human
Complete this python program:
def asjacobian(J):
assistant
#Here is the Python program you requested.

    """Convert given object to one suitable for use as a Jacobian.
    """
    spsolve = scipy.sparse.linalg.spsolve
    if isinstance(J, Jacobian):
        return J
    elif (inspect.isclass(J) and issubclass(J, Jacobian)):
        return J()
    elif isinstance(J, np.ndarray):
        if (J.ndim > 2):
            raise ValueError('array    must    have    rank    <=    2')
        J = np.atleast_2d(np.asarray(J))
        if (J.shape[0] != J.shape[1]):
            raise ValueError('array    must    be    square')
        return Jacobian(matvec=(lambda v: dot(J, v)), rmatvec=(lambda v: dot(J.conj().T, v)), solve=(lambda v: solve(J, v)), rsolve=(lambda v: solve(J.conj().T, v)), dtype=J.dtype, shape=J.shape)
    elif scipy.sparse.isspmatrix(J):
        if (J.shape[0] != J.shape[1]):
            raise ValueError('matrix    must    be    square')
        return Jacobian(matvec=(lambda v: (J * v)), rmatvec=(lambda v: (J.conj().T * v)), solve=(lambda v: spsolve(J, v)), rsolve=(lambda v: spsolve(J.conj().T, v)), dtype=J.dtype, shape=J.shape)
    elif (hasattr(J, 'shape') and hasattr(J, 'dtype') and hasattr(J, 'solve')):
        return Jacobian(matvec=getattr(J, 'matvec'), rmatvec=getattr(J, 'rmatvec'), solve=J.solve, rsolve=getattr(J, 'rsolve'), update=getattr(J, 'update'), setup=getattr(J, 'setup'), dtype=J.dtype, shape=J.shape)
    elif callable(J):
        class Jac(Jacobian, ):
            def update(self, x, F):
                self.x = x
            def solve(self, v, tol=0):
                m = J(self.x)
                if isinstance(m, np.ndarray):
                    return solve(m, v)
                elif scipy.sparse.isspmatrix(m):
                    return spsolve(m, v)
                else:
                    raise ValueError('Unknown    matrix    type')
            def matvec(self, v):
                m = J(self.x)
                if isinstance(m, np.ndarray):
                    return dot(m, v)
                elif scipy.sparse.isspmatrix(m):
                    return (m * v)
                else:
                    raise ValueError('Unknown    matrix    type')
        ...