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What is a the Python code you requested given the following:
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def lsim2(system, U=None, T=None, X0=None, **kwargs):

    ''''Simulate output of a continuous-time linear system, by using
    the ODE solver `scipy.integrate.odeint`.
    Parameters
    system : an instance of the `lti` class or a tuple describing the system.
    The following gives the number of elements in the tuple and
    the interpretation:
    * 1: (instance of `lti`)
    * 2: (num, den)
    * 3: (zeros, poles, gain)
    * 4: (A, B, C, D)
    U : array_like (1D or 2D), optional
    An input array describing the input at each time T.  Linear
    interpolation is used between given times.  If there are
    multiple inputs, then each column of the rank-2 array
    represents an input.  If U is not given, the input is assumed
    to be zero.
    T : array_like (1D or 2D), optional
    The time steps at which the input is defined and at which the
    output is desired.  The default is 101 evenly spaced points on
    the interval [0,10.0].
    X0 : array_like (1D), optional
    The initial condition of the state vector.  If `X0` is not
    given, the initial conditions are assumed to be 0.
    kwargs : dict
    Additional keyword arguments are passed on to the function
    `odeint`.  See the notes below for more details.
    Returns
    T : 1D ndarray
    The time values for the output.
    yout : ndarray
    The response of the system.
    xout : ndarray
    The time-evolution of the state-vector.
    Notes
    This function uses `scipy.integrate.odeint` to solve the
    system\'s differential equations.  Additional keyword arguments
    given to `lsim2` are passed on to `odeint`.  See the documentation
    for `scipy.integrate.odeint` for the full list of arguments.
    If (num, den) is passed in for ``system``, coefficients for both the
    numerator and denominator should be specified in descending exponent
    order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).'
    '''
assistant
#Here is the Python code you requested.
    if isinstance(system, lti):
        sys = system._as_ss()
    elif isinstance(system, dlti):
        raise AttributeError('lsim2    can    only    be    used    with    continuous-time    systems.')
    else:
        sys = lti(*system)._as_ss()
    if (X0 is None):
        X0 = zeros(sys.B.shape[0], sys.A.dtype)
    if (T is None):
        T = linspace(0, 10.0, 101)
    T = atleast_1d(T)
    if (len(T.shape) != 1):
        raise ValueError('T    must    be    a    rank-1    array.')
    if (U is not None):
        U = atleast_1d(U)
        if (len(U.shape) == 1):
            U = U.reshape((-1), 1)
        sU = U.shape
        if (sU[0] != len(T)):
            raise ValueError('U    must    have    the    same    number    of    rows    as    elements    in    T.')
        if (sU[1] != sys.inputs):
            raise ValueError(('The    number    of    inputs    in    U    (%d)    is    not    compatible    with    the    number    of    system    inputs    (%d)' % (sU[1], sys.inputs)))
        ufunc = interpolate.interp1d(T, U, kind='linear', axis=0, bounds_error=False)
        def fprime(x, t, sys, ufunc):
            'The    vector    field    of    the    linear    system.'
            return (dot(sys.A, x) + squeeze(dot(sys.B, nan_to_num(ufunc([t])))))
        xout = integrate.odeint(fprime, X0, T, args=(sys, ufunc), **kwargs)
        yout = (dot(sys.C, transpose(xout)) + dot(sys.D, transpose(U)))
    else:
        def fprime(x, t, sys):
            'The    vector    field    of    the    linear    system.'
            return dot(sys.A, x)
        xout = integrate.odeint(fprime, X0, T, args=(sys,), **kwargs)
        yout = dot(sys.C, transpose(xout))
    return (T, squeeze(transpose(yout)), xout)