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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def find_actions(orbit, N_max, force_harmonic_oscillator=False, toy_potential=None):
 r""" Find approximate actions and angles for samples of a phase-space orbit. Uses toy potentials with known, analytic action-angle transformations to approximate the true coordinates as a Fourier sum. This code is adapted from Jason Sanders' `genfunc <https://github.com/jlsanders/genfunc>`_ Parameters orbit : `~gala.dynamics.Orbit` N_max : int Maximum integer Fourier mode vector length, :math:`|\boldsymbol{n}|`. force_harmonic_oscillator : bool (optional) Force using the harmonic oscillator potential as the toy potential. toy_potential : Potential (optional) Fix the toy potential class. Returns ------- aaf : dict A Python dictionary containing the actions, angles, frequencies, and value of the generating function and derivatives for each integer vector. Each value of the dictionary is a :class:`numpy.ndarray` or :class:`astropy.units.Quantity`. """


    if orbit.norbits == 1:
        return _single_orbit_find_actions(
            orbit, N_max,
            force_harmonic_oscillator=force_harmonic_oscillator,
            toy_potential=toy_potential)

    else:
        norbits = orbit.norbits
        actions = np.zeros((3, norbits))
        angles = np.zeros((3, norbits))
        freqs = np.zeros((3, norbits))
        for n in range(norbits):
            aaf = _single_orbit_find_actions(
                orbit[:, n], N_max,
                force_harmonic_oscillator=force_harmonic_oscillator,
                toy_potential=toy_potential)
            actions[n] = aaf['actions'].value
            angles[n] = aaf['angles'].value
            freqs[n] = aaf['freqs'].value

    return dict(actions=actions*aaf['actions'].unit,
                angles=angles*aaf['angles'].unit,
                freqs=freqs*aaf['freqs'].unit,
                Sn=actions[3:], dSn=angles[6:], nvecs=aaf['nvecs'])