3e34371d41f0a1e8ab6df4214c77ace3ca9eac7d,scipy/optimize/least_squares.py,,least_squares,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,148

Before Change

        raise ValueError("Method "lm" doesn"t work when the number of "
                         "residuals is less than the number of variables.")

    if jac in ["2-point", "3-point", "cs"]:
        if method == "lm":
            if jac_sparsity is not None:
                raise ValueError("Usage of method="lm" with `jac_sparsity` "

After Change

    if callable(jac):
        J0 = jac(x0, *args, **kwargs)

        if issparse(J0):
            J0 = csr_matrix(J0)

            def jac_wrapped(x, _=None):
                return csr_matrix(jac(x, *args, **kwargs))
        elif isinstance(J0, LinearOperator):
            def jac_wrapped(x, _=None):
                return jac(x, *args, **kwargs)
        else:
            J0 = np.atleast_2d(J0)

            def jac_wrapped(x, _=None):
                return np.atleast_2d(jac(x, *args, **kwargs))

        if jac_sparsity is not None:
            warn("`jac_sparsity = `%s is ignored." % jac_sparsity)

    else:

Instances