytest.mark.parametrize("use_dask", [True, False])
    def test_curvefit_ignore_errors(self, use_dask: bool) -> None:
        if use_dask and not has_dask:
            pytest.skip("requires dask")

        # nonsense function to make the optimization fail
        def line(x, a, b):
            if a > 10:
                return 0
            return a * x + b

        da = DataArray(
            [[1, 3, 5], [0, 20, 40]],
            coords={"i": [1, 2], "x": [0.0, 1.0, 2.0]},
        )

        if use_dask:
            da = da.chunk({"i": 1})

        expected = DataArray(
            [[2, 1], [np.nan, np.nan]], coords={"i": [1, 2], "param": ["a", "b"]}
        )

        with pytest.raises(RuntimeError, match="calls to function has reached maxfev"):
            da.curvefit(
                coords="x",
                func=line,
                # limit maximum number of calls so the optimization fails
                kwargs=dict(maxfev=5),
            ).compute()  # have to compute to raise the error

        fit = da.curvefit(
            coords="x",
            func=line,
            errors="ignore",
            # limit maximum number of calls so the optimization fails
            kwargs=dict(maxfev=5),
        ).compute()

        assert_allclose(fit.curvefit_coefficients, expected)


class TestReduce: